###### Abstract

Particle therapy is a well established clinical treatment of tumors. More than
one hundred particle therapy centers are in operation world wide. The
advantage of using hadrons like protons or carbon ions as particles for tumor
irradiation is the distinct peak in the depth dependent energy deposition,
which can be exploited to accurately deposit dose in the tumor cells. To
guarantee this, high accuracy of monitoring and control of the particle beam
is of utmost importance. Before the particle beam enters the patient, it
traverses a monitoring system which has to give fast feedback to the beam
control system on position and dose rate of the beam while minimally
interacting with the beam. The multi-wire chambers mostly used as beam
position monitor have their limitations when fast response time is required
(drift time). Future developments like MRI-guided ion beam therapy pose
additional challenges for the beam monitoring system like tolerance of
magnetic fields and acoustic noise (vibrations). Solid-state detectors promise
to overcome these limitations and the higher resolution they offer can create
additional benefits. This article presents the evaluation of an HV-CMOS
detector for beam monitoring, provides results from feasibility studies in a
therapeutic beam and summarizes the concepts towards the final large-scale
assembly and readout system.

###### keywords:

HV-CMOS, ion therapy, high intensity ion-beam monitoring, beam-line
instrumentation, HV-MAPS, radiation-hard detector, silicon sensor

1 1 0 https://doi.org/ A Beam Monitor for Ion Beam Therapy based on HV-CMOS
Pixel Detectors Matthias Balzer 1, Alexander Dierlamm 1,2,∗, Felix Ehrler 1,5,
Ulrich Husemann 2, Roland Koppenhöfer 2, Ivan Perić 1, Martin Pittermann 2,
Bogdan Topko 2, Alena Weber 1,‡, Stephan Brons 3, Jürgen Debus 3,4,6, Nicole
Grau 5,6, Thomas Hansmann 3, Oliver Jäkel 3,7, Sebastian Klüter 5, Jakob
Naumann 3 Correspondence<EMAIL_ADDRESS>
##  1 Introduction

In this section the concept of ion beam therapy is introduced followed by the
requirements for a beam monitoring system and a description of a state-of-the-
art system. This information is based on the beam application and monitoring
system of the Heidelberg Ion beam Therapy center (HIT), but applies to similar
ion beam therapy facilities, too. A short review of alternative beam
monitoring concepts and devices follows. The section concludes with a
description of the newly proposed system.

###  1.1 Ion Beam Therapy

Today, ion beam therapy as a treatment against cancer is well established
after a long history of developments Jäkel et al. (2022). More than one
hundred particle therapy facilities are being operated
today111https://www.ptcog.ch/index.php/facilities-in-operation. Protons or
heavier ions can be well controlled both in energy by the accelerator and in
direction by magnetic deflection in the beam delivery system. The sharply
peaking dose-versus-depth characteristic (Bragg peak) of these hadrons in
tissue, as sketched in Figure 1, allows to control the depth of the deposited
dose in the patient by the energy of the particles.

Figure 1: Energy deposition as a function of penetration depth for photons and
protons. In contrast to photons, protons have a distinct Bragg peak. A spread-
out proton peak can be achieved by superposition of energy depositions from
proton beams of different energies to uniformly irradiate the entire tumor.
From Royce and Efstathiou (2019).

Using a treatment plan with different raster points in different iso-energy
slices (IES), highly conformal irradiation is possible, which maximizes the
damage to the tumor while sparing healthy tissue.
HIT came into clinical operation in 2009 Haberer et al. (2004). It consists of
a chain of ion accelerators designed for the scanning treatment technique
which enables three-dimensional control of particle fluence and hence also
dose. The technique used here is called fluence controlled continuous spot
scanning Haberer et al. (1993) and uses a continuously extracted beam, while
scanning. The lateral motion is stopped at predefined spots until a predefined
number of ions has been delivered, before the beam is quickly moving to the
next spot. Ions are extracted from one of the three ion sources, then
accelerated in a linear accelerator (linac) up to
$7\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ and injected into the
compact synchrotron with a circumference of about $65\text{\,}\mathrm{m}$
after stripping off all electrons. The ions can reach energies of up to
$430\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$. The extracted energy
is controlled directly by the synchrotron and may be varied from spill to
spill to achieve the depth variation. Clinically, carbon ions and protons are
used.

Table 1: Example parameter ranges describing therapeutic particle beams as they are implemented at HIT. Protons and carbon ions are selected here since they are most commonly used for treatments. | Proton | Carbon
---|---|---
Energy (MeV/u) | $48221$ | $88430$
Intensity (${\mathrm{s}}^{-1}$) | $1.2\text{\times}{10}^{8}3.2\text{\times}{10}^{9}$ | $5\text{\times}{10}^{6}8\text{\times}{10}^{7}$
Width (FWHM in mm) | $832$ | $612$

Table 1 provides some basic beam parameters.
The ions are guided through the beam transport line to four irradiation rooms.
Two horizontal irradiation rooms and one room with a
$360\text{\,}\mathrm{\SIUnitSymbolDegree}$ rotating ion gantry are available
for patient treatment Galonska et al. (2013). A fourth room is used for
quality assurance and research activities (QA room), and the measurements with
a particle beam presented in Section 4 have been performed there. All rooms
are equipped for 3D scanning irradiations. An overview of the complex is shown
in Figure 2.

Figure 2: Overview of the accelerator complex (ion sources, linac, synchrotron
and high energy beam transport line (HEBT)) and treatment rooms (H1 and H2 for
the horizontal irradiation rooms, and Q-A for the quality assurance and
experimental irradiation room) at HIT from Kleffner et al. (2009). The large
rotating gantry is on the left.

The accelerator control system can currently provide 255 different energy
settings, 15 intensity steps and six spot sizes for each ion species; for
practical reasons only a subset of the intensity steps and spot sizes is used.
The beam is produced in spills with lengths of up to $5\text{\,}\mathrm{s}$
and intensities up to $3.2\text{\times}{10}^{9}\text{\,}{\mathrm{s}}^{-1}$ for
protons. As the extracted beam intensity is not constant and may vary
considerably during extraction, the monitor system is used to measure the
number of delivered ions at any time. The beam intensity is controlled
dynamically using a feedback loop which involves a monitor chamber Schömers et
al. (2013). A measurement of the number of particles within a spill performed
with an ionization chamber is shown in Figure 3.

Figure 3: Time structure of a spill measured with an ionization chamber taken
from Schömers et al. (2013). The magenta line represents the desired spill
shape, while the green line is the actual measurement. This example is for a
carbon ion beam with
$250\text{\,}\mathrm{M}\mathrm{e}\mathrm{V}\mathrm{/}\mathrm{u}$ and can be
different for other beam settings.

When a predefined number of ions is reached, the feedback loop to the scanner
magnets triggers the movement of the beam to the next raster point Haberer et
al. (1993). The spills can be aborted as soon as all raster points in one IES
have been irradiated and before the energy has to be switched. Fluence
controlled continuous spot scanning requires a fast (typically within
$10\text{\,}\mathrm{\SIUnitSymbolMicro s}$) monitoring and control feedback
loop, which is part of the Beam Application and Monitoring System described in
Section 1.2.
To fully benefit clinically from high precision dose delivery by scanned ion
beams, image guidance in treatment position during the course of the treatment
is mandatory. Real-time imaging can help locating the target volume in moving
tissue and adapting the treatment plan during irradiation, but is currently
not available for ion beams. Unlike x-ray based computed tomography (CT),
magnetic-resonance imaging (MRI) offers superior soft tissue contrasts and
good discrimination between tumor and normal tissue. Moreover, it is not based
on ionizing radiation and does not lead to additional imaging dose, which
makes it suitable for continuous monitoring. For photon-based radiotherapy,
the first hybrid treatment system came to the market in 2014 and combines
$0.35\text{\,}\mathrm{T}$ MRI with intensity modulated radiotherapy. While
this initial system was based on Co-60 sources, linac based systems are
available since 2016. This system was also implemented for clinical use in
Heidelberg Klüter (2019). In contrast, MR-based image guidance for ion beam
therapy is technologically even more challenging and its development is still
in a very early phase. Recently, studies on the realization of MRI-guided
proton therapy have started with several challenges ahead Hoffmann et al.
(2020). Within the ARTEMIS222Adaptive RadioThErapie Mit IonenStrahlen, funded
by BMBF project in Heidelberg, a demonstrator system is under development to
implement MRI-guided ion beam delivery including online MR imaging of the
target region during irradiation. Specifically, beam control and beam
monitoring in the presence of an active MRI device need to cope with magnetic
fields and acoustic noise, which specifically poses a problem for MWCs with
thin windows (vibrations), and may thus call for alternative detector
technologies.

###  1.2 Beam Monitoring

The beam monitoring system needs to provide information about the position and
particle number at each raster point and is placed close to the patient.
Additionally, control of the beam spot size is desirable, although this is not
actively controlled during beam delivery. The requirements for a next-
generation beam monitoring system at HIT can be formulated as follows:

  * •

Position measurement: The beam position can be calculated as the center of
gravity of the induced signals. The accuracy of the calculated position shall
be better than $200\text{\,}\mathrm{\SIUnitSymbolMicro m}$.

  * •

Spot size measurement: The accuracy of the calculated beam spot width shall be
better than 10% for a Gaussian shape.

  * •

Fluence measurement: The number of particles needs to be counted for each
raster point. The particle numbers (>$10\,000$ carbon ions; >$200\,000$
protons) shall be measured with 0.5% accuracy.

  * •

Timing and latency: The position and spot size shall be measured within
$100\text{\,}\mathrm{\SIUnitSymbolMicro s}$ and delivered to the fast control
interface within $100\text{\,}\mathrm{\SIUnitSymbolMicro s}$ latency. An
updated value shall be delivered to the fast interface every
$1\text{\,}\mathrm{\SIUnitSymbolMicro s}2\text{\,}\mathrm{\SIUnitSymbolMicro
s}$ for the fluence measurement and every
$50\text{\,}\mathrm{\SIUnitSymbolMicro
s}100\text{\,}\mathrm{\SIUnitSymbolMicro s}$ for the position and width
measurement.

  * •

Radiation tolerance: The system shall be operable for at least five years. For
the central position, where the maximum accumulated dose is expected (few
mm2), this corresponds to a particle fluence of
$3\text{\times}{10}^{14}\text{\,}{\mathrm{cm}}^{-2}$ with carbon ions and
$3\text{\times}{10}^{15}\text{\,}{\mathrm{cm}}^{-2}$ with protons, which falls
off very fast with increasing radial distance. This very localized radiation
damage might be an additional challenge for the detector. The radiation damage
deteriorates the performance of the system, which needs to be replace
regularly. The regular replacement and recommissioning after five years
operation shall not take longer than one day. More frequent replacements shall
not last longer than two hours.

  * •

Size of sensitive area: The overall active area shall be
$$25\text{\,}\mathrm{cm}$\times$25\text{\,}\mathrm{cm}$$ to cover the
treatment area of $$20\text{\,}\mathrm{cm}$\times$20\text{\,}\mathrm{cm}$$
including penumbra.

  * •

Dimensions: The thickness of the outer housing shall be smaller than
$5\text{\,}\mathrm{cm}$ and fit in a cylinder of $60\text{\,}\mathrm{cm}$
diameter. The material shall correspond to a water equivalent thickness of
less than 0.35 mm.

  * •

Environment: The detector must tolerate light, acoustic noise and magnetic
fields of at least $100\text{\,}\mathrm{mT}$ in the fringe field of an MRI
system (magnetic fields in the iso-center can reach up to
$1.5\text{\,}\mathrm{T}$).

The current beam monitoring system at HIT consists of two multi-wire chambers
(MWC, see e.g. Sauli (1977)) each with one plane for x- and y-direction to
measure position and spot size and three ionization chambers (IC) to track the
applied dose. The MWC have a channel pitch of $2\text{\,}\mathrm{mm}$, but
only a projection of the beam spot can be measured. The signal from the first
MWC is used to control a feedback loop for the beam position, the position is
monitored by the second MWC. If the deviation between both measurements of
position and width exceeds a threshold, a beam interlock is triggered. Both
chambers are also used to derive a spot size measurement, on which an
interlock is defined, in case upper and lower thresholds are exceeded. The
integrated signal from the first IC controls the progress of the irradiation,
and the beam is moved to the next raster point when the desired dose is
reached. The other two ICs serve as independent checks of the particle fluence
and ensure redundancy and diversity. If the deviation between the ICs exceeds
a threshold, a beam interlock is triggered.
The MWCs, apart from their resolution, have some limitations which restrict
their field of application. The concept of gas ionization and drift of charge
carriers is limited to the drift velocity of the ions in gas. The signal is
slightly delayed with respect to the first particles traversing the detector
and there is still ion drift left when the particles have disappeared. These
delays can be up to several hundreds of microseconds Lin et al. (2009), which
delays the interlocks, so that several raster points may be affected, before
abort. The performance of MWCs can also be affected by acoustic noise which
can lead to vibrations of the wires and therefore deterioration of the
resolution. One possible source of such acoustic noise can be an MRI system
used for online position control of the target. At the HIT QA room, an MRI
system (Section 3.2) for developing MRI-guided ion beam therapy is available
for testing the behavior of novel beam monitors.

###  1.3 Alternative Beam Monitoring Concepts and Devices

For more than 10 years, the community has been searching for improved
detectors for high-rate beam monitoring. This section has no intention to be
complete, but rather give a short introduction into some recent attempts. An
extensive review is given, for example, in Giordanengo et al. (2017).
Some approaches are gas-based as the Time Projection Chamber-like approach
described in Wang et al. (2017), improved segmented ionization strip chambers
with spatial resolution of $100\text{\,}\mathrm{\SIUnitSymbolMicro m}$ in
Actis et al. (2014) or a more vibration tolerant version of an ionization
chamber in Lin et al. (2009). They all have in common that the charge
collection time is in the order of milliseconds and very fast feedback on the
timescale of few hundred microseconds is not possible.
One different approach is the measurement of the magnetic field of the
deflecting magnets in the beam delivery system. The field strength is
proportional to the final position of the beam spot and provide a very fast
($10\text{\,}\mathrm{\SIUnitSymbolMicro s}$) and precise
($10\text{\,}\mathrm{\SIUnitSymbolMicro m}$) beam position measurement Klimpki
et al. (2017). One drawback might be that the measurement is performed at
quite a distance (more than about $5\text{\,}\mathrm{m}$) to the patient and
the beam could be deflected by other sources, e.g. the magnetic field of an
MRI, on its path. In addition, remanence effects and dependencies on the beam
position in the beam line can deteriorate the projected beam position at the
target.
Scintillating fibers coupled to silicon photomultipliers (SiPM) are already
used as fast, large area beam monitor Papa (2016); Ortega Ruiz et al. (2019);
Allegrini et al. (2021). The drawback here is the weak radiation tolerance,
which is limited to 1000 patient treatments for the device in Allegrini et al.
(2021). Additionally, a reduction of the attenuation length below 10% after a
dose of about $50\text{\,}\mathrm{kGy}$ is indicated in Joram et al. (2015).
Using photo diodes to read out scintillating fibers is investigated in
Leverington et al. (2018). There, it is also suggested to use fibers with
higher radiation hardness not only as natural attempt to overcome this
weakness but also to profit from the shift in the emitted light spectrum.
An interesting attempt based on silicon is documented in Martišíková et al.
(2011). The investigated large-scale detector
($$20\text{\,}\mathrm{cm}$\times$20\text{\,}\mathrm{cm}$$) is a commercial
amorphous silicon based x-ray imager, but in this case applied to an ion beam.
The resolution and stability over a period of four hours was very good, but
the readout time was still high
($80\text{\,}\mathrm{m}\mathrm{s}\mathrm{/}\mathrm{f}\mathrm{r}\mathrm{a}\mathrm{m}\mathrm{e}$).
The radiation tolerance over a period of one year needs to be evaluated.
Another promising silicon detector type are Ultra Fast Silicon Detectors
(UFSD) based on thin Low Gain Avalanche Detectors (LGAD). Three examples of
applying this detector type in particle therapy applications can be found in
Sacchi et al. (2020); Vignati et al. (2020); Krüger et al. (2022). These
detectors can be used for very fast timing applications like time-of-flight
detector systems. The good time resolution of better than
$100\text{\,}\mathrm{ps}$ is a result of the intrinsic signal gain of these
devices, which is about 10 to 20. This gain (and the time resolution) is
reduced significantly after irradiation. A gain reduction of 20% after a
fluence of $1\text{\times}{10}^{12}\text{\,}{\mathrm{cm}}^{-2}$ is quoted in
Sacchi et al. (2020). This is small compared to the yearly expected fluence in
the center of a beam monitoring detector. This detector type requires external
readout electronics. For a pixellated layout, the readout electronics needs to
be connected via bump bonds to the LGAD, adding material and complexity during
the assembly.
To avoid the interconnection step, reduce material and bring the first signal
amplification stage close to the generated signal, monolithic detector chips
have been developed. In Flynn et al. (2022) a commercial large scale CMOS
detector for x-ray imaging was evaluated as proton beam monitor. The
determination of the beam profile was demonstrated to reproduce measurements
with films with minor deviations as long as saturation is not reached. The
rolling shutter readout mode of this device limits the readout speed and a
full readout of the $$12\text{\,}\mathrm{cm}$\times$14\text{\,}\mathrm{cm}$$
large matrix leads to saturation effects already at low beam currents. For
this device, no evaluation of the radiation tolerance was reported in Flynn et
al. (2022).

###  1.4 A Beam Monitor Based on HV-CMOS Detectors

In this article, a novel approach is discussed based on custom HV-CMOS
detectors, introduced in Section 2. These monolithic devices combine the
sensing element with signal processing in one thin silicon chip. For fast
readout, the chips implement particle counting and projection of particle
counts on the x- and y-axis. The reticle-sized chips will be arranged in a
$13\times 13$ array to achieve the required active area of
$$25\text{\,}\mathrm{cm}$\times$25\text{\,}\mathrm{cm}$$ and interconnected by
thin flex PCBs to the surrounding electronics, where electrical signals are
converted to optical signals which allow stable data transmission to a fast
field-programmable gate array (FPGA) board for further data processing. The
chip array is mounted on thin carbon fiber plates for mechanical and thermally
dissipative support.

Figure 4: Schematic 3D rendering of the full size matrix with $13\times 13$
chips (2), interconnected by flex cables (3), assembled on a thin carbon fiber
plate (1). The surrounding electronic boards (4) are mounted on a stabilizing
frame (5).

Figure 4 shows a schematic 3D rendering of the final detector design.
After the introduction of the chip technology in Section 2, the systems and
facilities used for the characterizing measurements are described in Section 3
and, finally, the evaluation of the detector and system performance is
discussed in Section 4.

##  2 A Beam Monitoring Chip based on HV-CMOS Technology

###  2.1 Silicon Sensor Technology

Particle detectors made of silicon base material are widely used in
experimental particle physics Hartmann (2011) and proposed for usage in
radiotherapy for many years Bruzzi (2016). They are operated in high magnetic
fields (up to $3.8\text{\,}\mathrm{T}$) and high particle fluxes (up to
$3.5\text{\,}\mathrm{GHz}\text{\,}{\mathrm{cm}}^{-2}$). The basic building
blocks are pn-junctions operated in reverse bias. Traversing charged particles
generate electron-hole pairs by ionization (about 75 per
$\mathrm{\SIUnitSymbolMicro m}$) in the depleted silicon bulk and the readout
electronics detects the produced current pulses. For hybrid systems, the
readout electronics is implemented on dedicated ASICs which are connected to
the silicon sensor by wire bonds in case of planar strip sensors or bump bonds
for pixelated sensors Hartmann (2017); Lutz (2007). The hybrid approach allows
to combine a specialized sensor with specialized readout electronics, which
are developed independently. Still, the hybridization requires additional and
potentially expensive production steps. It also limits the granularity and
mass (saving) of the final detector. An alternative are monolithic devices
described in the next section.

###  2.2 The HV-CMOS Technology

CMOS technology allows to combine the sensitive pn-junction with the readout
electronics on one thin (less than $150\text{\,}\mathrm{\SIUnitSymbolMicro
m}$) chip. While keeping the high granularity of a pixel sensor, this approach
avoids the additional readout chip (reducing material thickness) and the
connectivity step (reducing costs). The radiation environment in experimental
particle physics and beam monitoring calls for silicon chips with increased
radiation tolerance. One possibility is to use a commercially available High-
Voltage CMOS (HV-CMOS) process Perić et al. (2011). This technology allows to
apply a bias voltage of up to about $300\text{\,}\mathrm{V}$ generating a wide
depletion zone (typically $35\text{\,}\mathrm{\SIUnitSymbolMicro
m}50\text{\,}\mathrm{\SIUnitSymbolMicro m}$). Generated charge carriers are
then collected by fast drift (order of few $\mathrm{ns}$) in the electric
field and not only by slow diffusion as in standard CMOS devices. The faster
drift reduces the effect of charge carrier trapping Moll (1999) in irradiated
silicon and more charge carriers are generated in the wider depletion zone
yielding a higher signal. At least the electronics of the first steps of
signal processing is located inside the pixels (smart diode). Typically, also
signal amplification and digitization circuits are added. Combining improved
radiation tolerance with integrated electronics and small pixel sizes makes
the HV-CMOS technology a promising candidate for a beam monitoring system.
Several HV-CMOS based detectors have been developed for particle physics
experiments so far Arndt et al. (2021); Augustin et al. (2020); Schimassek et
al. (2021); Perić et al. (2021).

###  2.3 An HV-CMOS Detector for Beam Monitoring

The beam monitoring detector chip HitPix has been developed in
$180\text{\,}\mathrm{nm}$ HV-CMOS technology and was produced in two
generations. HitPix1 has $24\times 24$ pixels, is
$$5\text{\,}\mathrm{mm}$\times$5\text{\,}\mathrm{mm}$$ in size and is
described in detail in Weber et al. (2022); Weber (2021). HitPix2 has
$48\times 48$ pixels, is
$$10\text{\,}\mathrm{mm}$\times$10\text{\,}\mathrm{mm}$$ in size and is the
generation investigated in this article. The dimensions of a detector chip for
the envisaged final beam monitoring system will be
$$20\text{\,}\mathrm{mm}$\times$20\text{\,}\mathrm{mm}$$ with $96\times 96$
pixels. In this section, only the main features of the HitPix family in view
of the targeted application are summarized.
The very high particle rates can be processed by counting the particle
transitions in each pixel cell during a programmable period of several
microseconds. One hit is registered when the induced signal of a charged
particle traversing a pixel cell passes a programmable threshold, which needs
to be optimized with respect to noise and induced signal. The hit counts are
accumulated over a programmable time period. The resulting count status of the
pixel matrix is called frame. One frame can then be read out, either for each
pixel of the matrix (_counter readout_ , slow) or for the sums of each row and
column (_adder readout_ , fast), which are calculated on-chip. In the counter
readout mode the readout takes longer since more data
($129\,024\text{\,}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{s}$ per frame for the
final chip) is handled. It is used for debugging or detailed beam diagnostics,
since some skewed beam shapes can only be detected with two-dimensional
measurements. In the adder readout mode, the projected data
($2688\text{\,}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{s}$ per frame for the
final chip) can be read out 48 times faster, while the pixel hit counting
continues. The adding step happens quasi instantaneous when any counter in the
corresponding row/column is increased, and all sums are transferred to the
shift register by one load pulse when the readout is triggered.

(a) Components in the pixel cell

(b) Pixel matrix readout in counter mode

(c) Pixel matrix readout in adder mode

Figure 5: Illustration of the hit counting and adding features of the HitPix.
In (a), the signal from the sensitive diode (Sensor diode) is amplified (Amp)
and a threshold is applied in the comparator (Comp). The hits are counted and
stored in the counter. This value can either be read out via the counter bus
(left path in (a), and (b)), or added to the sum being propagated from the
preceding pixel and then passed on to the next pixel (blue path in (a) , and
(c)).

The concept is illustrated in Figure 5.
It is clear that the projections in adder readout mode do not contain the full
information on the beam shape, but the most relevant like position and width.
The shape is typically constant on the scale of an irradiation day, therefore
the projections of the beam profile are sufficient to generate a fast
interlock in case the beam behaves unexpectedly.
The required pixel size was evaluated from cluster size measurements with
available HV-CMOS detectors featuring a similar charge collecting diode
structure, but smaller pixels, and the requirement to reach at least
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ position resolution. The
ionization of therapeutic ions is much larger than minimum ionizing particles
as they typically appear in particle physics experiments. Protons in the range
given in Table 1 generate two to six times more charge and carbon ions 50 to
135 times more. Although the deposited charge is much higher, the average
cluster size was measured to be below two pixels for
$$150\text{\,}\mathrm{\SIUnitSymbolMicro
m}$\times$50\text{\,}\mathrm{\SIUnitSymbolMicro m}$$ pixels for these type of
ions Schimassek (2021). This concludes that the charge of one particle can be
well contained in a $$200\text{\,}\mathrm{\SIUnitSymbolMicro
m}$\times$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$$ pixel also fulfilling
the requirement for a resolution of at least
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$.
Another aspect for the chip design is a narrow inactive periphery, which was
achieved by locating data processing (analog-to-digital converters, hit
counters, hit adders) and data storage inside each pixel. The periphery houses
only configuration storage and a simple shift register readout.
The HitPix2 is prepared for daisy-chain readout of several detectors to
minimize readout lines on the interconnecting cable, when moving to a multi-
chip array. The chain can be up to seven detectors long. For the final system,
the detectors will have $96\times 96$ pixels and two projections with
$14\text{\,}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{s}$ per line. This results
in $18\,816\text{\,}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{s}$ for a chain
containing seven detectors to be read out in adder mode during the integration
time of one frame, which is in the order of
$20\text{\,}\mathrm{\SIUnitSymbolMicro s}$ depending on the beam intensity. To
achieve this, a data rate of about $1\text{\,}\mathrm{GHz}$ is required. In
case the readout time for many detectors in a daisy-chain turns out to not
meet the specifications, each detector has an additional direct readout
option. In this mode the selection of individual detectors for readout is
possible to define a region-of-interest for each frame and, to save data
traces on the flex cable, allows using a common data bus structure sharing the
signals of some detectors on one line.

##  3 Irradiation Facility and Test Systems

###  3.1 Irradiation facility

To accumulate a significant particle fluence in short time, a compact
cyclotron with $23\text{\,}\mathrm{MeV}$ protons was used. The cyclotron is
operated by the company ZAG Zyklotron AG333https://www.zyklotron-
ag.de/index.php (ZAG) and situated on the Campus North of KIT. The beam has a
width of about $8\text{\,}\mathrm{mm}$ (FWHM) and the beam current is set to
about $2\text{\,}\mathrm{\SIUnitSymbolMicro A}$ for irradiation of the
detectors. At this beam current, the samples are irradiated to the target
fluence of around $1\text{\times}{10}^{15}\text{\,}{\mathrm{cm}}^{-2}$ within
$15\text{\,}\mathrm{min}$. The samples are placed inside an insulated box
which is flushed with cold nitrogen gas (below
$-20\text{\,}\mathrm{\SIUnitSymbolCelsius}$). The box is scanned in front of
the beam to achieve a uniform irradiation of the samples. The damage to the
silicon lattice caused by these protons can be converted into an equivalent
damage caused by $1\text{\,}\mathrm{MeV}$ neutrons by the non-ionization
energy loss (NIEL) hypothesis Lindström et al. (1999). The particle fluence
$F_{\mathrm{particle}}$ can be converted to the equivalent fluence as
$F_{\mathrm{eq}}=\kappa\times F_{\mathrm{particle}}$. The corresponding
scaling factor is called hardness factor $\kappa$, with $\kappa=2.0$ for
$23\text{\,}\mathrm{MeV}$ protons.

###  3.2 Magnetic Field Test Environments

The HV-CMOS technology does not only have the potential to improve the
performance of the existing beam monitoring system, but the tolerance of
silicon sensors towards magnetic fields promises the simultaneous irradiation
and MR imaging of the target. While most sensor technologies can be operated
in a certain distance to the high field region of an MRI system, HV-CMOS
sensors are expected to work within the center of the field. HIT has built a
large scale Helmholtz coil pair with an inner diameter of
$60\text{\,}\mathrm{cm}$ for measurements in a magnetic field of up to
$100\text{\,}\mathrm{mT}$ under lab condition. A picture of the setup is shown
in Figure 6(a).

(a) Helmholtz coil pair

(b) MRI system

Figure 6: Pictures of the Helmholtz coil pair (a) and MRI system (b). Both are
used for measurements at HIT. The Helmholtz coils allow in-beam
characterization of devices up to a static magnetic field of
$100\text{\,}\mathrm{mT}$. In the MRI system, the ion beam enters from the
right side through the wave guide. The whole setup is located inside a movable
enclosure for shielding the stray fields. Image source: HIT.

It was used for basic measurements in a static field with the HV-CMOS
detectors.
In order to measure the effect on the detector of the even stronger field of
an MRI magnet and its alternating field during scanning, an MRI
system444Esaote S-Scan compact was used which is available in the QA room at
HIT with a static magnetic field of $250\text{\,}\mathrm{mT}$. The MRI system
is located inside an enclosure for shielding the stray fields as shown in
Figure 6(b). The whole setup can be moved into the beam for experiments. It
was used for the tests reported in Section 4.6.

###  3.3 Data Acquisition System

The test system to control and read out the detectors is split into four
parts.
The detectors are mounted and wire-bonded on a simple PCB called _carrier_.
The carrier can be plugged into a PCIe socket of the GEneric Configuration and
COntrol board (GECCO) Ehrler (2021); Schimassek (2021). GECCO provides all
necessary supply voltages, test signals and routes data lines from and to an
FPGA. In this case, a Nexys Video Artix-7 FPGA
board555https://digilent.com/shop/nexys-video-artix-7-fpga-trainer-board-for-
multimedia-applications/ is used.
The firmware to control the detector implements a state machine. Communication
to the HitPix detector is established via a two phase shift register driven by
the FPGA with up to
$200\text{\,}\mathrm{M}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{/}\mathrm{s}$.
Finally, the hardware is connected to a PC by USB. The software interacting
with the FPGA uses multi-threading to receive and decode data from the FPGA as
quickly as possible while online data processing can continue.
Figure 7 shows a block diagram of the data acquisition chain with the
different elements and the data streams.

Figure 7: Block diagram of the data acquisition chain with the four
components: PC, FPGA board, GECCO board and carrier board for the detector.
Communication and data paths are indicated between the blocks.

##  4 Detector Characterization and Evaluation as a Beam Monitoring Device

This section summarizes the characterization of the detector technology and
describes the evaluating studies in view of the beam monitoring application
performed so far.

###  4.1 Technology Decisions

Since the beam monitoring detector should register nearly all traversing
particles, the insensitive regions need to be very small. Therefore, the
insensitive periphery of the detector can only occupy a small fraction of the
overall detector area. This is possible by using simple and area saving
building blocks for the communication part and moving data processing blocks
into the pixel cells.
The first version of HitPix has been produced in two flavors. One is designed
in standard technology (STD) with separated charge collecting diode and deep
n-well housing the electronics. The other flavor (ISO design) has additional
deep p-wells isolating the shallow n-wells from the common deep n-well
allowing for the collection diode to cover the whole pixel area. This
difference is visualized in Figure 8.

(a) Standard cell with separated n-wells (STD)

(b) Common n-well design with isolating deep p-well (ISO)

Figure 8: Pixel cross sections of the two designs. In the STD design the
n-wells are separated for the charge collecting diodes and electronics (a). A
common n-well enlarges the collecting diode, but requires deep p-wells to
isolate the electronics (b). After Weber et al. (2022).

Illuminating the pixel cells with an infrared laser from the backside
confirmed that the area below the electronics part of the standard design is
insensitive to the generated charge, while the design with the isolating deep
p-well is sensitive in the entire pixel cell. Figure 9 shows that about one
third of the STD pixel cell area is insensitive in this measurement.

(a) Signal height map for the STD design

(b) Signal height map for the ISO design

Figure 9: Signal height distribution measured on one pixel cell during
illumination of the detectors with an infrared ($904\text{\,}\mathrm{nm}$)
laser from the backside for the STD cell (a) and the ISO cell (b). The laser
spot size was about $10\text{\,}\mathrm{\SIUnitSymbolMicro m}$ (FWHM) while
the spatial step size was $1\text{\,}\mathrm{\SIUnitSymbolMicro m}$. The setup
is described in more detail in Schimassek (2021). The analog signal of the
pixel can be read out on a dedicated output line.

This effect was expected, since this is the fraction of the pixel cell
occupied by the electronics part. However, the clusters by protons and carbon
ions are sufficiently large so that even a particle passing in the middle of
the insensitive area will still leave a signal in the adjacent pixel diodes.
Even if this was not the case, the inefficiency would be predictable and on
average the lost signal could be corrected for.
Another effect of the common deep n-well in the ISO design is an increase in
detector capacitance, leading to smaller and shorter induced signals, which
could lead to a critically low signal-to-noise ratio with minimum ionizing
particles. The signals from an ion beam, however, are comparably large
(Section 2.3) and could provoke extended dead times while the signals exceed
the threshold. In this case, shorter signals would be beneficial to increase
the rate capability.
The radiation tolerance of the detector needs to be addressed already at the
design stage. Therefore, the design of HitPix2 uses p-MOS electronics where
possible and enclosed n-MOS transistors where needed. Besides being more
radiation tolerant Snoeys et al. (2000), an amplifier built solely with n-MOS
transistors requires only one supply voltage. This reduces the number of power
supply pads and, therefore, inactive area in the periphery.
The depth of the depleted zone and the electric field below the collecting
diode depends on the substrate resistivity and bias voltage, and has a
significant effect on the induced signal. Three different resistivities of the
silicon substrate have been tested with HitPix2 and the results are discussed
in Section 4.3.
The chip is designed for low power consumption to minimize the challenges of
cooling the matrix in this low mass application. The total power consumption
measured on HitPix2 is $20\text{\,}\mathrm{\SIUnitSymbolMicro W}$ per pixel or
$47\text{\,}\mathrm{mW}\text{\,}{\mathrm{cm}}^{-2}$, split into equal
fractions for analog and digital power. This is comparable to other low power
CMOS detectors like the ALPIDE chip with
$40\text{\,}\mathrm{mW}\text{\,}{\mathrm{cm}}^{-2}$ Mager (2016), which was
designed for much lower particle density though.

###  4.2 Hit Detection and Noise

Ionizing particles are registered by the HitPix detector when the induced
signal exceeds a programmable threshold. The signal height is not measured by
the standard data processing chain. For debugging purpose, the analog signals
of one row can be routed to a readout pad. To determine the noise of the pixel
cells and to understand the response to electrical test signals, an external
voltage pulse of varying amplitude can be injected into the pixel front-end.
By scanning the amplitude of the injected signal at a fixed threshold, the
pixel response and noise can be determined. The distribution follows an error-
function and the noise corresponds to the width of the transition region.
Figure 10 shows an example of such a measurement.

Figure 10: Typical response curve of a pixel to injected charge pulses. Here,
efficiency is defined as the ratio of detected hits to injected pulses. The
data can be fit by an error-function as indicated by the red curve. The green
line and band mark the threshold voltage and the one standard deviation noise
amplitude. The noise figure here is units of voltage in the injection circuit
and not to be compared with noise voltage at the amplifier output.

The general noise level of HitPix2 at the comparator stage is about
$28\text{\,}\mathrm{mV}$, while a typical signal from high energy protons is
about $200\text{\,}\mathrm{mV}$. Knowing the noise level and the expected
signal height of the relevant particles, one can set an optimal threshold,
which eliminates hit counts due to noise, but still registers all particle
transitions.
To verify that the chosen pixel size is adequate for the ion beam, the cluster
size was evaluated for different beam conditions. A cluster is a group of
adjacent hits. If the cluster size is close to one, the generated charge
carriers are mainly localized within one pixel, which is advantageous for this
counting application. Figure 11 shows the average cluster size distribution in
a carbon ion beam with small spot size.

Figure 11: Average cluster size over the pixel matrix for a carbon ion beam
from Pittermann (2022). The higher cluster size in the center corresponds to
pileup effects (described in the text). The white line is caused by a
defective column which was masked for this analysis. Beam parameters: carbon
ions, energy range of
$108\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}423\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$,
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ particle rate.

The larger cluster sizes in the center are mainly from pileup. That means that
within the integration time of one $50\text{\,}\mathrm{\SIUnitSymbolMicro s}$
frame many hits are registered and the probability increases that two hits
appear in adjacent pixels. By definition that would be clusters, but from
several particles and not from one. To evaluate the average cluster size from
individual particles, the Gaussian distribution of the cluster sizes is fitted
and the baseline extracted. This results in a baseline average cluster size of
1.14 pixels for carbon ions of a wide energy range from
$108\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}423\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$.
For protons with energies in the range of
$60\text{\,}\mathrm{MeV}217\text{\,}\mathrm{MeV}$ the average cluster size is
1.12 pixels.
These results confirm the correct selection of the pixel dimensions.

###  4.3 Radiation Tolerance

Detectors with different substrate resistivities were irradiated at ZAG with
$23\text{\,}\mathrm{MeV}$ protons up to a $1\text{\,}\mathrm{MeV}$ neutron
equivalent fluence of $1\text{\times}{10}^{15}\text{\,}{\mathrm{cm}}^{-2}$.
The uniform irradiation resulted in an increase of the leakage current as
listed in Table 2.

Table 2: Tentative currents for the $1\text{\,}{\mathrm{cm}}^{2}$ detectors of different substrate resistivities. The current measurements were performed at room temperature and at $25\text{\,}\mathrm{V}$ bias voltage. Substrate resistivity | Current before irrad. | Current after irrad.
---|---|---
$20\text{\,}\mathrm{\SIUnitSymbolOhm}\text{\,}\mathrm{cm}$ | <$100\text{\,}\mathrm{nA}$ | $220\text{\,}\mathrm{\SIUnitSymbolMicro A}$
$300\text{\,}\mathrm{\SIUnitSymbolOhm}\text{\,}\mathrm{cm}$ | <$100\text{\,}\mathrm{nA}$ | $130\text{\,}\mathrm{\SIUnitSymbolMicro A}$
$5000\text{\,}\mathrm{\SIUnitSymbolOhm}\text{\,}\mathrm{cm}$ | <$100\text{\,}\mathrm{nA}$ | $80\text{\,}\mathrm{\SIUnitSymbolMicro A}$

These irradiated detectors were exposed to a carbon ion beam at HIT with a
defined intensity from which the total number of particles is derived
(uncertainty of 5% on number of particles in the QA room; less than 2% in the
treatment rooms). This number is compared to the number of acquired hits and
the ratio is the hit detection efficiency quoted in Figure 12.

Figure 12: Hit detection efficiency measured with carbon ions of different
energies after Pittermann (2022). Sample HP2.03
($300\text{\,}\mathrm{\SIUnitSymbolOhm}\text{\,}\mathrm{cm}$) is not
irradiated and operated at $50\text{\,}\mathrm{V}$, while the other samples
are irradiated to a $1\text{\,}\mathrm{MeV}$ equivalent fluence of
$1\text{\times}{10}^{15}\text{\,}{\mathrm{cm}}^{-2}$ and operated at
$25\text{\,}\mathrm{V}$. The two numbers in the brackets behind the sample
name in the legend correspond to substrate resistivity and comparator
threshold voltage (Vth), respectively. Beam parameters: carbon ions,
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$/$3\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$
particle rate for the unirradiated/irradiated sample, respectively, spot width
adapted (steps indicated by vertical dashed lines) depending on the beam
energy to stay at around $8\text{\,}\mathrm{mm}9\text{\,}\mathrm{mm}$ (FWHM).

The hit detection efficiency of the unirradiated sample HP2.03 exceeds 100%
since for each particle on average 1.14 hits are registered (Section 4.2). The
uniformly irradiated detectors still work and detect the beam spot correctly.
Compared to the unirradiated reference sample, the efficiency is reduced,
which gets more pronounced at higher ion energies, for which less ionization
and, therefore, signal is expected. Since the results are based only on one
sample each, one cannot draw a final conclusion on the best choice of
substrate resistivity, yet. There are further test conditions which have not
been optimized so far. The irradiated samples were operated at room
temperature and not cooled which can lower the leakage current and noise.
Therefore, also the threshold was possibly set too high so that the pixels
were less sensitive to small signals. A further handle to improve the
efficiency is a higher bias voltage, which was limited to
$25\text{\,}\mathrm{V}$ due to the high leakage current of the samples with
the lowest resistivity in this comparative study.
In general, the detectors are operational after irradiation up to a fluence
equivalent to one year operation at the central spot, but further tuning is
required to keep the efficiency high avoiding the need for too frequent
calibrations.

###  4.4 Beam Monitoring

Fast reconstruction of the beam position is one of the key requirements for a
beam monitoring system. With the current HitPix2 detector only an area of
$$9.6\text{\,}\mathrm{mm}$\times$9.6\text{\,}\mathrm{mm}$$ is sensitive for
particles and, therefore, only very tiny beam spots and small movements can be
traced. Distortions of the reconstruction at the edges of the detector are
expected and will not occur in the final system, since the missing beam spot
part will be recorded by the surrounding detectors. Figure 13 shows the
reconstructed beam positions for a carbon ion beam with the smallest focus
value possible at HIT.

Figure 13: Reconstructed beam centers for a continuous spot scan with
$2\text{\,}\mathrm{mm}$ steps. The detector was in counter readout mode with
$50\text{\,}\mathrm{\SIUnitSymbolMicro s}$ integration time per frame. Each
point in the plot corresponds to the reconstructed beam center in a frame. The
$2\text{\,}\mathrm{mm}$ raster is indicated by the red square. The green
square indicates the area without distortions which occur at the edge of a
single detector. Beam parameters: carbon ions,
$430\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ energy,
$3.4\text{\,}\mathrm{mm}$ spot width (FWHM),
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ particle rate.

Between each irradiation spot, the beam is moved by $2\text{\,}\mathrm{mm}$.
During one spot irradiation of several seconds length, the position is
reconstructed many times from the hits acquired during a
$50\text{\,}\mathrm{\SIUnitSymbolMicro s}$ frame, and each of the
reconstructed points is one entry in the histogram of Figure 13. For the
reconstruction of the beam spot, a simple mean algorithm is used, which can
also be easily implemented on an FPGA. The projected hits are binned by pixels
at positions $x_{i}$ with number of hits $n_{i}$. The mean beam position
$x_{0}$ and beam width $\sigma_{0}$ (or full width half maximum FWHM) are
calculated as

$\displaystyle x_{0}$
$\displaystyle=\frac{1}{n_{\mathrm{tot}}}\sum_{i}n_{i}\cdot x_{i}$ (1)
$\displaystyle\sigma_{0}^{2}$
$\displaystyle=\frac{1}{n_{\mathrm{tot}}-1}\sum_{i}n_{i}\cdot\left(x_{i}-x_{0}\right)^{2}\quad(\mathrm{FWHM}=2\sqrt{2\ln{2}}\;\sigma_{0}).$
(2)

In the center, one can clearly see the separation of $2\text{\,}\mathrm{mm}$
as intended for this irradiation plan. At the detector edges the reconstructed
position is distorted due to the missing particles outside the detector as
expected.
A special feature of the HitPix family is the projection of the hit counts on
one (later two) axis (adder readout mode). Figure 14 illustrates this feature.

Figure 14: Reconstructed beam centers for a continuous spot scan with
$1\text{\,}\mathrm{mm}$ step size using adder readout with
$20\text{\,}\mathrm{\SIUnitSymbolMicro s}$ integration time. Two features are
indicated in the plot: at ’1’ the beam intensity ramps up, and at ’2’ part of
the beam spot extends beyond the detector edge, which deteriorates the
position reconstruction. In the center the beam spot is contained within the
detector matrix and a correct reconstruction is possible showing the expected
$1\text{\,}\mathrm{m}\mathrm{m}$ steps. Beam parameters: carbon ions,
$430\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ energy,
$3.4\text{\,}\mathrm{mm}$ spot width (FWHM),
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ particle rate.

It shows the reconstructed positions of the projected beam profile integrated
within $20\text{\,}\mathrm{\SIUnitSymbolMicro s}$ during a spot scanning
irradiation. The small carbon ion beam spot was scanned in
$1\text{\,}\mathrm{mm}$ steps. This demonstrates that in this acquisition
mode, which will be the default during operation as beam monitor, the beam
motion can be traced continuously without dead time during readout.
To investigate the precision of the reconstruction method, a steady beam of
carbon ions was monitored for several seconds and the reconstructed position
and width filled in the two histograms in Figure 15.

Figure 15: Reconstructed beam centers (left) and beam widths (right) for a
steady carbon ion beam for projected hit profiles from Pittermann (2022). The
integration time for a frame used for reconstruction was
$30\text{\,}\mathrm{\SIUnitSymbolMicro s}$. Beam parameters: carbon ions,
$430\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ energy,
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ particle rate,
$3.4\text{\,}\mathrm{mm}$ spot width (FWHM).

The standard deviation or precision of the reconstructed position in this case
is $150\text{\,}\mathrm{\SIUnitSymbolMicro m}$. Assuming a chip alignment
precision of $10\text{\,}\mathrm{\SIUnitSymbolMicro m}$, which is a plausible
value assuming an automatized pick and place procedure, the resulting position
accuracy is below the required accuracy of
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$. For the presented low intensity
of $5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ and
$30\text{\,}\mathrm{\SIUnitSymbolMicro s}$ integration time, each projected
beam profile contains about 150 hits on average, which limits the
reconstruction precision. Higher intensities result in a better precision,
e.g. at $5\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ the precision is
improved to $80\text{\,}\mathrm{\SIUnitSymbolMicro m}$.
The width of the beam is taken as the standard deviation of the hit
distribution. From these measurements, a mean beam width of
$3.66\text{\,}\mathrm{mm}$ (FWHM) is derived and indicated in the Figure 15
(right). This is slightly higher than the nominal width of
$3.4\text{\,}\mathrm{mm}$, but still well within the allowed delivered width
range of +25%/–10%.
In this section, we have demonstrated that with the HitPix detector it is
possible to monitor the beam position and width with the required accuracy.
The short acquisition time of below $30\text{\,}\mathrm{\SIUnitSymbolMicro s}$
allows rapid feedback, and the operation in projection mode allows fast
readout of the data, and, thus, low latency of the results.

###  4.5 High-Rate Capability

The measurements presented so far have been mainly acquired at low beam
intensities. This section focuses on the high-rate capability of the HitPix2
detector. To address this property, an intensity scan of a steady and small
carbon ion beam at highest energy was investigated. The expected local
particle rate is calculated by the average intensity of the spot irradiation
and the position of the pixel with respect to the beam center assuming a
Gaussian beam profile. The registered hit rate versus the expected local
particle rate for each pixel at several beam intensities is plotted in Figure
16.

Figure 16: Single pixel hit rates versus expected local particle rates from
Pittermann (2022). The plot combines data from spot irradiations with
different beam intensities (colors:
$5\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$ (blue),
$1\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ (orange),
$2\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ (green),
$3\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ (red),
$5\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ (violet),
$8\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$ (brown)). For each pixel,
the expected local particle rate is calculated assuming a Gaussian beam
profile and the nominal beam intensities. The black line indicates a 100% hit
detection efficiency. The blue line is a fit according to Equation 3 with
$\epsilon=1.75$, $\theta=0.31$ and
$\tau=$$20.6\text{\,}\mathrm{\SIUnitSymbolMicro s}$. Beam parameters: carbon
ions, $430\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ energy,
$3.4\text{\,}\mathrm{mm}$ spot width (FWHM).

At low intensities, the pixels register the expected number of hits also
considering that, on average, each particle generates 1.14 hits (Section 4.2).
With increasing local particle rate the registered hit rate saturates and a
huge spread for individual pixels is observed. This effect can be modeled
taking dead time of the hit detection into account using a slightly modified
version of Takacs’ formula Müller (1991):

$\nu_{\mathrm{out}}=\dfrac{\epsilon\cdot\nu\cdot\theta}{e^{\epsilon\cdot\nu\cdot\theta\cdot\tau}+\theta-1}$
(3)

where $\nu_{\mathrm{out}}$ is the measured hit rate, $\nu$ the true particle
rate, $\epsilon$ the hit efficiency (additional parameter to account for
clusters), $\theta$ the probability of paralyzing dead time ($\theta=1$ would
be fully paralyzing, i.e. hits during dead time extent the dead time), and
$\tau$ the dead time. The blue line in Figure 16 represents the result of a
fit to the data indicating a dead time of $\tau=$
$20.6\text{\,}\mathrm{\SIUnitSymbolMicro s}$. This behavior is unexpected both
from design and laboratory measurements and is not in compliance with the
requirements. If the registered hit rate would follow a steady function with
respect to the local particle rate, the hit rate could be corrected, but for
dropping and widely scattered rates this is not possible.
Further investigations have been performed to understand this behavior. Short
light pulses generated by a pulsed infrared LED were injected on the detector
with increasing pulse frequency. The pixel counts were compared to the number
of light pulses. For optimally illuminated pixels the count rate follows the
injection rate up to a rate of $225\text{\,}\mathrm{kHz}$ as shown in Figure
17.

(a) Average hit rate for the pixels in the red rectangle on the right

(b) Map of the pixel hit rates for $200\text{\,}\mathrm{kHz}$ injections

Figure 17: Hit rates of pixels illuminated by a pulsed infrared LED. The
average hit rate (blue symbols) versus the expected nominal hit rate is
plotted in (a). The black line indicates the expected rate for 100%
efficiency. (b) shows, as an example, the map of the pixel rates for
$200\text{\,}\mathrm{kHz}$ injections.

In this configuration the hit detection efficiency is very high up to much
higher injection rates than in the ion beam in Figure 17. This indicates that
the fast counting capability of the pixels is functioning.
Looking at the analog signals of the amplifier of a pixel in the ion beam we
observe an increasing number of dips of the baseline voltage when exposed to
higher particle rates. Figure 18 shows examples of such measurements.

(a) Signals for protons at a rate of
$8\text{\times}{10}^{7}\text{\,}{\mathrm{s}}^{-1}$.

(b) Signals for protons at a rate of
$4\text{\times}{10}^{8}\text{\,}{\mathrm{s}}^{-1}$.

(c) Signals for carbon ions at a rate of
$2\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$.

Figure 18: Examples of voltage measurements at the amplifier output of one
pixel when exposed to different particle beams.

Carbon ions generate the most severe, but less frequent dips. During the time
the baseline is reduced, no hits are detected, causing dead time.
These measurements suggest that the heavily ionizing ions influence the
functioning of the pixels when a certain region in the pixel cell is hit. In
addition, analog signals were recorded of injected alpha particles with an
energy of about $5.5\text{\,}\mathrm{MeV}$ from an Am-241 source. Similar
baseline voltage drops as in the ion beam could be provoked with these alpha
particles. By placing the source above different locations of the detector, it
could be excluded that the electronics in the periphery is affected.
In conclusion, the hit detection efficiency of the HitPix2 drops for high-rate
particle beams. The investigations indicate that at a high rate of highly
ionizing particles the baseline voltage is affected and hit detection is
deteriorated. Still, the pixel cells function as expected for moderate charge
injection and further work can concentrate on mitigating effects induced by
highly ionizing particles. If the high-rate capability is not improved in a
following version of the detector the beam monitoring requirements cannot be
met.

###  4.6 Magnetic Field Tolerance

Magnetic fields are required for MRI-guided radiotherapy, however, they
influence the movement of charged particles and charge carriers in solids.
Since all modern detector technologies in beam monitoring rely at least
partially on electric fields and movement of charge carriers, the operation
within the strong magnetic field of an MRI machine or the somewhat lower
fringe field of a scanner has to be part of the technology evaluation process.
In a first step, we have investigated the performance of a detector setup with
HitPix1 in the adjustable field of the Helmholtz coils as described in Section
3.2. Unfortunately, but as expected, the commercial FPGA board has several
components (mainly voltage regulation) which cannot be operated in magnetic
fields. Therefore, the readout stopped already at $60\text{\,}\mathrm{mT}$
field. Up to this field strength, the detector kept working and no performance
degradation in monitoring a carbon ion beam has been detected.
To cope with the sensitivity of the FPGA board for these tests, a PCIe x16
twisted-pair riser cable with 1:1 connectivity has been designed and produced.
Using this cable, the commercial readout electronics was moved out of the
field center and the detector readout worked up to $100\text{\,}\mathrm{mT}$
which is the maximum possible field of the Helmholtz-coil pair.
For MRI tests, the modified setup with riser cable and HitPix2 has been used.
The detector carrier-PCB has been placed in the middle of the MRI (described
in Section 3.2) and the readout FPGA board at a distance of approximately
$1\text{\,}\mathrm{m}$. No influence of the static magnetic field was observed
in this configuration. The rapidly changing field of the scanning MRI,
however, causes the detector to lose its configuration, rendering it non-
operational. The reason for the configuration loss is the large induced
voltage on the detector’s configuration lines. Depending on the MRI scanning
procedure, we measured pulses of several volts on these lines, while the logic
levels are about $1.8\text{\,}\mathrm{V}$. At a distance of
$35\text{\,}\mathrm{cm}$ from the center of the scanning MRI (approximately
one quarter of the central field strength), the detector kept its
configuration and readout worked normal.
In the next iteration of the detector, a lockable configuration is foreseen,
meaning that random noise on the configuration line will be ignored and only
configuration bits preceded by an unlock-code will be accepted.

###  4.7 Multi-Detector Readout

To reach the required large size of the beam monitor, it is necessary to read
out many detectors. HitPix2 implements two schemes for multi-detector readout.
In daisy chain mode, several detectors can be directly interconnected (digital
data_out to data_in) and the data shifted through all of them. The other mode
is a bus configuration for which several detectors can be connected to a
common data line and the detectors individually selected for readout.
A PCB was designed to validate these functionalities in a $2\times 5$ matrix
(Figure 19).

Figure 19: Picture of the $2\times 5$ matrix PCB with five mounted detectors.

A first PCB was equipped with five detectors in one row. The detectors were
successfully read out in both readout modes. At HIT, the matrix was exposed to
particle beams for different beam parameter settings. The collected hit counts
for three beam settings are shown in Figure 20.

(a) Protons with beam width of $0.81\text{\,}\mathrm{cm}$ (FWHM)

(b) Carbon ions with beam width of $0.34\text{\,}\mathrm{cm}$ (FWHM)

(c) Carbon ions with beam width of $0.78\text{\,}\mathrm{cm}$ (FWHM)

Figure 20: Hit maps for all five detectors of the matrix after alignment for
three different beam settings. The red squares indicate the sensitive area of
the aligned detectors. The colored circles are contour lines of the
2d-Gaussian profile fitted to the hit distribution. The fit parameters are
provided in the plots. Each plot contains about $250\,000$ hits.

The reconstructed beam spot widths are well in agreement with the nominal
settings. Especially in the bottom plot one can see a smooth transition of hit
counts from one detector chip to the next. This demonstrates the comparable
hit detection efficiency of the neighboring detectors.
To achieve very high readout rates the bus configuration should be used since
the daisy chain readout showed a limit of about
$28\text{\,}\mathrm{M}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{/}\mathrm{s}$ on
the test setup.

###  4.8 Simulation Results

Since the proposed beam monitoring system marks a transition from gas filled
chambers to solid state detectors, the material effect on the beam needs to be
studied. For this, a simulation with the GEANT4 toolkit Allison et al. (2016)
has been performed comparing the current system at HIT with the proposed
system described in Section 1.4. The setup of the simulation is illustrated in
Figure 21.

Figure 21: Illustration of the simulated setup. The green rectangles represent
the position sensitive detectors and the narrow blue rectangle between them
the effective water equivalent of the ionization chambers. The plots at the
water box indicate examples of the expected transverse (top plot) and lateral
(right plot) energy deposition.

The narrow blue layer represents the three ICs with a water equivalent
thickness of $3\times$$230\text{\,}\mathrm{\SIUnitSymbolMicro m}$ Parodi et
al. (2012). This corresponds to the scenario in which the HitPix system only
replaces the MWCs for beam position and shape monitoring. In another scenario,
the HitPix system could even replace the ICs if the dose measurement is proven
to be compatible. This would reduce the material budget further. The green
layers in Figure 21 are either the MWCs
($160\text{\,}\mathrm{\SIUnitSymbolMicro m}$ water equivalent Parodi et al.
(2012)) or the HitPix system. The HitPix system consists of
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ carbon-fiber-reinforced polymer as
the thermal and mechanical support, $100\text{\,}\mathrm{\SIUnitSymbolMicro
m}$ of silicon for the thinned detectors and
$90\text{\,}\mathrm{\SIUnitSymbolMicro m}$ polyimide as flex cable with
$7\text{\,}\mathrm{\SIUnitSymbolMicro m}$ of either aluminum or copper per
side. An area factor is applied for the metal traces to account for
$80\text{\,}\mathrm{\SIUnitSymbolMicro m}$ wide traces at
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ pitch. For comparison, carbon ions
at $128.1\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$ were used as
primary beam traversing the beam monitoring arrangement and entering a water
target after about $1.2\text{\,}\mathrm{m}$ in air. The spatial distribution
of the energy deposition was recorded. The resulting profiles are compared in
Figure 22 for the current system at HIT, a water equivalent of
$2\text{\,}\mathrm{mm}$, which is the specified maximum material for five
layers (Section 1.2), and the HitPix system in two variants: with a single-
layer flex cable made of aluminum traces, and with a double-layer flex cable
made of copper traces.

Figure 22: Comparison of the simulation results for the different arrangements
from Pittermann (2022). Plotted are the lateral (left) and transverse (right)
energy deposition.

The distributions do not show significant deviations. As expected, the current
system with gas chambers does not affect the low energy carbon beam as much as
the solid state approach. Still, the additional broadening of the beam is not
very large if one avoids copper traces.

Table 3: Simulation results of the widening of a carbon ion beam after passing different detector arrangements and entering a water target. The width of the energy deposition is extracted from Figure 22 by fitting two Gaussian functions. Beam parameters: carbon ions, $128.1\text{\,}\mathrm{M}\mathrm{eV}\mathrm{/}\mathrm{u}$, parallel beam, point-like beam spot. Arrangement | Energy deposition
---|---
| FWHM width
HIT current (2 $\times$ MWC + 3 $\times$ IC) | $3.03\text{\,}\mathrm{mm}$
$2\text{\,}\mathrm{mm}$ WE (water equivalent) | $3.60\text{\,}\mathrm{mm}$
HitPix (Al single) (2 $\times$ HitPix + 3 $\times$ IC) | $3.79\text{\,}\mathrm{mm}$
HitPix (Cu double) (2 $\times$ HitPix + 3 $\times$ IC) | $4.23\text{\,}\mathrm{mm}$

Table 3 summarizes the extracted FWHM for the four scenarios. At low energy,
envisaged arrangement HitPix (Al single) broadens the carbon ion beam by about
5% more than the $2\text{\,}\mathrm{mm}$ water equivalent, which represents a
tolerable material budget. The almost homogeneous material distribution of the
proposed detector is an advantage compared to the tungsten wires in MWCs,
which act as strong scattering centers.
The HitPix detectors have a very small periphery to cover a maximally
sensitive area. Still, manufacturing aspects cannot avoid a small insensitive
region at three edges of the detector of
$150\text{\,}\mathrm{\SIUnitSymbolMicro m}$, and at the forth side the end-of-
column electronics ($128\text{\,}\mathrm{\SIUnitSymbolMicro m}$) together with
the contact pad region ($260\text{\,}\mathrm{\SIUnitSymbolMicro m}$) add up to
a width of about $400\text{\,}\mathrm{\SIUnitSymbolMicro m}$. Also the side-
by-side placement of the detectors adds a small gap of about
$100\text{\,}\mathrm{\SIUnitSymbolMicro m}$. In summary, there can be
insensitive gaps of up to $500\text{\,}\mathrm{\SIUnitSymbolMicro m}$ every
$20\text{\,}\mathrm{mm}$, which is the final detector chip dimension. To study
the effect of a worst case gap of $600\text{\,}\mathrm{\SIUnitSymbolMicro m}$
(equivalent to three missing pixel columns) on the beam spot reconstruction, a
simulation of the hit distribution for various Gaussian beam shapes and
positions has been performed. Figure 23 shows two examples of the beam shapes
with the gap at around position 2.5.

Figure 23: Illustration of two simulated beam profiles with an insensitive gap
at $x=2.5$ from Pittermann (2022). The vertical dashed lines represent the
true center of the beams, and the solid lines a Gaussian fit of the hit counts
represented by the bars. For the narrow beam, the bias of the reconstructed
peak is visible. Statistical fluctuations are omitted for this example.

Distributions following such shapes are generated by Poisson random numbers
for an average intensity of $2\text{\times}{10}^{6}\text{\,}{\mathrm{s}}^{-1}$
and $100\text{\,}\mathrm{\SIUnitSymbolMicro s}$ integration time. In Figure
24, the mean and standard deviation of the reconstructed position from $1500$
frames is plotted in dependence of the beam distance to the gap applying two
different reconstruction algorithms.

Figure 24: Reconstructed beam position bias (top) and standard deviation
(bottom) of simulated frames as a function of the distance to a
$600\text{\,}\mathrm{\SIUnitSymbolMicro m}$ wide insensitive gap from
Pittermann (2022). Two algorithms are used: simple mean (dashed line) and
likelihood fit of a Gaussian function (solid line). The beam is simulated by a
random number of hits per frame following Poisson statistics and a Gaussian
distribution. The true beam position is varied and three beam widths
(different colors) are tested.

The simple mean algorithm is visualized by the dashed lines, while the solid
lines represent the results of a likelihood fit with a Gaussian function. The
upper plot shows the average deviation (bias) which is the offset of the
reconstructed position compared to the true position. It is mainly unaffected
for the likelihood fit, while the simple mean algorithm has a maximum bias of
close to $200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ when the gap lies in the
beam spot tails breaking the symmetry. A systematic shift in the position
information for the feedback loop has to be avoided otherwise the uniform
irradiation may be degraded. The standard deviation (SD) of the beam spot
position in the lower plot of Figure 24 shows no significant difference
between the algorithms. Wider beams result in a worse standard deviation or
uncertainty due to the reduced hit counts per pixel.
The appropriate dimensioning of the pixels to mainly record single pixel
clusters was validated by measuring the cluster size in Section 4.2. With the
simulation framework introduced above, the effect of the pixel dimensions on
the precision of the reconstructed beam position and width has been
investigated. The results are shown on Figure 25 for different beam widths,
pixel sizes and algorithms.

Figure 25: Uncertainty (RMS deviation) of reconstructed beam position (top)
and beam width (bottom) of simulated frames as a function of pixel size
Pittermann (2022). Two algorithms are used: simple mean (dashed line) and
likelihood fit of a Gaussian function (solid line). The beam is simulated by a
random number of hits per frame following Poisson statistics and a Gaussian
distribution. The pixel size is varied and three beam widths (different
colors) are tested.

These plots demonstrate that pixel sizes below
$400\text{\,}\mathrm{\SIUnitSymbolMicro m}$ result in similar uncertainties
even for beams as narrow as $1\text{\,}\mathrm{mm}$ and can be implemented in
the detector. Therefore, the pixel size can be adapted to other constraints
like readout speed, diode capacitance or power consumption.

##  5 Summary and Conclusion

This article describes a new detector system based on hit counting HV-CMOS
detectors which targets the use as a beam monitor for ion therapy. The
detector is tailored to the requirements of the beam monitoring system at the
Heidelberg Ion beam Therapy center.
The pixel size is adapted to the resolution requirements. The hit counting
capability and the built-in projections aim for processing high particle rates
and fast readout at minimum latency. Attention was put into avoiding inactive
area and achieving low power consumption.
In several studies, the properties of the detector in view of the requirements
as beam monitor have been investigated. The resolution of the beam position
and spot width for small beam spots were well within the requirements of
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ accuracy. Hits from the particle
beam can be recorded continuously with an integration time of
$20\text{\,}\mathrm{\SIUnitSymbolMicro s}$ and the scanned beam can be traced.
The HV-CMOS detectors were irradiated to a fluence corresponding to the
maximum expected fluence in the center of the beam monitor after one year. The
irradiated samples did work in a carbon ion beam with reduced hit detection
efficiency which could be corrected for after calibration. There are options
to improve the performance like optimizing the threshold, cooling the
detectors and operating at higher bias voltage, which could extent the period
for calibrations.
Measurements with high-rate ion beams revealed a hit rate limiting effect,
which is being investigated. A likely cause are heavily ionizing particles
generating and accumulating charge below the cell electronics which cause the
baseline voltage to drop, making following hits undetectable. This failure
mode will be further analyzed and corrected in the next version. One possible
correction would be to modify the feedback circuit to be able to restore the
baseline faster.
The detectors were also tested in magnetic fields and demonstrated tolerance
of static magnetic fields of at least $250\text{\,}\mathrm{mT}$. The rapidly
changing fields of a scanning MRI induced high voltages in the connecting
cables, which were not optimized for this application yet. In some scanning
modes, these voltage pulses on the configuration lines made operation in a
scanning MRI system impossible. The next version of the detector chip will get
lockable configuration registers.
A first step towards a large matrix of HitPix detectors was the production and
partial assembly of a PCB providing supply and data lines for up to ten chips.
The daisy chain and bus readout modes were tested successfully and the matrix
recorded particle beams at HIT. The reconstructed beam spot widths are well in
agreement with the nominal beam settings.
In addition to measurements with the detectors, several simulation studies
were performed. The impact of the solid-state detector on the scattering of
the beam is close to the specified upper limit of $2\text{\,}\mathrm{mm}$
water equivalent, and has the advantage that concentrated scattering centers,
like the wires of the multi-wire chambers, are not present. The effect on the
position resolution with unavoidable gaps of sensitive area between detector
chips was studied. In a worst-case scenario with
$600\text{\,}\mathrm{\SIUnitSymbolMicro m}$ gaps and a very narrow beam of
$1\text{\,}\mathrm{mm}$ (FWHM), the bias of the position reaches
$200\text{\,}\mathrm{\SIUnitSymbolMicro m}$ at the worst position about
$400\text{\,}\mathrm{\SIUnitSymbolMicro m}$ away from the gap. This is true
for a simple algorithm calculating the mean of the hit distribution. A
likelihood fit of a Gaussian function would not be affected at all by the gaps
and will be considered for implementation on an FPGA. In another simulation,
it was shown that pixel sizes up to $400\text{\,}\mathrm{\SIUnitSymbolMicro
m}$ show similar and adequate reconstruction accuracy of the beam spot with a
width down to $1\text{\,}\mathrm{mm}$.

In summary, the investigated HitPix2 detector has proven to be a promising
candidate for a beam monitoring system at an ion beam facility. The
shortcomings identified during laboratory and beam tests are being addressed
and a successor is in development. The next HitPix version will feature offset
tuning, the second projection direction, faster readout concept, and increased
tolerance against single-event and charge-up effects. The next step is to
assemble a matrix as envisioned in Section 1.4 but with a reduced number of
$5\times 5$ chips. This detector system will be used for long-term operation
tests in the QA room at HIT.

Conceptualization, Alexander Dierlamm, Ivan Perić, Alena Weber and Jürgen
Debus; Data curation, Martin Pittermann; Formal analysis, Martin Pittermann,
Bogdan Topko, Thomas Hansmann and Jakob Naumann; Funding acquisition,
Alexander Dierlamm, Felix Ehrler, Ulrich Husemann, Ivan Perić, Jürgen Debus,
Nicole Grau, Oliver Jäkel and Sebastian Kluter; Investigation, Felix Ehrler,
Roland Koppenhöfer, Martin Pittermann, Bogdan Topko, Alena Weber and Jakob
Naumann; Project administration, Alexander Dierlamm and Ulrich Husemann;
Resources, Felix Ehrler, Ivan Perić, Martin Pittermann, Alena Weber, Stephan
Brons and Jakob Naumann; Software, Felix Ehrler and Martin Pittermann;
Supervision, Matthias Balzer, Ulrich Husemann, Ivan Perić and Sebastian
Kluter; Validation, Alexander Dierlamm and Jakob Naumann; Visualization, Felix
Ehrler, Martin Pittermann and Bogdan Topko; Writing – original draft,
Alexander Dierlamm and Felix Ehrler; Writing – review and editing, Ulrich
Husemann, Roland Koppenhöfer, Nicole Grau, Thomas Hansmann, Oliver Jäkel and
Jakob Naumann.

This research was funded by the Heidelberg Karlsruhe Strategic Partnership
(HEiKA), the KIT Center Elementary Particle and Astroparticle Physics (KCETA),
Helmholtz Program Matter and Technology, German Federal Ministry of Education
(BMBF) within the Adaptive RadioThErapie Mit IonenStrahlen (ARTEMIS) Project
under Grant 13GW0436A.

###### Acknowledgements.

The authors would like to thank Rudolf Schimassek for his contribution to the
DAQ system and GECCO board, Horacio Mateos for the assembly and bonding and
Bernd Berger for performing the irradiations at the cyclotron. References

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