# Ultrasonic Actuation of a Fine-Needle Improves Biopsy Yield

Emanuele Perra  Medical Ultrasonics Laboratory (MEDUSA), Department of
Neuroscience and Biomedical Engineering, Aalto University, Espoo, 02150 ,
Finland  Eetu Lampsijärvi  Electronics Research Laboratory, Department of
Physics, University of Helsinki, Helsinki, 00560, Finland  Gonçalo Barreto
Translational Immunology Research Program, University of Helsinki, Helsinki,
00100, Finland  Orton, Helsinki, 00280, Finland  Muhammad Arif  Medical
Ultrasonics Laboratory (MEDUSA), Department of Neuroscience and Biomedical
Engineering, Aalto University, Espoo, 02150 , Finland  Tuomas Puranen
Electronics Research Laboratory, Department of Physics, University of
Helsinki, Helsinki, 00560, Finland  Edward Hæggström  Electronics Research
Laboratory, Department of Physics, University of Helsinki, Helsinki, 00560,
Finland  Kenneth P.H. Pritzker  Department of Laboratory Medicine and
Pathobiology, University of Toronto, Toronto, M5S 1A8, Canada  Department of
Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, M5G 1X5,
Canada  Heikki J. Nieminen  Medical Ultrasonics Laboratory (MEDUSA),
Department of Neuroscience and Biomedical Engineering, Aalto University,
Espoo, 02150 , Finland<EMAIL_ADDRESS>
###### keywords:

Physics, Nonlinear Ultrasound, Medical Needles, Fine-needle Biopsy Aspiration

## ABSTRACT

Despite the ubiquitous use over the past 150 years, the functions of the
current medical needle are facilitated only by mechanical shear and cutting by
the needle tip, i.e. the lancet. In this study, we demonstrate how nonlinear
ultrasonics (NLU) extends the functionality of the medical needle far beyond
its present capability. The NLU actions were found to be localized to the
proximity of the needle tip, the SonoLancet, but the effects extend several
millimeters from the physical needle boundary. The observed nonlinear
phenomena, transient cavitation, fluid streams, translation of micro- and
nanoparticles and atomization, were quantitatively characterized. In the fine-
needle biopsy application, the SonoLancet contributed to obtaining tissue
cores with increase in tissue yield by 3-6x in different tissue types compared
to conventional needle biopsy technique using the same 21G needle. In
conclusion, the SonoLancet could be of interest to several other medical
applications, including drug or gene delivery, cell modulation, and minimally
invasive surgical procedures.

## Introduction

The antecedent of the medical lancet was described by Hippocrates for the
purpose of puncturing and draining pus[1]. Currently the lancet, a small
lance[2], is widely employed in medical cutting and piercing devices, e.g.
hypodermic needles, surgical tools and tissue sampling needle biopsy devices.
Structurally a lancet typically has at least two converging edges and a sharp
tip[3]. When pressed against or moved along a tissue interface, the lancet’s
purpose is to utilize manually mechanical forces to separate one structure
from another in order to achieve or enable a medical purpose[4]. The medical
needle, employing lancet-shape or other needle tip geometries[5], is a common
tool in healthcare, exemplified by the estimated 16 billion annual injections
worldwide[6]. However, the functions of the needle tip are limited to
mechanical shear and cutting by the needle tip. In fact, while not extensively
studied, previous literature suggests that some needle functions still present
limitations with regard to pain (about 10% of the population suffers from
needle phobia[7] and 3-10 % of the population has been estimated to avoid
medical care because of the fear of needles [8, 9, 10]), precision[11, 12],
spatial localization[13] and for needle biopsies, adequacy with regard to
quality and quantity of tissue yield[14].

An example of a field limited by current functions of a medical needle is
needle biopsy for cancer diagnosis. To provide a cancer therapy, histological
and molecular tissue samples are required. However, up to 34% of histological
and up to 50% molecular assessments fail, because of obtaining diagnostically
insufficient sample characterized by limited quantity of obtained pathological
cells or nucleic acids[14, 15]. Insufficiently adequate biopsies induce a
burden on the patients due to extended wait times before obtaining the
diagnosis[16]. The time pressure to start the therapy can lead to the
treatment initiation with inadequate information. Therefore, ways to improve
tissue yield, while not compromising safety, are urgently needed in cancer
diagnostics.

Actuation of medical needles by ultrasound has been observed to induce tissue
movement that can help with localizing the needle under Doppler ultrasound[17,
18] or to reduce penetration resistance of the needle[19, 20], which could
potentially help in reducing the pain of the needle insertion through the skin
[21, 22]. In conjunction with microneedles, low frequency mechanical
oscillations in the kHz range have been used for oocyte micro-dissection[23],
to enhance the microneedle penetration into mouse embryos[24], fish eggs[25]
and oocytes[26], and subsequently to improve oocyte viability for in vitro
fertilization[27]. However, until now, the potential of NLU extending beyond
the needle tip has been overlooked as a way to add value to the function of
medical needles. In fact, the NLU can generate acoustic force fields providing
a precise manipulation of entities selectively closer or at a farther distance
from the sound source.

Fine-needle aspiration biopsy (FNAB) is a common biopsy method in which a
hypodermic needle and a syringe are employed to aspirate tissue constructs
from a target tissue, e.g. suspected tumor. The needle is translated by the
operator, while the needle tip is inside the target tissue. Suction by the
syringe causes the tissue to bulge towards the needle lumen and adhere to the
inner walls of the needle, while the rapid movement of the needle tip will
cause the protruded portion of tissue to be sliced off by the cutting edges of
the needle and to be aspirated into the lumen[28]. Here the source of the
external force is the operator hand, which translates to compressive, shear
and tensile forces at the needle tip and explain the detachment of cells and
tissue constructs from the target tissue. Contrary to FNAB, we hypothesize
that ultrasound could serve as an external source of forces near the needle
tip further accelerating the detachment of cells and tissue constructs.

Coupling flexural waves to a needle induces sideways motion of the needle tip.
This is anticipated to exert direct shear, compression and tensile stresses to
the needle tip environment as well as induce sound emission, beyond the forces
induced by the operator’s hand movement. The sound emission could generate NLU
phenomena such as acoustic radiation force[29], acoustic streaming[30] and
cavitation[31]. In the context of biopsy, the direct and indirect forces are
expected to contribute to extracting cells and tissue constructs, which could
enhance the yield in biopsy.

The aim of this study was to investigate how adding ultrasound to a
conventional medical needle could change its conventional functions. We first
demonstrated how ultrasound emission could be localized at a tip of a
conventional medical needle, as an energy source for NLU around the needle
tip. From micrometer to millimeter scale, we quantitatively characterized the
NLU effects potentially contributing to tissue actuation, such as cavitation,
acoustic radiation force and atomization spatially reaching beyond the
physical lancet; we defined the confined volume around the needle tip
exhibiting pronounced nonlinear effects as the SonoLancet. Finally, we
demonstrated the capability of SonoLancet to increase the sample yield in the
FNAB application.

## Results

### Localization of ultrasound near the needle tip

To demonstrate that the effects potentially contributing to tissue actuation
can be generated near an ultrasonically actuated medical needle (Figure
1A(1-3)), a 21 gauge hypodermic needle was selected, because it represents a
common medical needle. Moreover, needles of this diameter or less (fine
needles) induce less tissue trauma than larger needles. The selected geometry
permits access to the needle hub with a variety of adjuvant devices commonly
used in medical practice, e.g. tubing, syringe, vacutainer; for this study we
selected a $10\text{\,}\mathrm{mL}$ syringe.

We employed an axially translating Langevin transducer as a sound source,
which was coupled to an S-shaped waveguide connected to a medical needle
(Figure 1A(1)). Using the waveguide, the longitudinal mode waves of the
ultrasound transducer are converted to flexural mode waves in the needle.
Reflection of the wave from the needle tip allowed generation of a flexural
standing wave between the tips of the needle and the waveguide. Moreover, the
converging structure of the medical needle bevel gives geometric amplification
of the wave towards the needle extremity. As a consequence of the wave
amplification, the needle tip is made to act as a dipole-like sound source
oscillating at a large displacement amplitude (Figure 1D), exhibiting
considerably greater time-averaged acoustic intensity at the needle tip
(Figure 1B) than elsewhere near the needle lumen, which carries the energy.
These characteristics have specific relevance to non-linear ultrasonics (NLU)
associated with time-averaged intensity (e.g. acoustic radiation pressure) or
characterized by threshold behavior (e.g. cavitation), since the NLU phenomena
can be limited to the proximity of the needle tip.

As the ultrasound field near the needle is largely confined within a distance
of few mm near the needle bevel (Figure 1B(1)), the localization of the
SonoLancet is spatially precise and microtrauma in tissues farther away from
the needle tip is expected to be minimized. In fact, the threshold phenomenon
of cavitation and the fast geometric attenuation of the acoustic field near
the needle exclude explanations, where cavitation could unexpectedly occur
very far from the needle. Cells and tissue components influenced by the
SonoLancet can be withdrawn through the needle lumen directly from the site of
ultrasound action or alternatively, cells and agents can be delivered to a
spatially well-defined site in conjunction with ultrasonic actions.

### Cavitation

Large displacements in the direction of x-axis (Figure 1D) detected near the
lancet point produce pronounced acoustic intensity radiating outwards from the
center axis of the needle. The high magnitude of the peak-negative-pressure,
associated with the acoustic intensity, elevates the probability of
ultrasound-microbubble interactions, i.e. cavitation (Figure 1C(1,2)).
Cavitation activity exhibited within a region extending less than
$2\text{\,}\mathrm{mm}$ from the tip along the positive z-direction. Optical
high-speed (HS) imaging ($300\,000\text{\,}\mathrm{f}\mathrm{p}\mathrm{s}$)
revealed that the temporal probability of observing cavitation across a time
window of $100\text{\,}\mathrm{ms}$ can be up to 50% in this region (Figure
1C(2)), while in the proximity of the rest of the needle there were no signs
of cavitation. This spatio-temporal behaviour arises from the inertial
cavitation being a threshold phenomenon[32]. Cavitation, i.e. growth,
oscillation and collapse of gas bubbles, is a consequence of the fluctuating
pressure amplitude being momentarily the lowest in this area due to the
pronounced amplification of needle tip motion compared to other locations
along the needle lumen (Figure 1B(1,2)).

While the needle tip displacement was observed to be <
$100\text{\,}\mathrm{\SIUnitSymbolMicro m}$ (Figure 1D), the bubble-water
boundary displacement was more pronounced, extending beyond
$300\text{\,}\mathrm{\SIUnitSymbolMicro m}$ along the positive x-direction.
This is due to the different compliances of water and an air bubble. The
activity of the primary bubble within the SonoLancet produced fluid movements
of several $\text{\,}\mathrm{m}\text{\,}{\mathrm{s}}^{-1}$ (Figure 1G),
accelerations up to five orders of magnitude of gravity (Figure 1H), thus
allowing production of high shear stresses localized near the needle tip[33].
Collapsing bubbles produce secondary sound formation, a potential mechanism of
shock wave formation[34] and strong and transient shear forces have great
potential to actuate matter, such as micro- and nanoparticles or tissue such
as cells, groups of cells or localized regions of an organ.

### Acoustic radiation pressure

Acoustic radiation force can be employed to push or pull medium, objects and
interfaces[35]. It is a force exerted on a target arising from acoustic
radiation pressure, which is due to a change in momentum of the acoustic wave,
when the wave interacts with such target. We here studied the capability of
SonoLancet to generate acoustic radiation pressure in a suspension of
microparticles. Two main jets (Figure 2A) of microparticles (models for micro-
vehicles), were emanating from opposite sides of the needle bevel with a
maximum velocity of approximately
$1\text{\,}\mathrm{mm}\text{\,}{\mathrm{s}}^{-1}$ at $0.6\text{\,}\mathrm{mm}$
from the needle tip, decreasing
$0.5\text{\,}\mathrm{mm}\text{\,}{\mathrm{s}}^{-1}$ at a distance of
$2\text{\,}\mathrm{mm}$ mm away from the maximum. Considering the wavelength,
the small object size and similar acoustic impedance of particles compared to
that of water, the main mechanism of translation arises from acoustic
streaming, i.e. acoustic radiation force exerted on the liquid, rather than
acoustic radiation force directly pushing the particles. This is supported by
a finding that SonoLancet in water
($22\text{\,}\mathrm{\SIUnitSymbolCelsius}$) without microparticles induced
acoustic streaming; such observation was confirmed under Schlieren imaging
(Figure 2B), which revealed a disturbance of water laminar flow
($15\text{\,}\mathrm{\SIUnitSymbolCelsius}$) close to the sonicating needle.
The results demonstrate that SonoLancet is capable of inducing acoustic
radiation pressure leading to mass transfer near the needle tip, which could
be relevant to delivery of directional transportation of liquids or particles
in localized therapeutic applications such as gene and drug delivery.

### Atomization

Capillary waves propagating at the water-air interface can induce micro-
droplet formation at large displacement amplitudes[36]. To investigate the
potential of SonoLancet to produce micro-droplets, we first introduced a water
droplet near the needle tip, while the needle was embedded in air. Capillary
waves were observed at low driving power levels (electrical output power <<
$1\text{\,}\mathrm{W}$) of the transducer. At increased powers (electrical
output power $\sim$ $1\text{\,}\mathrm{W}$) crests of the waves started to
extrude, eventually forming droplets ejected from the water-air interface[36].
By adjusting the driving frequency, we modified the size distribution of the
deionized water droplets ejected from the surface (Figure 2C-D) from a median
size of $39.5\text{\,}\mathrm{\SIUnitSymbolMicro m}$ down to
$17.5\text{\,}\mathrm{\SIUnitSymbolMicro m}$. The trend in median droplet size
is in line with the theoretical prediction:

$\displaystyle d_{p}=0.34\Big{(}\frac{8\pi\sigma}{\rho f^{2}}\Big{)}^{1/3}$
(1)

where $d_{p}$ is the droplet size, $\sigma$ is the surface tension, $\rho$ is
the density and $f$ is the excitation frequency[37]. These results demonstrate
the capability of SonoLancet to produce water micro-droplets with a controlled
size distribution, relevant to e.g. delivery of therapeutic agents such as
drugs or antiseptics in pulmonary conditions.

### Influence of SonoLancet on a tissue phantom and tissue

As demonstrated above, the SonoLancet can induce nonlinear effects in well-
defined media such as water and air. In the following, we demonstrate
SonoLancet’s influence on a tissue phantom and on excised tissue. Ballistic
gelatin was selected as a model for visualizing the needle activity inside a
soft-tissue-like material. We subjected a hydrogel tissue phantom (10% w/v
porcine gelatin, $22\text{\,}\mathrm{\SIUnitSymbolCelsius}$) to the SonoLancet
in conjunction with fluorescent nanoparticles (diameter
$63\text{\,}\mathrm{n}\mathrm{m}$) introduced to the proximity of the needle
tip through the lumen. When a continuous wave of $31.7\text{\,}\mathrm{kHz}$
and total acoustic power (TAP) $\sim$ $0.8\text{\,}\mathrm{W}$ were applied to
the needle, the generation of cavitation bubbles and acoustic streaming was
optically confirmed. The boundary of the influenced volume extended outward
from the needle tip over time (Figure 3A). After sonication was applied
together with fluorescent nanoparticles, a 3D reconstruction of the
nanoparticle distributions characterized by optical projection tomography
revealed a volume containing nanoparticles is localized near the needle tip
(Figure 3B). Dissection of the phantom was used to verify that the gel was
liquefied. At the highest TAP levels, $\sim$ $0.8\text{\,}\mathrm{W}$, we
recorded a temperature rise of < $2\text{\,}\mathrm{\SIUnitSymbolCelsius}$ or
< $4\text{\,}\mathrm{\SIUnitSymbolCelsius}$ during a 5 or
$20\text{\,}\mathrm{s}$ sonication, respectively, suggesting that cavitation
was the main mechanism of liquefaction[38], rather than ultrasound-induced
temperature rise. Even though the observed acoustic phenomena in gelatin may
occur in a different fashion in an ex vivo tissue, this experiment gave us an
insight on how the acoustic energy is manifesting an influencing the
surroundings of the needle tip, when the needle has been confined by material
with similar acoustic impedance to that of soft tissue.

To demonstrate the influence of SonoLancet on tissue, we performed FNABs with
and without ultrasound at the needle tip (ultrasound-enhanced fine-needle
aspiration biopsy, USeFNAB) in different bovine tissues: liver, kidney, spleen
and striated muscle. USeFNAB contributed to increased sample yield, whose
weight increased with increasing TAP (p < 0.0125), being on average up to 4x
the yield obtained with FNAB in liver, 5x in kidney, 3x in spleen and 6x in
muscle (Figure 3C), as compared to FNAB. When ultrasound-enhanced biopsies
were performed at the highest TAP ($0.8\text{\,}\mathrm{W}$), the average
sample weight obtained in liver was $88.6\pm 9.3\text{\,}\mathrm{m}\mathrm{g}$
(average $\pm$ standard deviation; n = 6) (Figure 3C(1)), $53.7\pm
8.6\text{\,}\mathrm{m}\mathrm{g}$ (n = 6) in kidney (Figure 3C(2)), $62.2\pm
5.4\text{\,}\mathrm{m}\mathrm{g}$ (n = 6) in spleen (Figure 3C(3)) and
$11.9\pm 1.9\text{\,}\mathrm{m}\mathrm{g}$ (n = 6) in muscle (Figure 3C(4));
the sample masses obtained with FNAB were respectively $22.7\pm
1.8\text{\,}\mathrm{m}\mathrm{g}$ (n = 6), $11.7\pm
2.0\text{\,}\mathrm{m}\mathrm{g}$ (n = 6), $16.6\pm
1.0\text{\,}\mathrm{m}\mathrm{g}$ (n = 6) and $1.8\pm
0.6\text{\,}\mathrm{m}\mathrm{g}$ (n = 6). Based on a histopathological
evaluation, performed by a pathologist (KP) with > 40 years of histopathology
and cytopathology experience, all tissue types included intact cells and
tissue (Figure 4) containing histologically relevant structures that could be
observed in all samples.

A computer-assisted method was adopted to quantify the fragmentation in the
liver samples (Figure 5A). The area of tissue fragments (large regions of
adjacent hepatocytes), cell clusters (small aggregation of hepatocytes),
single cells and debris pieces (organic waste) detected in the control group
slides (FNAB) were measured and compared to the experimental groups (USeFNAB,
TAP levels: $0\text{\,}\mathrm{W}$, $0.2\text{\,}\mathrm{W}$,
$0.5\text{\,}\mathrm{W}$ and $0.8\text{\,}\mathrm{W}$). On average the total
areas of tissue fragments, cell clusters, single cells and debris pieces were
slightly influenced by ultrasound; however, they were not statistically
significantly different from the respective areas of FNAB (p > 0.0125). At the
highest TAP the relative total area of tissue fragments was lower ($57.9\pm
9.5\text{\,}\%$, average $\pm$ standard deviation, n = 6, p = 0.0306) as
compared to FNAB ($69.9\pm 5.8\text{\,}\%$, n = 5) (Figure 5B(1)). The
relative total area of cell clusters and individual cells were not different
from those of FNAB when the highest TAP was employed (p = 0.0656 and p =
0.8102, respectively) (Figure 5B(2,3)). The relative total debris area
($17.2\pm 4.6\text{\,}\%$, n = 6, p = 0.0131) was higher as compared to FNAB
($11.0\pm 2.3\text{\,}\%$, n = 5) (Figure 5B(4)).

The results show a systematic increase in the sample mass with increasing TAP,
while inducing a minimal effect on the morphological structure of the sample
as compared to the FNAB approach, as a manifestation of the actuation of
tissue induced by SonoLancet.

## Discussion

We successfully coupled flexural standing waves to a conventional medical
needle. The converging structure of the needle bevel seemed acoustically quite
optimal at the employed frequency, because it geometrically amplified the wave
allowing to generate a highly localized and large displacements of the needle
tip. The acoustic intensity of the longitudinal waves emitted from the needle
extended beyond the linear regime to nonlinear regime, suggested by large
displacements < $100\text{\,}\mathrm{\SIUnitSymbolMicro m}$ and the observed
nonlinear effects. The maximum time-averaged acoustic intensity next to the
needle bevel was more than twice compared to that along the lumen. Since the
acoustic radiation pressure associated phenomena, such as acoustic radiation
force or acoustic streaming, are proportional to intensity, the mass transfer
mechanisms are pronounced at the needle tip. The long needle shaft has
multitude of resonant eigen-frequencies, which allowed changing the operation
frequency. This permitted controlling the size of the atomized droplets
contrary to common ultrasound atomizers, which typically operate on a single
frequency[39, 40, 41].

Cavitation being a threshold phenomenon allowed generation of cavitation at
will. Importantly, this was spatially restricted to the proximity of the
needle tip without observations of cavitation along the needle lumen,
suggesting that these mechanisms can be made to localize to the proximity of
the needle tip. The high accelerations > $20\,000\text{\,}$x the gravitational
acceleration of the bubble-water boundary suggests that extreme shear forces
can be induced by this boundary to the surroundings, when cavitation is
intended. In addition, the direct effect of the rapidly moving needle tip with
sharp edges provide points to exert high stress fields on matter, such as
tissue.

Minimally invasive high-frequency mechanical actuation at a known position
inside the body has specific relevance to various medical applications. We
exemplified the influence of the SonoLancet on tissue in the FNAB application.
Depending on the tissue type, the tissue yield was increased 3-6x on average
and with increasing TAP. A potential explanation of the enhanced mass of the
biopsy sample lies in the combined action of the localized movement of the
needle tip and the suction force applied with the syringe. The suction force
is needed to pull the tissue against the needle tip and to prevent it to slip
during the cutting process. However, the suction alone does not tear cells or
tissue fragments from the target. In fact, Kreula et al. demonstrated that the
sample yield is linearly dependent on the suction force only when combined
with the needle movement (e.g. fanning)[28]. Based on this finding, we believe
that the ultrasonic actuation of the needle introduces an additional degree of
freedom in the needle movement (flexural displacement of the needle tip) that
introduces additional forces facilitating the tissue extraction in an
analogous way to what the fanning technique would contribute to, but at a
smaller length-scale and higher frequency. In addition, the studied NLU
phenomena are expected to generate shear forces that contribute to the
extraction of cells and tissue constructs from the target, which are then
drawn into the needle by the low pressure applied with the syringe. We foresee
this to have importance especially in cancer diagnostics, which increasingly
relies on molecular assessments for therapy decisions. The failure rate of
molecular assessment is up to 50%[14] arising mainly from inadequacy of the
nucleic acids required for determining the cancer type. This could be
resolved, by obtaining a greater sample volume using SonoLancet permitting
access to greater nucleic acid quantity. The SonoLancet could contribute also
to histopathological assessments, which suffer from failure rates up to 34%
due to inadequacy of tissue yield[42, 43].

Future studies should address the clinically relevant adequacy of the sample,
its micro-level integrity and the influence of ultrasound on the needle tract.

SonoLancet could be also beneficial for other medical applications beyond
cancer diagnostics. Controlled cavitation, used in a variety of existing and
emerging ultrasonic medical technologies[44], could be exploited in
personalized therapeutic and diagnostic applications, by applying cavitation
locally at the needle tip precisely at the target site. Such applications
include tumor ablation[45], permeation of tissue matrix for enhanced stem cell
delivery or migration, bubble-enhanced poration of cells, i.e.
sonoporation[46], transfection of genetic material[47] or even modifying gene
expression by stimulating ultrasound[48]. Moreover, cavitation-induced shock
waves and associated shear forces, arising from imploding cavitation
bubbles[49], could be employed for lithotripsy[50] or controlled softening of
calcified vessels[51] with spatially precise and localized mechanical stress
gradients[52]. The SonoLancet could potentially serve as a way to induce
streaming of biological fluids and translation of entities inside the body.
Unidirectional motion of drugs or drug nanocarriers, induced by the transfer
of momentum from the wave to the liquid, could enhance pharmaceutical
effectiveness[53] and facilitate applications such as targeted and localized
drug, stem cell or gene delivery. Atomization provides the ability to
transform liquid into micro-droplets with control over droplet size
distribution and direction of the droplet jets allowing new platforms for
delivery of drugs or cells e.g. within bodily cavities such as those in the
respiratory system.

Considering the safety, the diameter of the volume of tissue influenced by
SonoLancet is comparable to that of a 11G needle (outer diameter =
$3.05\text{\,}\mathrm{m}\mathrm{m}$), while the energy is delivered through a
small tract generated by a 21G needle (outer diameter =
$0.82\text{\,}\mathrm{m}\mathrm{m}$). This allows influencing a large volume
of tissue in respect to the small size of the needle, while minimizing trauma,
when accessing target site. Therefore, the SonoLancet could contribute to
modifying the tissue permeability for drug delivery applications at precise
tissue locations and with extreme ultrasound exposure, or allow minimally
invasive surgical interventions via spatially precise histotripsy.
Importantly, in all of these experimentations the employed ultrasound
frequencies were relatively low, < $100\text{\,}\mathrm{kHz}$. Moreover, the
risk of cavitation to occur and induce mechanical damage in unwanted regions
inside tissue (e.g. along the needle shaft) is minimized by the fact that the
acoustic energy is highly concentrated at the tip of the needle, as supported
by numerical simulations (Figure 1B(1,2)). For this reason, cavitation is more
likely to appear at the needle tip than elsewhere, and if such event were to
occur along the needle shaft, its effects would be limited in a confined
region from the needle boundary, as the intensity attenuates strongly in the
direction radial to the needle center axis due to geometric factors. Since at
these frequencies the attenuation coefficients in tissue and water are small,
the heat deposition to tissue is minimized. This is supported by low
temperature rise recordings < $2\text{\,}\mathrm{\SIUnitSymbolCelsius}$ and in
extreme conditions < $4\text{\,}\mathrm{\SIUnitSymbolCelsius}$. Therefore,
these findings suggest that the SonoLancet provides a minimally invasive way
to influence matter via non-linear ultrasonic mechanisms within a confined
volume at the proximity of the needle without major thermal impact. To our
knowledge, this study is the first to demonstrate the selected NLU effects
near the ultrasonically actuated medical needle. While this study exemplified
the use of ultrasonically actuated needle in the biopsy application, its use
could extend to other medical applications.

To conclude, we have functionalized the medical needle tip by nonlinear
ultrasonics and, at a micrometer to millimeter scale, and quantitatively
characterized its physical properties such as cavitation, acoustic radiation
pressure and atomization within a confined volume defined as the SonoLancet.
In this approach, the conventional hypodermic needle structure employs the
lumen as a conduit to bring sound energy to the needle tip. The 3D shape of
the conventional needle bevel amplifies the ultrasound action resulting in
localized nonlinear effects at the proximity of the needle tip. Limiting the
ultrasound action to the SonoLancet provides spatiotemporal control of sound-
tissue interaction and with respect to minimizing microtrauma of adjacent
tissues. By bringing precisely controlled ultrasound energy to a specific
location in the body, the SonoLancet has the potential to give conventional
medical needles a new role in many applications, such as tissue biopsy,
molecular diagnostics, drug or gene delivery, cell modulation, or minimally
invasive surgical procedures.

## Methods

### Experimental arrangement

A Langevin ultrasound transducer (Figure 1A(1) and Figure 6A) was coupled via
a custom-designed solid 3D printed aluminum waveguide (3D Step Oy, Ylöjärvi,
Finland) to a 21G $\times$ $80\text{\,}\mathrm{m}\mathrm{m}$ hypodermic needle
(model: 4665465, 100 STERICAN, B Braun, Melsungen, Germany) connected to a
$10\text{\,}\mathrm{m}\mathrm{L}$ syringe (catalogue number: 12931031, Plastic
PP Syringes Luer Slip, Fisherbrand, Fisher Scientific, Hampton, NH, United
States) (Figure 1A(1)). The device was powered by a computer-controlled
combination of an RF amplifier (model: AG 1012LF, Amplifier/Generator, T&C
Power Conversion, Inc., Rochester, NY, United States) and a function generator
(model: Analog Discovery 2, Digilent, Inc., Henley Court Pullman, WA, United
States), which provided the driving signal. High speed (HS) imaging of needle
actuation was employed to observe and quantify the NLU phenomena in different
experiments. The HS camera (model: Phantom V1612, Vision Research, Wayne, NJ,
United States) was operated in conjunction with a macro lens (model: Canon
MP-E 65 mm f / 2.8 1-5x Macro Photo, Canon Inc., Ōta, Tokyo, Japan) and a
general purpose lens (model: Canon EF-S 15-85 mm f / 3.5-5.6 IS USM, Canon
Inc.). A white light-emitting diode (catalogue number: 4052899910881, White
Led, 3000 K, 4150 lm, Osram Opto Semiconductors, Germany) was used as a light
source to produce background light for shadowgraphy of the object during the
HS camera recordings. The spatial position of the needle tip was controlled by
a motorized three-axis translation stage (model: 8MT50-100BS1-XYZ, Motorized
Translation Stage, Standa, Vilnius, Lithuania) operated by a computer user
interface programmed in LabVIEW. Additionally, a combination of a dual-axis
goniometer (model: GNL20/M - Large Dual-Axis Goniometer, Thorlabs, Inc.,
Newton, NJ, United States) and a continuous rotation stage (model: CR1/M -
Continuous Rotation Stage, Thorlabs, Inc., Newton, NJ, United States) was
mounted on the translation stage to manually control the polar and azimuthal
angle of the needle shaft.

### Numerical simulation

In this study, the software COMSOL Multiphysics v5.5[54] was used to simulate
the acoustic emission of the needle in a volume of water. The 3D geometry
consists of an ultrasound transducer coupled to a 21G hypodermic needle via an
S-shaped aluminum waveguide (Figure 1A(1)). The needle shaft is surrounded by
a cylindrical volume of water (external dimensions = R $\times$ H =
$5\text{\,}\mathrm{m}\mathrm{m}$ $\times$ $50\text{\,}\mathrm{m}\mathrm{m}$).
The ultrasonic actuation of the needle is obtained by applying a potential
difference of $100\text{\,}\mathrm{V}$ at a frequency of
$31.32\text{\,}\mathrm{kHz}$ across the piezoelectric stack. The pressure
field in water, generated by the vibrating needle, was calculated by
performing a frequency domain analysis. The x-component of the time-average
acoustic intensity, defined as
$I_{ta,x}=\frac{1}{2}\operatorname{\mathbb{R}e}\\{pv_{x}^{*}\\}$ with p being
the complex pressure and $v_{x}^{*}$ the complex conjugate of the acoustic
velocity along the x-direction, was then evaluated on the xy-plane coincident
with the needle center axis (Figure 1B(1)) and on a line adjacent to the outer
needle surface, starting from the needle tip and ending at the waveguide-
needle attachment (Figure 1B(2)).

### Cavitation

Cavitation experiments were performed in an acrylic chamber (external
dimensions = L $\times$ W $\times$ H = $21\text{\,}\mathrm{m}\mathrm{m}$
$\times$ $14\text{\,}\mathrm{m}\mathrm{m}$ $\times$
$15\text{\,}\mathrm{m}\mathrm{m}$, wall thickness =
$5\text{\,}\mathrm{m}\mathrm{m}$) filled with deionized water degassed to
$5.8\text{\,}\mathrm{mg}\text{\,}{\mathrm{L}}^{-1}$ (catalogue number:
11754266, Traceable Portable Dissolved Oxygen Meter, Fisherbrand, Fisher
Scientific, Hampton, NH, United States) (Figure 6B). The needle was immersed
to a depth of $45\text{\,}\mathrm{m}\mathrm{m}$ from the water surface and
subsequently actuated by a continuous sinusoidal signal in the frequency range
from $31\text{\,}\mathrm{kHz}$ to $32\text{\,}\mathrm{kHz}$ and emitted TAP of
$\sim$ $0.2\text{\,}\mathrm{W}$. HS recordings were taken in order to visually
capture the cavitation activity around the needle at different positions along
the needle length. More specifically 45 videos (sample rate =
$300\,000\text{\,}$ frames per second (fps), exposure =
$2.8\text{\,}\mathrm{\SIUnitSymbolMicro s}$, resolution = 128
pixels$\times$112 pixels, lens aperture = 3.3; lens model: Canon MP-E 65 mm)
were acquired, covering a total length of $45\text{\,}\mathrm{m}\mathrm{m}$
from the needle tip to the waveguide after vertical concatenation. These
settings permitted to achieve an image resolution of about
$9\text{\,}\mathrm{\SIUnitSymbolMicro}\mathrm{m}\mathrm{/}\mathrm{p}\mathrm{i}\mathrm{x}\mathrm{e}\mathrm{l}$.
The HS videos were finally analyzed by an algorithm implemented in MATLAB
(R2020b)[55] capable of tracking the needle position over time and quantify
the cavitation activity. The needle displacement along the x-axis from its
rest position was measured using sub-pixel image registration by cross-
correlation in the frequency domain[56] between the $i^{th}$ frame
$I_{i}(x,y)$ and the first frame $I_{1}(x,y)$ of the high speed footage as
follows:

$\displaystyle\Delta
x_{i}=\operatorname*{arg\,max}_{x}(FFT\\{I_{i}(x,y)\\}\cdot
FFT\\{I_{1}(x,y)\\}^{*})$ (2)

where $\Delta x_{i}$ is the measured needle x-displacement from the rest
position and $FFT$ is the two-dimensional fast Fourier transform. In order to
quantify the projected area of cavitation a new set of frames, where only the
cavitation activity is present, is created. This is done by subtracting the
reference image $I_{1}$ (rigidally translated by $\Delta x_{i}$ in order to
match the needle position in the $i^{th}$ frame) from each frame of the
original footage:

$\displaystyle
I_{cavitation,i}(x,y)=iFFT\\{(FFT\\{I_{i}(x,y)\\}-(FFT\\{I_{1}(x+\Delta
x_{i},y)\\}\\}$ (3)

where $iFFT$ is the two-dimensional discrete inverse Fourier transform. A
probability map $P_{cavitation}(x,y)$, in which the value of each pixel
represents the probability to observe a cavitation event in a specific
coordinate, is then measured as follows:

$\displaystyle
P_{cavitation}(x,y)=\frac{100}{N}\sum_{i=1}^{N}I_{cavitation,bw,i}(x,y),$ (4)

where $N$ is the total number of frames and $I_{cavitation,bw}(x,y)$ is a
frame-set generated by thresholding $I_{cavitation}(x,y)$ with the Otsu
method[57]. The projected area of cavitation as a function of time is then
obtained:

$\displaystyle A_{cavitation,i}=\int\int I_{cavitation,bw,i}(x,y)dx\kern
1.66672ptdy$ (5)

Finally, a total of 45 probability maps were vertically concatenated to
reproduce the entire length from the needle tip to the waveguide.

### Atomization

The purpose of this experiment was to demonstrate that with an ultrasonically
actuated needle one can eject micro-droplets from the needle tip surface and
control the droplet size distribution. A droplet of deionized water was
introduced near the needle tip, while the needle was operated in air (Figure
6C). HS recordings of the atomization process were acquired with the following
settings: sample rate = $16\,653\text{\,}\mathrm{f}\mathrm{p}\mathrm{s}$,
exposure = $10\text{\,}\mathrm{\SIUnitSymbolMicro s}$, resolution = 768 pixels
$\times$ 768 pixels, lens aperture = 16 (lens model: Canon MP-E 65 mm). The
video frames were then analyzed in MATLAB to determine the droplet size
distribution for different excitation frequencies and to compare it with
theoretical predictions. Each frame $I_{i}(x,y)$ was first segmented with an
adaptive thresholding[58]. Then, the built-in MATLAB function ‘regionprops’
was applied to measure the area and the equivalent diameter for each
8-connected component in the binary image $I_{bw,i}(x,y)$. Finally, the median
droplet diameter distribution was calculated over $N=1000$ randomly selected
frames and compared with theoretical predictions defined by Equation (1).

### Acoustic streaming

Polystyrene based microparticles with a diameter of
$30\text{\,}\mathrm{\SIUnitSymbolMicro m}$ (catalogue number: 84135-5ML-F,
Micro particles based on polystyrene analytical standard, size: 30 $\mu$m,
Sigma-Aldrich, St. Louis, MO, United States) were used to visualize their
translations near the needle tip. The test was conducted in a plastic cuvette
(external dimensions = L $\times$ W $\times$ H =
$12\text{\,}\mathrm{m}\mathrm{m}$ $\times$ $12\text{\,}\mathrm{m}\mathrm{m}$
$\times$ $45\text{\,}\mathrm{m}\mathrm{m}$, wall thickness =
$1\text{\,}\mathrm{m}\mathrm{m}$) filled with deionized water
($3\text{\,}\mathrm{m}\mathrm{L}$) with a particle concentration of 0.05% v/v
(Figure 6D). A low power continuous sinusoidal signal (TAP =
$0.1\text{\,}\mathrm{W}$) was applied to the needle, whose action was recorded
with the following care settings: sample rate =
$10\,000\text{\,}\mathrm{f}\mathrm{p}\mathrm{s}$, exposure =
$2\text{\,}\mathrm{\SIUnitSymbolMicro s}$, resolution = 1024 pixels $\times$
800 pixels, lens aperture = 2.8 (lens model: Canon MP-E 65 mm). An averaged
velocity field $\bar{V}(x,y)=\bar{v}_{x}\hat{x}+\bar{v}_{y}\hat{y}$, being
$\hat{x}$ and $\hat{y}$ unit vectors, was then calculated by employing a
cross-correlation technique[59]. Each frame $I_{i}(x,y)$ is divided into small
interrogation boxes of the size of 64 pixels $\times$ 64 pixels. Considering
$I_{i}(x,y)$ and $I_{i+1}(x,y)$to be the frames recorded at time $t$ and
$t+dt$ , let $f(x,y)$ be an interrogation box centered at specific location
$(x,y)$ in $I_{i}(x,y)$ and $g(x,y)$ an interrogation box centered at specific
location $(x,y)$ in $I_{i+1}(x,y)$. The displacement field $\vec{u}(x,y)$ of
two consecutive frames is calculated by measuring the offset $(\Delta x,\Delta
y)$ of the peak of the correlation map between $f(x,y)$ and $g(x,y)$ as
follows:

$\displaystyle\Delta x_{i}=\operatorname*{arg\,max}_{x}(FFT\\{g(x,y)\\}\cdot
FFT\\{f(x,y)\\}^{*}),$ (6) $\displaystyle\Delta
y_{i}=\operatorname*{arg\,max}_{y}(FFT\\{g(x,y)\\}\cdot FFT\\{f(x,y)\\}^{*}),$
$\displaystyle\vec{u}_{i}(x,y)=\Delta x_{i}(x,y)\hat{x}+\Delta
y_{i}(x,y)\hat{y}.$

The averaged velocity map is then calculated as:

$\displaystyle\bar{V}(x,y)=\frac{1}{N}\sum_{i=1}^{N}\frac{\partial}{\partial
t}\vec{u}_{i}(x,y),$ (7)

where $N=1000$ is the total number of frames.

### Schlieren imaging

The experiment was performed in a glass chamber (external dimensions = L
$\times$ W $\times$ H = $250\text{\,}\mathrm{m}\mathrm{m}$ $\times$
$250\text{\,}\mathrm{m}\mathrm{m}$ $\times$
$250\text{\,}\mathrm{m}\mathrm{m}$, wall thickness =
$4\text{\,}\mathrm{m}\mathrm{m}$) filled with deionized and degassed water of
temperature $T$ = $22\text{\,}\mathrm{\SIUnitSymbolCelsius}$ as measured by a
thermocouple thermometer (model: FLUKE T3000 FC, Fluke, Everett, WA, United
States). A laminar flow of water ($15\text{\,}\mathrm{\SIUnitSymbolCelsius}$,
$v$ = $0.3\text{\,}\mathrm{m}\text{\,}{\mathrm{s}}^{-1}$) emanating from a
secondary 21G needle directed towards SonoLancet (Figure 2B and 6E) was
generated on a plane parallel to the needle center axis. Ultrasound continuous
waves of $31.7\text{\,}\mathrm{k}\mathrm{H}\mathrm{z}$ and a TAP $\sim$
$0.8\text{\,}\mathrm{W}$ were applied to the needle for
$10\text{\,}\mathrm{s}$. HS Schlieren recordings of the disturbance of a water
laminar flow induced by the needle action were acquired (sample rate =
$100\,000\text{\,}\mathrm{f}\mathrm{p}\mathrm{s}$, exposure =
$0.357\text{\,}\mathrm{\SIUnitSymbolMicro s}$, resolution = 128 pixels
$\times$ 128 pixels, lens model: Canon EF-S 15-85 mm).

### Tissue phantom experiment

Experiments in a tissue phantom (10% w/v porcine gelatin/deionized water,
catalogue number: 53028, Gelatin from bovine and porcine bones for ballistic
analysis Type 1, Honeywell Fluka, Morris Plains, NJ, United States) were
carried out in combination with the ultrasonically actuated needle pre-filled
with contrast agent (0.1% w/v, fluorescent particles/deionized water,
catalogue number: 11894932, Fluoro-Max Dyed Red Aqueous Fluorescent Particles,
Thermo Fisher Scientific, Waltham, MA, United States). The needle was inserted
to a depth of $7\text{\,}\mathrm{m}\mathrm{m}$ from the gelatin surface,
penetrating three times the sample in order to let the contrast agent wet the
walls of the created cavity. Continuous ultrasound wave at
$31.4\text{\,}\mathrm{k}\mathrm{H}\mathrm{z}$ and TAP $\sim$
$0.8\text{\,}\mathrm{W}$ was applied to the needle for
$10\text{\,}\mathrm{s}$. HS videos of projections of the volume of interaction
between the gelatin and the SonoLancet were taken using the following
settings: sample rate = $1000\text{\,}\mathrm{f}\mathrm{p}\mathrm{s}$,
exposure = $10\text{\,}\mathrm{\SIUnitSymbolMicro s}$, resolution = 768 pixels
$\times$ 768 pixels, lens aperture = 16 (lens model: Canon MP-E 65 mm).
Optical projection tomography scanning of the sample was performed using an
OPT scanner (Bioptonics OPT 3001M Scanner). Reconstructed images (resolution =
512 pixels $\times$ 512 pixels), which represent the intersection between
planes perpendicular to the needle center-axis and the volume of actuation in
the tissue phantom, were generated using NRecon version 1.6.1.0 (Skyscan)
software and further analyzed in MATLAB. Each reconstructed image $I_{z}(x,y)$
was first thresholded with the Otsu method. A sequence of morphological
erosion and dilation using a disk-shaped structuring element of radius
$r=$10\text{\,}\mathrm{p}\mathrm{i}\mathrm{x}\mathrm{e}\mathrm{l}\mathrm{s}$$
was then applied to fill eventual gaps in the image and remove small unwanted
objects arising from noise. Contours of the sections, defined as sequences of
n contour points $\\{P_{0},P_{1},…,P_{n-1}\\}$, are extrapolated from the
images and filtered with a Savitzky-Golay finite impulse response (FIR)
smoothing filter (polynomial order = 2, window size = 11). Finally, the 3D
surface of actuation around the needle tip is constructed with triangular
elements and further adjusted in Fusion 360.

### USeFNAB

We quantified the ultrasound-tissue interaction by measuring the tissue yield
of ultrasound-enhanced fine-needle aspiration biopsies obtained from bovine
liver, kidney, spleen and muscle at 4 different TAP levels
($0\text{\,}\mathrm{W}$ control; sonication groups: $0.2\text{\,}\mathrm{W}$,
$0.5\text{\,}\mathrm{W}$, $0.8\text{\,}\mathrm{W}$) with the yield obtained
with the conventional fine-needle aspiration biopsy approach (FNAB control)
having the same syringe ($10\text{\,}\mathrm{m}\mathrm{L}$) and needle (21G
$\times$ $80\text{\,}\mathrm{m}\mathrm{m}$) as USeFNAB. Liver (from 33 months
old female bovine), kidney (from 33 months old male bovine), spleen (from 55
months old female bovine) and striated muscle (diaphragm, from 19 months old
female bovine) specimens were obtained from the slaughterhouse (Vainion
Teurastamo Oy, Orimattila, Finland) within $1\text{\,}\mathrm{h}$ post mortem
and experiments were performed 3-$5\text{\,}\mathrm{h}$ post mortem at room
temperature (22-$24\text{\,}\mathrm{\SIUnitSymbolCelsius}$). Only peripheral
parts of the same liver were used, to avoid large blood vessels and
acquisition of bloody samples. In liver and in spleen, samples were taken at a
depth of $2\text{\,}\mathrm{c}\mathrm{m}$ from the organ surface by keeping
the needle parallel to the table, where the target tissue is fixed throughout
the procedure. Sample acquisition in kidney was limited to the cortical area
and each biopsy was performed in different renal lobes, while, in muscle,
biopsies were taken along the fibre orientation. The used needles and syringes
were weighed before and after the biopsies using a balance with resolution of
$0.1\text{\,}\mathrm{m}\mathrm{g}$ (model: Quintix Precision Balance 5,100 g
$\times$10 mg, Sartorius AG, Germany) to measure the mass of the sample
extracted from the tissue. The test was divided into 6 sets of 5 repetition.
In each set, the order of the groups to be tested (FNAB (n = 6); USeFNAB:
$0\text{\,}\mathrm{W}$ (n = 6), $0.2\text{\,}\mathrm{W}$ (n = 6),
$0.5\text{\,}\mathrm{W}$ (n = 6) and $0.8\text{\,}\mathrm{W}$ (n = 6)) was
randomized with a random permutation within a set of five samples (one sample
from each group). The FNAB procedure consisted of inserting the tip of the
needle into the target tissue using a ‘fanning technique’, pulling the plunger
back to the $2\text{\,}\mathrm{m}\mathrm{L}$ mark and moving the needle back
and forth 7 times with a frequency of 1 pass per second. The penetration depth
was approximately $15\text{\,}\mathrm{m}\mathrm{m}$ at a targeted angular
offset of approximately $5\text{\,}\mathrm{\SIUnitSymbolDegree}$ between the
passes. The suction was maintained manually throughout the biopsy sampling by
keeping the plunger of the syringe at the the $2\text{\,}\mathrm{m}\mathrm{L}$
mark and only released after the needle was withdrawn[60]. The same procedure
was adopted for USeFNABs, where ultrasound continuous waves (f =
$31.7\text{\,}\mathrm{k}\mathrm{H}\mathrm{z}$, pulse repetition frequency
(PRF) = $55\text{\,}\mathrm{H}\mathrm{z}$, duty cycle (DC) =
$52.05\text{\,}\%$) were applied throughout the biopsy after the needle was
inserted into the tissue. The selected parameters of the protocol were
considered appropriate to obtain a sufficient amount of sample for yield
analysis or to be processed into agarose cell blocks. The operator skills in
performing the biopsy and the protocol were confirmed by a specialist in
radiology (J.K.) with considerable experience in FNAB. Assuming that normal
distribution does not apply, the FNAB mass was compared to the masses of
USeFNAB groups using Mann–Whitney U test. The Bonferroni-corrected level of
statistical significance was 0.0125.

### Histology

Biopsy samples were processed into agarose cell blocks for histological
assessment[61]. Aspirates were expressed into
$1.5\text{\,}\mathrm{m}\mathrm{L}$ tubes (11569914, Snap Cap Low Retention
Microcentrifuge Tubes, Thermo Fisher Scientific, Waltham, MA, United States)
containing $500\text{\,}\mathrm{\SIUnitSymbolMicro L}$ of 1x PBS (BP399-4,
Phosphate Buffered Saline, 10X Solution, Fisher BioReagents, Fisher
Scientific, Hampton, NH, United States) and subjected to centrifugation at
$500\text{\,}\mathrm{G}$ for $5\text{\,}\mathrm{min}$. After a second PBS
washing, pellets were resuspended in $500\text{\,}\mathrm{\SIUnitSymbolMicro
L}$ of 10% neutral buffered formalin (15817114, HistoTainer, Simport, Saint-
Mathieu-de-Beloeil, Quebec, Canada). After $10\text{\,}\mathrm{min}$ of
incubation time, tubes were centrifuged at $500\text{\,}\mathrm{G}$ for
$5\text{\,}\mathrm{min}$, then, the supernatant was carefully discarded, and
pellets were washed in PBS twice. Excess PBS was carefully removed and
formalin fixed pellets were resuspended in
$100\text{\,}\mathrm{\SIUnitSymbolMicro L}$ of molten agarose (10377033,
Agarose Low-Melting, Nucleic Acid Recovery/Molecular Biology Grade, Thermo
Fisher Scientific, Waltham, MA, United States) kept at
$42\text{\,}\mathrm{\SIUnitSymbolCelsius}$ and gently centrifuged at
$180\text{\,}\mathrm{G}$ for $1\text{\,}\mathrm{min}$. The agarose cell blocks
were let solidify at $4\text{\,}\mathrm{\SIUnitSymbolCelsius}$ and then
transferred into 70% v/v ethanol (172381, 70% v/v Ethanol Solution Molecular
Biology Grade, Fisher Scientific, Hampton, NH, United States) pre-filled
tubes. Several sections of the paraffin embedded cell blocks (4 to 5 for each
sample) were cut at $5\text{\,}\mathrm{\SIUnitSymbolMicro m}$ thickness,
mounted on $25\text{\,}\mathrm{m}\mathrm{m}$ $\times$
$75\text{\,}\mathrm{m}\mathrm{m}$ slides (J1800AMNZ, SuperFrost Plus Adhesion
slides, Thermo Fisher Scientific, Waltham, MA, United States) and stained with
hematoxylin and eosin (H&E). Finally, microscopy pictures (bright field, 20x
magnification, extended focus) were generated using 3DHISTECH Panoramic 250
FLASH II digital slide scanner. Four biopsy samples (liver, n = 1; spleen, n =
1; muscle, n = 2) failed to be processed for histological analysis due to
breakage of the agarose cell block.

### Quantification of sample fragmentation

A supervised classification method has been implemented in MATLAB to quantity
the fragmentation of the liver samples by means of feature extraction of
objects identified in the histological images[62](Figure 7). The
classification algorithm is able to detect four different histological
structures, namely tissue fragments (large regions of adjacent hepatocytes),
cell clusters (small aggregation of hepatocytes), single cells and debris
(organic waste). The dataset is composed of 29 histological slides belonging
to the following sample groups: FNAB (n = 5); USeFNAB: $0\text{\,}\mathrm{W}$
(n = 6), $0.2\text{\,}\mathrm{W}$ (n = 6), $0.5\text{\,}\mathrm{W}$ (n = 6)
and $0.8\text{\,}\mathrm{W}$ (n = 6). Each image $I_{h}(x,y)$ was first
converted into gray-scale image and then subjected to thresholding using the
Otsu method. The the Moore-Neighbor tracing algorithm modified by Jacob’s
stopping criteria[63] was applied to trace the boundaries of all 8-connected
objects detected in the binary image $I_{bw,h}(x,y)$. The objects were
assigned to a certain class based on a similarity score method defined as
follows:

$\displaystyle C=\operatorname*{arg\,min}_{k}S(x_{i},k),$ (8) $\displaystyle
S(x_{i},k)=\sum_{m=1}^{M}\frac{|x_{i,m}-b_{k,m}|}{c_{k,m}},$ $\displaystyle
b_{k,m}=\frac{1}{N}\sum_{n=1}^{N}Y_{k,m,n},$ $\displaystyle
c_{k,m}=\sqrt{\frac{1}{N}\sum_{n=1}^{N}(Y_{k,m,n}-b_{k,m})^{2}}.$

In the above, $C$ is the the output class which each object is assigned to by
the classifier, $x_{i}$ is a vector containing a number $M$ of morphological
features (i.e. area, eccentricity, circularity, solidity, etc.) extracted from
the $i_{th}$ object and $k$ is an integer number corresponding to a certain
class (1 = tissue fragments; 2 = cell clusters; 3 = single cells; 4 = debris).
$S(x_{i},k)$ is the score function whose output value denotes how well an
object is represented by a class $k$ (the lower the score, the higher the
similarity). $Y_{k}$ is a $M\times N$ matrix containing feature vectors
belonging to pre-classified objects that were priorly assigned to a class $k$
in the supervised learning phase. Finally, several indicators of sample
fragmentation (i.e. total number of tissue fragments, cell clusters, single
cells, debris pieces and their respective average area) were extracted and
used for statistical comparison between the FNAB and USeFNAB groups. Assuming
that normal distribution does not apply, the Mann–Whitney U test was chosen,
with a Bonferroni-corrected level of statistical significance of 0.0125.

## References

  * [1] Kirkup, J.  The history and evolution of surgical instruments. V needles and their penetrating derivatives.  _Annals of the Royal College of Surgeons of England_ 68, 29–33 (1986).
  * [2] Bynum, B. & Bynum, H.  Lancet.  _The Lancet_ 386, 945, DOI: 10.1016/S0140-6736(15)00108-7 (2015).
  * [3] Kucklick, T.  Introduction to Needles and Cannulae.  In _The Medical Device R &D Handbook_, chap. 5, 89–112, DOI: 10.1201/9781420038354.ch5 (CRC Press, FL, USA, 2005).
  * [4] Wang, Y., Tai, B. L., Chen, R. K. & Shih, A. J.  The needle with lancet point: Geometry for needle tip grinding and tissue insertion force.  _Journal of Manufacturing Science and Engineering, Transactions of the ASME_ 135, 1–7, DOI: 10.1115/1.4023718 (2013).
  * [5] Han, P., Che, D., Pallav, K. & Ehmann, K.  Models of the cutting edge geometry of medical needles with applications to needle design.  _International Journal of Mechanical Sciences_ 65, 157–167, DOI: 10.1016/j.ijmecsci.2012.09.014 (2012).
  * [6] Hauri, A. M., Armstrong, G. L. & Hutin, Y. J.  The global burden of disease attributable to contaminated injections given in health care settings.  _International Journal of STD and AIDS_ 15, 7–16, DOI: 10.1258/095646204322637182 (2004).
  * [7] Hamilton, J. G.  Needle phobia: A neglected diagnosis.  _Journal of Family Practice_ 41, 169–175 (1995).
  * [8] Jenkins, K.  Needle phobia: A psychological perspective, DOI: 10.1093/bja/aeu013 (2014).
  * [9] American Psychiatric Association.  Diagnostic and Statistical Manual of Mental Disorders (DSM-5®) - American Psychiatric Association - Google Books (2013).
  * [10] Ayala, E. S., Meuret, A. E. & Ritz, T.  Treatments for blood-injury-injection phobia: A critical review of current evidence, DOI: 10.1016/j.jpsychires.2009.04.008 (2009).
  * [11] Rossa, C., Sloboda, R., Usmani, N. & Tavakoli, M.  Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy.  _Int. J. Comput. Assist. Radiol. Surg._ 11, 1347–1359, DOI: 10.1007/s11548-015-1329-4 (2016).
  * [12] Wan, G., Wei, Z., Gardi, L., Downey, D. B. & Fenster, A.  Brachytherapy needle deflection evaluation and correction.  _Med. Phys._ 32, 902–909, DOI: 10.1118/1.1871372 (2005).
  * [13] Ji, H. Y., Kim, E. K., Min, J. K., Ji, Y. L. & Ki, K. O.  Missed breast cancers at us-guided core needle biopsy: How to reduce them.  _Radiographics_ 27, 79–94, DOI: 10.1148/rg.271065029 (2007).
  * [14] Pritzker, K. P. & Nieminen, H. J.  Needle biopsy adequacy in the era of precision medicine and value-based health care.  _Archives of Pathology and Laboratory Medicine_ 143, 1399–1415, DOI: 10.5858/arpa.2018-0463-RA (2019).
  * [15] Gutierrez, M. E. _et al._ Genomic Profiling of Advanced Non–Small Cell Lung Cancer in Community Settings: Gaps and Opportunities.  _Clinical Lung Cancer_ 18, 651–659, DOI: 10.1016/j.cllc.2017.04.004 (2017).
  * [16] E, C., Dahrouge, S., Samant, R., Mirzaei, A. & Price, J.  Radical radiotherapy for cervix cancer: The effect of waiting time on outcome.  _International Journal of Radiation Oncology Biology Physics_ 61, 1071–1077, DOI: 10.1016/j.ijrobp.2004.09.030 (2005).
  * [17] Gui, L. _et al._ Automatic frequency tracking system for needle actuating device.  _IEEE International Ultrasonics Symposium, IUS_ 815–818, DOI: 10.1109/ULTSYM.2014.0200 (2014).
  * [18] Kuang, Y. _et al._ Modelling and characterisation of a ultrasound-actuated needle for improved visibility in ultrasound-guided regional anaesthesia and tissue biopsy.  _Ultrasonics_ 69, 38–46, DOI: 10.1016/j.ultras.2016.02.018 (2016).
  * [19] Liao, X. _et al._ Performance optimization of ultrasonic needle actuating device for insertion operation into tissue mimics.  In _IEEE International Ultrasonics Symposium, IUS_ , 823–826, DOI: 10.1109/ULTSYM.2014.0202 (IEEE, IL, USA, 2014).
  * [20] Liao, X., Sadiq, M., Corner, G., Cochran, S. & Huang, Z.  Reduced penetration force through ultrasound activation of a standard needle: An experimental and computational study.  _IEEE International Ultrasonics Symposium, IUS_ 1, 1436–1439, DOI: 10.1109/ULTSYM.2013.0364 (2013).
  * [21] Kundan, K. K., Laha, S. & Ghatak, A.  Vibration assisted puncturing of a soft brittle solid.  _Extreme Mechanics Letters_ 26, 26–34, DOI: 10.1016/j.eml.2018.11.006 (2019).
  * [22] Kaushik, S. _et al._ Lack of pain associated with microfabricated microneedles.  _Anesthesia and Analgesia_ 92, 502–504, DOI: 10.1213/00000539-200102000-00041 (2001).
  * [23] Gao, X. _et al._ Design and Simulation Optimization of a Novel Oocyte Ultrasonic Micro-dissection Instrument.  In _2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018_ , 591–596, DOI: 10.1109/ICARCV.2018.8581216 (Institute of Electrical and Electronics Engineers Inc., Singapore, Singapore, 2018).
  * [24] Bahadur, I. M., Wong, C. Y., Jiang, X. & Mills, J. K.  Dynamic modelling and embryo zona pellucida perforation experiments with piezoelectric actuated micro-needles.  In _2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017_ , 445–450, DOI: 10.1109/ICMA.2017.8015858 (Institute of Electrical and Electronics Engineers Inc., 2017).
  * [25] Wu, T., Zhou, Z., Wang, Q., Yang, X. & Xiao, M.  A Miniature Probe for Ultrasonic Penetration of a Single Cell.  _Sensors_ 9, 3325–3336, DOI: 10.3390/s90503325 (2009).
  * [26] Johnson, W. _et al._ A Flexure-Guided Piezo Drill for Penetrating the Zona Pellucida of Mammalian Oocytes.  _IEEE Transactions on Biomedical Engineering_ 65, 678–686, DOI: 10.1109/TBME.2017.2713302 (2018).
  * [27] Yanagida, K. _et al._ The usefulness of a piezo-micromanipulator in intracytoplasmic sperm injection in humans.  _Human Reproduction_ 14, 448–453, DOI: 10.1093/humrep/14.2.448 (1999).
  * [28] Kreula, J., Virkkunen, P. & Bondestam, S.  Effect of suction on specimen size in fine-needle aspiration biopsy.  _Investigative Radiology_ 25, 1175–1181, DOI: 10.1097/00004424-199011000-00005 (1990).
  * [29] Dayton, P., Klibanov, A., Brandenburger, G. & Ferrara, K.  Acoustic radiation force in vivo: A mechanism to assist targeting of microbubbles.  _Ultrasound in Medicine and Biology_ 25, 1195–1201, DOI: 10.1016/S0301-5629(99)00062-9 (1999).
  * [30] Nyborg, W. L.  Acoustic Streaming near a Boundary.  _Journal of the Acoustical Society of America_ 30, 329–339, DOI: 10.1121/1.1909587 (1958).
  * [31] Neppiras, E. A. & Noltingk, B. E.  Cavitation produced by ultrasonics: Theoretical conditions for the onset of cavitation.  _Proceedings of the Physical Society. Section B_ 64, 1032–1038, DOI: 10.1088/0370-1301/64/12/302 (1951).
  * [32] Holland, C. K. & Apfel, R. E.  Thresholds for transient cavitation produced by pulsed ultrasound in a controlled nuclei environment.  _Journal of the Acoustical Society of America_ 88, 2059–2069, DOI: 10.1121/1.400102 (1990).
  * [33] Collis, J. _et al._ Cavitation microstreaming and stress fields created by microbubbles.  _Ultrasonics_ 50, 273–279, DOI: 10.1016/j.ultras.2009.10.002 (2010).
  * [34] Brujan, E. A., Ikeda, T. & Matsumoto, Y.  Jet formation and shock wave emission during collapse of ultrasound-induced cavitation bubbles and their role in the therapeutic applications of high-intensity focused ultrasound.  _Physics in Medicine and Biology_ 50, 4797–4809, DOI: 10.1088/0031-9155/50/20/004 (2005).
  * [35] Sapozhnikov, O. A. & Bailey, M. R.  Radiation force of an arbitrary acoustic beam on an elastic sphere in a fluid.  _The Journal of the Acoustical Society of America_ 133, 661–676, DOI: 10.1121/1.4773924 (2013).
  * [36] Vukasinovic, B., Smith, M. K. & Glezer, A.  Mechanisms of free-surface breakup in vibration-induced liquid atomization.  _Physics of Fluids_ 19, DOI: 10.1063/1.2434799 (2007).
  * [37] Rajan, R. & Pandit, A. B.  Correlations to predict droplet size in ultrasonic atomisation.  _Ultrasonics_ 39, 235–255, DOI: 10.1016/S0041-624X(01)00054-3 (2001).
  * [38] Bader, K. B., Haworth, K. J., Maxwell, A. D. & Holland, C. K.  Post Hoc Analysis of Passive Cavitation Imaging for Classification of Histotripsy-Induced Liquefaction in Vitro.  _IEEE Transactions on Medical Imaging_ 37, 106–115, DOI: 10.1109/TMI.2017.2735238 (2018).
  * [39] Barreras, F., Amaveda, H. & Lozano, A.  Transient high-frequency ultrasonic water atomization.  _Experiments in Fluids_ 33, 405–413, DOI: 10.1007/s00348-002-0456-1 (2002).
  * [40] James, A. J., Vukasinovic, B., Smith, M. K. & Glezer, A.  Vibration-induced drop atomization and bursting.  _Journal of Fluid Mechanics_ 476, 1–28, DOI: 10.1017/s0022112002002835 (2003).
  * [41] Ueha, S., Mori, E. & Maehara, N.  Mechanism of ultrasonic atomization using a multipinhole plate.  _Journal of the Acoustical Society of Japan (E)_ 6, 21–26, DOI: 10.1250/ast.6.21 (1985).
  * [42] Carson, H. J., Saint Martin, G. A., Castelli, M. J. & Gattuso, P.  Unsatisfactory aspirates from fine-needle aspiration biopsies: A review.  _Diagnostic Cytopathology_ 12, 280–284, DOI: 10.1002/dc.2840120319 (1995).
  * [43] Nassar, A.  Core needle biopsy versus fine needle aspiration biopsy in breast-A historical perspective and opportunities in the modern era.  _Diagnostic Cytopathology_ 39, 380–388, DOI: 10.1002/dc.21433 (2011).
  * [44] Brennen, C. E.  Cavitation in medicine.  _Interface Focus_ 5, 1–12, DOI: 10.1098/rsfs.2015.0022 (2015).
  * [45] Zhou, Y.-F.  High intensity focused ultrasound in clinical tumor ablation.  _World Journal of Clinical Oncology_ 2, 8, DOI: 10.5306/wjco.v2.i1.8 (2011).
  * [46] Mehier-Humbert, S., Bettinger, T., Yan, F. & Guy, R. H.  Plasma membrane poration induced by ultrasound exposure: Implication for drug delivery.  _Journal of Controlled Release_ 104, 213–222, DOI: 10.1016/j.jconrel.2005.01.007 (2005).
  * [47] Chettab, K. _et al._ Spatial and temporal control of cavitation allows high in vitro transfection efficiency in the absence of transfection reagents or contrast agents.  _PLoS ONE_ 10, DOI: 10.1371/journal.pone.0134247 (2015).
  * [48] Hernot, S. & Klibanov, A. L.  Microbubbles in ultrasound-triggered drug and gene delivery.  _Advanced Drug Delivery Reviews_ 60, 1153–1166, DOI: 10.1016/j.addr.2008.03.005 (2008).
  * [49] Akhatov, I. _et al._ Collapse and rebound of a laser-induced cavitation bubble.  _Physics of Fluids_ 13, 2805–2819, DOI: 10.1063/1.1401810 (2001).
  * [50] Yoshizawa, S. _et al._ High intensity focused ultrasound lithotripsy with cavitating microbubbles.  _Medical and Biological Engineering and Computing_ 47, 851–860, DOI: 10.1007/s11517-009-0471-y (2009).
  * [51] Siegel, R. J. _et al._ Ultrasonic plaque ablation: A new method for recanalization of partially or totally occluded arteries.  _Circulation_ 78, 1443–1448, DOI: 10.1161/01.CIR.78.6.1443 (1988).
  * [52] Bailey, M. R., Khokhlova, V. A., Sapozhnikov, O. A., Kargl, S. G. & Crum, L. A.  Physical mechanisms of the therapeutic effect of ultrasound.  _Akusticheskij Zhurnal_ 49, 437–465 (2003).
  * [53] Mitragotri, S.  Healing sound: The use of ultrasound in drug delivery and other therapeutic applications.  _Nature Reviews Drug Discovery_ 4, 255–260, DOI: 10.1038/nrd1662 (2005).
  * [54] COMSOL Multiphysics.  Available at: www.comsol.com (2020).
  * [55] Mathworks.  MATLAB.  Available at: www.mathworks.com (2016).
  * [56] Guizar-Sicairos, M., Thurman, S. T. & Fienup, J. R.  Efficient subpixel image registration algorithms.  _Optics Letters_ 33, 156, DOI: 10.1364/ol.33.000156 (2008).
  * [57] Otsu & N.  A threshold selection method from gray-level histograms.  _IEEE Trans. on Systems, Man and Cybernetics_ 9, 62–66 (1996).
  * [58] Bradley, D. & Roth, G.  Adaptive Thresholding using the Integral Image.  _Journal of Graphics Tools_ 12, 13–21, DOI: 10.1080/2151237x.2007.10129236 (2007).
  * [59] Jambunathan, K., Ju, X. Y., Dobbins, B. N. & Ashforth-Frost, S.  An improved cross correlation technique for particle image velocimetry.  _Measurement Science and Technology_ 6, 507–514, DOI: 10.1088/0957-0233/6/5/012 (1995).
  * [60] Kreula, J., Bondestam, S. & Virkkunen, P.  Sample size in fine needle aspiration biopsy.  _British Journal of Surgery_ 76, 1270–1272, DOI: 10.1002/bjs.1800761216 (1989).
  * [61] Koh, C. M.  Preparation of cells for microscopy using ’cell blocks’.  In _Methods in Enzymology_ , vol. 533, chap. 16, 249–255, DOI: 10.1016/B978-0-12-420067-8.00018-0 (Academic Press, MA, USA, 2013).
  * [62] Kumar, R., Srivastava, R. & Srivastava, S.  Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features.  _Journal of Medical Engineering_ 2015, 1–14, DOI: 10.1155/2015/457906 (2015).
  * [63] Gonzalez, R., Woods, R. & Eddins, S.  _Digital image processing using MATLAB_ (2004).

## Acknowledgements

We thank Mr. Matti Mikkola, M.Sc., Mr. Yohann Le Bourlout, M.Sc., Mr. Pauli
Tuovinen, B.Sc. Nallannan Balasubramanian, Ph.D. and Adjunct Prof. Gösta
Ehnholm, Ph.D., for constructive discussions related to the topic, and Dr.
Nick Hayward, MBBS, Ph.D. for linguistic review of the manuscript. We thank
Jyrki Kreula, MD, Ph.D. for guidance and providing us extensive information
related to the FNAB procedure. We also would like to thank Prof. Kari Eklund,
MD, Ph.D. for support in histological experimentation. We thank the Tissue
Preparation and Histochemistry Unit in the Department of Anatomy, University
of Helsinki. Histology images were generated using the 3DHISTECH Pannoramic
250 FLASH II digital slide scanner at Genome Biology Unit supported by HiLIFE
and the Faculty of Medicine, University of Helsinki, and BioCenter Finland.
The Academy of Finland is acknowledged for financial support (grants 314286
and 311586).

## Author contributions statement

All authors contributed to the design of the study, writing or reviewing the
manuscript and have approved the final version of the manuscript. Emanuele
Perra produced all data and conducted all data analysis, except Kenneth
Pritzker and Emanuele Perra also analyzed the histology images. Emanuele Perra
was responsible for the histology process.

## Conflict of Interest

Heikki Nieminen, Kenneth Pritzker, Edward Hæggström and Eetu Lampsijärvi have
stock ownership in Swan Cytologics Inc., Toronto, ON, Canada and are inventors
within the patent application WO2018000102A1. Emanuele Perra, Gonçalo Barreto,
Muhammad Arif and Tuomas Puranen do not have any competing interests in
relation to this work.

## Data availability

The datasets are available upon request.

## Code availability

The codes are available upon request.

Figure 1: (A(1)) Schematic represents the investigational device that
comprises a conventional Langevin ultrasound transducer coupled via an
aluminum waveguide to a (A(2-3)) 21G hypodermic needle connected to a
$10\text{\,}\mathrm{m}\mathrm{L}$ syringe. The geometry permits connecting
virtually any pressure source to the needle. (B(1)) Numerical simulation
result representing the x-component of the time-average acoustic intensity
evaluated on the xy-plane coincident with the needle center axis and on a line
adjacent to the outer needle surface, starting from the needle tip and ending
at the waveguide-needle attachment. These results demonstrate localization of
sound energy at the very tip of the needle, more than double the intensity
calculated elsewhere. (C(1)) The cavitation activity is highly concentrated at
the needle tip, as supported by (C(2)) the projected spatial probability of
cavitation in deionized water ([$O_{2}$]
$5.8\text{\,}\mathrm{mg}\text{\,}{\mathrm{L}}^{-1}$). (D,E,F) Temporally we
observed a cavitation onset after which the inertial cavitation events
continued in an uninterrupted manner. (G) The applied ultrasound induced peak
velocities up to $5\text{\,}\mathrm{m}\text{\,}{\mathrm{s}}^{-1}$ and (H)
acceleration of the bubble and water boundary that was equivalent to
$20\,000\text{\,}\mathrm{G}$. The results demonstrate that a conventional
medical needle can be converted into a highly controlled, ultrasonically
functionalized instrument with significant NLU phenomena concentrated at the
very tip of the needle. Figure 2: (A) $30\text{\,}\mathrm{\SIUnitSymbolMicro
m}$ diameter polystyrene microparticles were used to visualize the water flow
pattern around the needle during sonication. The graph represents the time-
averaged velocity field of the particles, calculated across a time window of
$100\text{\,}\mathrm{m}\mathrm{s}$. (B) Schlieren images show the disturbance
of water laminar flow induced by the needle action as a demonstration of
acoustic streaming taking place around the needle tip during sonication. (C)
The droplet size distribution was controlled with ultrasonic driving
frequencies and followed the theoretical relationship. This is exemplified in
HS imaging (D), which revealed micro-droplet ejections of water at different
driving frequencies from a main water drop hanging from the needle when the
needle was embedded in air. (A, B) The results demonstrate the capability of
SonoLancet to induce mass transfer as well as (C, D) controlling the size of
atomized droplets. On each box, the central mark represents the median, and
the lower and upper edges of the box indicate the 25th and 75th percentiles,
respectively. The whiskers extend to the most extreme values of the data set
excluding the outliers, and the outliers are plotted individually with non-
filled circles. Figure 3: (A) HS imaging of experiments in tissue phantom (10%
w/v ballistic gelatin/deionized water) reveals projections of the volume of
interaction between the gelatin and the Sonance at different time points
during continuous sonication. (B) A 3D reconstruction of the actuated region
was produced by examining the sample under optical projection tomography. (C)
The mass of extracted sample in ultrasound enhanced biopsies performed in
bovine (C(1)) liver, (C(2)) kidney, (C(3)) spleen and (C(4)) muscle at
different power levels compared to the standard FNAB. The needle employed in
FNAB and ultrasound-enhanced FNAB (USeFNAB) was the same 21G needle. In the
bar charts, the bar height represents the mean of the data set and the error
bar indicates the standard deviation. Individual data points are shown as
white-filled circles. Figure 4: Histological pictures (20x) of cell block
sections prepared from biopsy aspirates taken from different bovine organs
(top to bottom: liver, kidney, spleen and muscle) at different TAP levels
(left to right: FNAB, USeFNAB 0 W, 0.2 W, 0.5 W and 0.8 W). The results
demonstrated that different tissue types included histopathologically relevant
cells or tissue constructs, suggesting that SonoLancet could allow
histopathological evaluation of samples in selected FNAB applications, if
developed to its full potential. Figure 5: (A) Computer assisted evaluation of
tissue fragmentation in liver biopsy samples. (A(1)) represents exemplary
histological images used for the analysis. (A(2,3)) show the classified images
where tissue fragments, cell clusters, single cells and debris are detected
and highlighted in green, blue, red and black, respectively. (B(1)) The
relative total area of tissue fragments, (B(2)) cell clusters, (B(3)) single
cells, (B(4)) debris pieces were calculated and used for statistical
comparison between the FNAB and USeFNAB groups. In the bar charts, the bar
height represents the mean of the data set and the error bar indicates the
standard deviation. Individual data points are shown as white-filled circles.
Figure 6: Experimental arrangements: (A) Simplified schematics of the
ultrasound system arrangement with optical detection of needle tip activity,
(B) cavitation experiment, (C) atomization experiment, (D) acoustic streaming
experiment and the (E) Schlieren imaging experiment. Figure 7: General
description of the classification process. During the training phase a number
N of randomly selected unclassified objects objects are selected from the data
and firstly assigned to one of the output classes (tissue fragment, cell
cluster, single cell, debris) by a user. Several morphological features (area,
eccentricity, circularity, etc.) are then extracted from such objects and used
as classification criteria during the classification phase.