Hello, and welcome to the Physics World Weekly
podcast. I'm Hamish Johnston.
Coming up in this episode, we meet Daniel
Sarno,
who is a cofounder
and chief technology officer of Sona.
Based at The UK's
National Physical Laboratory,
Sona is developing a new method for determining
breast tissue density
using ultrasound
rather than conventional x-ray based mammography.
Sarno explains
how this can help improve
the early detection
of breast cancer.
But first, I'm in conversation
with Bhaskaran
Muraleed Haran,
who is at the Indian Institute of Technology,
Bombay.
An engineer by training, he has a keen
interest in using computational physics to develop new
materials and devices
for quantum science and technology.
I began the interview
by asking about how computational science
is being used to create
new quantum materials.
So
in order to so the next generation of
quantum technologies
will feature
what is called quantum hardware. And the quantum
hardware is obviously devices.
And just like you have the
complementary MOS or the CMOS being the building
block of the digital technology,
you will have building blocks based on quantum
devices for the next
generation or the upcoming quantum technologies.
For example, the, superconducting qubit, that's a device.
So
just like in the CMOS era,
the
the industry relied on device modeling as an
important aspect of, you know, giving feedback to
experiments.
So there's whole there's this whole thing about
a feedback between theory and experiment and and
as to achieve a synergy between theory and
experiment.
So that first experiment
is understood via theory
and then the theory can probably predict something
new. And the experiment can go toward that
step and back and forth and,
you know, that's how things develop.
Another thing is theory is also useful in
giving
inputs about
possibly new materials that can achieve the same
functionality.
One great example
is just before
we are in what is called the Beyond
Moore era, where devices are shrinking toward the
limits
and people are looking at alternate technologies.
One of the technologies
just before all this quantum,
revolution started was Spintronics.
Spintronics is the technology
or the
or what's called the paradigm which tries to
use spins or the electron spins
as a medium of information.
Just like you have the charge, which is
basically the charge of the electron,
you also each electron comes with a spin.
And in high school, you would have studied
up spin and down spin. That can be
units of information.
So one of the things computation
did is that they predicted a new material
called magnesium oxide,
which can produce a better spintronic device. And
lo and behold, that tech the magnesium oxide
based,
Spintronic devices are getting close to, you know,
being in the market or something like that.
This is an example where theory can predict
a new functionality
and eventually lead to new developments.
The same goes with probably
several nice ideas can come from theory.
And computational
is the computational
modeling is the next step. Theory is more
like at the level where you can come
up with neat ideas from physics.
Then comes the actual computational modeling where you
try to simulate possibly the actual device situation.
And that is more hands on towards
talking to experimentalists or talking towards technology, etcetera.
So another example is back in the ninety's
sorry, back in the early two thousand's, people
were trying out carbon nanotube transistors as a
possible next generation. And that's when a lot
of theorists were working
at the level of understanding how carbon nanotubes
can behave like transistors, etc. Today, there's a
lot of computational theory which working on two
d materials.
And especially
toward
transistor technologies, etcetera,
on molybdenum disulfide and various other materials.
The same way I could say that theory
and modeling helps
in many ways. One is, of course, there's
a lot of work on superconducting qubits.
And then from the superconducting
qubits, you need to achieve
communications
between these qubits.
So there's a lot of theory and modeling
at that level where you can understand and
go towards the
various layers that are involved in the quantum
technology.
You have the building block that is a
qubit.
Just like the transistor was a building block.
Then you have, you put them into circuits
and then you make them into a processor.
The same way we are hoping that quantum
technology will reach a processor level.
And at that level, you have a lot
of scope for computational engineers to sort of
help and improve the designs and things like
that.
So can you talk a bit about some
of the materials that you're investigating
at the moment? What are the hot materials
at the moment
for,
quantum Yeah. Technologies? Yep. So when we talk
about quantum technologies,
the first building block is a qubit or
the quantum bit.
And to realize quantum bit already or the
qubit, there are already many platforms.
I would just trace back to 1926
for a second.
At that point of time,
they predicted that a device called the MOSFET
or what's called metal oxide semiconductor
field effect is possible.
But no one took that for serious,
no one took that to serious notice.
And the bipolar junction transistor was invented in
somewhere around 1949.
And the inventors were back then asked, what
is the application?
Bardeen, Bertain and Shockley.
John Bardeen just came up and said, probably
it's a good amplifier. It can be used
as a hearing aid.
Now you can believe it. The transistor changed
the world.
And I think in nineteen fifties, someone took
up the field effect transistor
and then rest is history. Whatever the patent
was filed in 1924,
in nineteen fifties it came up. So here's
the deal.
Lots of competing
technologies or paradigms exist much before the real
one takes on and becomes
the true, you know, life changing technology. So
at this stage, at the nascent stage, we
have several candidates for the qubits. One is
a superconducting
qubit which is reasonably mature.
We are looking into superconducting
hybrid systems for that purpose to understand
the inner workings of the superconducting qubit device.
And at more exploratory levels or not
not so much nascent, but somewhere in between
we have the silicon qubits
and donor qubits and various types of materials
that are surrounding the silicon.
The ambition is to integrate silicon into cubits.
And so silicon cubits are also quite actively
investigated and we are also doing a lot
of work on understanding
the devices that
make these qubits.
The third one is for other quantum technologies.
Those are technologies that are not just necessarily
qubits but
maybe for single photon detection
or surrounding various other
applications
that come under the quantum umbrella.
You have a lot of materials like tungsten
telluride. So a lot of two d materials
are under a lot of investigation
for various applications
surrounding this whole quantum technology, which we are
also actively looking at. For instance, tungsten telluride
is a material that is known to be
something called a topological insulator.
Now a topological insulator is an interesting material
that sort
of conducts
what is called very pristine edge states that
are not
or that are
that do not have
what you call traditional words dissipation.
Now dissipation is like think about cars in
a traffic and a lot of people around.
Your car cannot go smoothly.
But these are materials
that can go in such an environment, but
on the edges, they conduct so well that
it's almost like edges of freeways
where you go
without scattering with anyone. But the bulk of
the material is like a crowded road.
So this kind of a new material gives
you very interesting properties which can be used
for various quantum applications.
It can also be used for classical applications.
So these are the classes of materials we
look at. And the word is a nice
word for these. It's called quantum materials.
Now you might ask every material could be
quantum. The answer is
it's not like that.
Quantum materials are special because
you can see their if I can we
finally use the word, quantumness
at longer length scales. For instance, when you
measure the resistance of a topological material, it
will show you something that's quantized
at
there's a standard number for that. But yeah.
So it will show you a quantized resistance
and things like that. So these are materials
that can be used for various surrounding quantum
technologies
That include,
photon detection
and materials.
They could be also what's called peripheral technologies,
the qubit technologies and various things like that.
So we are at an exciting phase and
world is changing rapidly. There are lots of
materials to investigate.
And every day there's a new breakthrough and
we hope to sort of ride the wave
with our research. Right. And and and what
about at the at the device level?
What what what sort of devices are you
are you interested in studying
from a computational point of view at the
moment?
Yes. Thank you.
So the devices I work on are specifically
related to two things. One is the qubits
stem cells. How
how to make better qubits with the existing
devices. So in that sense, we look at
what is called quantum dot devices.
These devices can host what is called, for
instance, silicon qubits or spin qubits.
These are one type of qubit. As I
said, there are many competing qubit
technologies. The other devices we look at are
superconducting hybrid systems as I said. One of
which is a reasonably mature technology, it's called
the transmon qubit, which is based on superconductors.
There are other qubits that are also being
currently investigated.
And there are many advantages slash disadvantages at
at the level of each platform.
So one of the things that would come
up next is a hybrid quantum system that
could actually leverage the advantages of various
types of, systems,
bring them together for a quantum processing. So
in that sense, we are looking at two
d materials for qubits.
We are looking at spin qubits at silicon
level. We are also looking at superconducting hybrid
systems
at a broad level for various other competing
qubit paradigms.
Yeah. I see. And one of the,
sort of early applications,
I suppose, of quantum computers
is doing
simulations
of materials
because, of course, materials are quantum in nature.
And it it in some cases, it's easier
to do the simulation on a quantum computer,
if you had one, than it would be
on a classical computer. Is that something that
you're you're actively
looking at at the moment, actually using
nascent quantum computers to do some of your
computational work? Or is that is that something
from for the future,
with regards to your research?
Yes. So thank you for this question. So
there are many,
let's say there are many aspects to your
question. The first part was more to do
with simulating materials. Right? So that is often
called quantum simulations. That's a word for it.
So you can simulate a hypothetical
material.
For instance, there is there was there were
some materials that people
predicted in theory that really don't come as
a material.
For instance, there's something called the Kita f
chain, which is supposed to have what's called
a p wave superconductivity.
Doesn't exist in nature.
Right? There's another chain called some of these
materials they are they have something called SSI
chain. Many of these materials don't exist in
nature. But you can simulate them using quantum,
for instance, quantum
computer. Not just a quantum computer but you
can simulate them by aligning materials in a
row
trying to achieve that Hamiltonian. That is called
a quantum simulation.
However, if you're asking about how we use
the quantum computer to do some of our
device simulations, the answer is no yet.
We do not we do not yet simulate
these things. And there are quantum computers I
know. And probably you can fire simulations
using Qiskit and other softwares.
But those are more about trying out certain
quantum algorithms.
And some people can, you know, run a
search algorithm or
one of these famous six algorithms are there,
four or five algorithms.
You could try out those algorithms on quantum
computers. That's what at the back end. So
that's probably what I think
is there
out is out there.
I'm not sure if we have done anything
on those fronts because we directly simulate the
physics of the devices.
So for instance,
the main let's say I would call the
protagonist of all these stories is the electrons
for us. Electrons are the subatomic particles that
carry electric current. Right? The reason you have
electricity is electrons. The reason you have a
computer eventually is electrons.
And, so the quantum devices some of the
quantum devices that could form quantum computers
or what's called solid state quantum computers
would
depend on electrons. So we simulate and understand
electron
motion or electron transport across these devices.
And that's precisely
what we use mathematical models to simulate.
And that at that level, we probably don't
need a quantum computer
to understand or speed up our algorithms. We'd
rather use standard GPU type, you know, speed
ups, which are good enough. Yeah.
I see. Okay. And and this year, 2025,
is the international
year
of quantum.
And what we're doing here
at Physics World is we're asking as many
physicists as we can,
one question.
And that question is,
what does quantum physics mean to you?
Well,
I have been
studying quantum
in devices
since 02/2003.
So much before the quantum,
technology
impeded started.
So in that sense,
I am an electrical engineer to begin with.
And
when I started my PhD,
the the corridors of my depart of the
region I was working on was always resonating
with Hamiltonian,
Quantum.
And I got used to that. So Quantum
means everything to me. And I believe,
the
quantum revolution, if it happens, can be
disruptive.
And I'm really hoping that quantum technologies take
up.
I'm not sure if only computing is the
thing. Computing will definitely speed up certain algorithms,
no doubt.
But I think
surrounding quantum computing is a bunch of quantum
enhanced technologies,
sensing, as well as,
communications
and various other aspects of surrounding quantum.
I'm sure if all this come together, we
should have a great
by twenty forties and early twenty fifties, next
century. Sorry. The the second half of the
century can be, I mean, can be a
very disruptive,
technology for humankind.
So quantum is
means everything to me at least. Yeah.
Well, that's great. Thanks. Thanks so much for
coming on the podcast. Thank you.
It was my pleasure. Thank you.
That was Bhaskaran
Muralidharan
of the Indian Institute of Technology,
Bombay.
He's on the editorial board of the journal
Materials
for Quantum Technology.
It's published by IOP Publishing,
which also brings you Physics World.
Now
moving on to medical physics.
The second segment of this podcast episode
features an interview with the medical ultrasound
expert,
Daniel Sarno,
who is based at The UK's
National Physical Laboratory.
Here he is in conversation
with Physics World's Tammy Freeman.
They look at the role that ultrasound can
play in diagnosing
breast cancer.
Mammography is an effective tool for detecting breast
cancer, and it's widely used in screening programs.
But mammography
exposes patients to X-ray radiation, and it doesn't
work well in dense tissue, which can hide
the presence of a tumor.
Researchers at The UK's National Physical Laboratory
have developed an ultrasound based system that can
provide safe, low cost breast density assessment,
and NPL is now looking to spin out
a company, Sona, to bring this technology to
market.
I'm speaking today with Daniel Sarno,
Sona's cofounder and chief technology officer. Welcome to
the podcast, Daniel.
Hi. Thanks for having me.
So can we start by looking at what
are the limitations
of current mammography
based cancer screening?
Screening in general
as a, as a tool used by health
care systems
aims at detecting
early signs of cancer in mostly asymptomatic populations.
So breast cancer screening, for instance,
in The UK, at least is
offered for women aged 50 onwards every three
years.
And the
the reason why we do this is that
the breast cancer is the most common cause
of cancer,
in
women worldwide.
There's
over three point three million new cases each
year.
And in The UK, there are about fifty
seven thousand
new cases with increasing rates
mainly in younger women.
Now the reason why we do screening is
that we want to detect
breast cancer earlier.
If we detect breast cancer earlier, particularly at
stage
one, so when cancers are localized,
survival rates are near a hundred percent is
incredibly survivable cancer.
Issue is when cancers are dissected much later
in stages
four
in predominantly stage four where cancers have metastasized
and gone to multiple sites,
where survival rates then dropped sadly to as
low as twenty two percent,
in some countries.
So screening aims to find cancer
earlier when it's more treatable.
Treatable. And like I said, for most women,
it's offered
at either 40 or 50 depending on what
country you live in.
With the main tool that's used is, mammography.
So mammography is a X-ray based
imaging
system.
Most
notably,
requires compression of the brass, which is sort
of what most people think of when they
think of mammography.
The issue actually is that
different breasts have different
compositions.
Some women have
higher amount of fibro glandular tissue in the
breast. Some women have more fatty breast tissue.
But mammography
performance
really depends on breast composition.
Women with the highest density of breast, that's
to say, women with mostly
fibro glandular tissue,
the performance of mammography
diminishes
drastically.
For women with batty breast tissue,
mammography the sensitivity of mammography, which is sort
of the
the metric by which you can assess the
performance of this tool, is as high as
ninety percent. So
most of the cancers that are present in
women with the lowest density breast tissue are
picked up by mammography.
For women with, highest breast density categories,
the performance of mammography drops to as low
as 50%
sensitivity.
That's to say, if a cancer is present,
almost half of the time, it will be
missed.
But the
onset con consequence of that being that cancer
is picked up later
or in a kind of a subsequent screening
opportunity.
Now
this limitation of mammography has been known for
a long time,
but it mammography still remains the best tool
we have. It's the gold standard tool for
breast cancer screening.
But there are other tools out there, other
modalities for breast cancer screening.
Some of them being ultrasound based.
There is MRI, which is,
obviously, a very costly
but effective
tool.
There's other there's different types of mammography, such
as, tomosynthesis,
a a a version of mammography that's sort
of this pseudo three d imaging,
and contrast enhanced mammography. So there's a plethora
of tools beyond mammography
that can be,
used as screening for women with different breast
densities.
Okay. So,
Sona is developing the ultrasound based approach. So
what what are the advantage advantages of ultrasound
scans over X-ray imaging?
Yeah. So what we're doing at Sona is
we're actually
providing a tool or developing a tool
that can do breast density assessment. So this
is not breast cancer screening. So we're we're
not trying to do the job of mammography
in trying to detect
cancers at the earliest,
stages.
Instead, we're trying to measure
global,
metrics of breast composition
such that women can be provided with the
right forms of breast cancer screening at the
right time for them based off their breast
composition.
And some of the advantages of,
of ultrasound over X-ray imaging
is that, of course, the kind of natural
one that I think most people would think
of is the X-ray imaging is a ionizing
based imaging tool.
This limits its use both in kind of
setting that these,
mammogram scans can be provided,
but also the frequency with which
mammogram imaging can be provided.
But ultrasound,
in contrast, is a safe tool.
It's non ionizing.
It's, accessible
and portable.
It's actually it's the second most commonly used
imaging modality worldwide.
So it's very pervasive for that reason.
Okay. And can you explain how your system
actually uses the ultrasound to measure tissue density?
Tissue density, breast density in particular,
to repeat, is important for to understand for
two reasons.
Firstly,
breast high breast density
actually increases
cancer risk. Seventy percent of all cancers are
detected in women with dense breasts.
Now how pervasive
is is breast density?
Well, about
half of all women over the age of
40 have dense breasts. It it varies
from individual to individual and varies with age,
but about half of all women have
high breast density.
It increases cancer risk, so women with the
highest category of breast density
can be up to six times more likely
to develop breast cancer than women with the
lowest category of breast density.
But just to repeat, the the other impacts
of high breast density is this this effect
that it has in reducing the performance of
mammography. So high breast density can mask answers
on screening mammograms
and reduces performance.
Breastness is currently assessed
at screen at the screening opportunity using mammogram
images. So a mammogram image will be,
taken of an individual going through screening. That
mammogram image can be used
to find any cancers present in the breast
tissue.
But, also, the image can be looked at
globally by either a clinician or software interpretation
to see
by either
visually by eye or or by using algorithms
the ratio of fat to fibroblegial tissue and
give a metric for breast density.
That's
it has
proven
incredibly
useful.
In fact, the US FDA
recently changed their reporting guidelines for women across
The US to mandate breast density assessment,
across all states,
such that, you know, it it's it's considered
such a an important factor to measure that
The US actually have mandated this reporting.
So the issue with mammogram based breast density
assessment
is that it actually is not particularly consistent.
Studies have found that
breast density assessment done by clinicians
varies depending on which clinician you have. It
varies from screening opportunity to screening opportunity.
And also breast density assessment
with mammography is not accessible. So at the
moment, you only find out if you have
high breast density
at your first screening opportunity.
Now coming from the National Physical Laboratory, we
see that this is a a measurement challenge.
And being an ultrasound scientist
and believing that ultrasound is a particularly useful
technology to use,
we believe that we can do breast density
assessment
using ultrasound measurement.
Now how it works is we do something
known as, global acoustic attenuation measurements of the
breast.
That's to say, how much does the breast
tissue
diminish
their ultrasound signals as they pass through the
breast?
With women with higher breast density having
higher
acoustic attenuation,
properties of the breast tissue compared to women
with lower breast density.
So our system was
developed at the National Physical Laboratory over a
number of years. We've developed
a new form of ultrasound sensor to
measure this property
in a quantitative way.
And what that actually unlocks is the ability
to,
a, measure
breast density,
in a repeatable, consistent way.
But,
b, you're actually able to now monitor breast
density
over time
with,
so rather than just a a single measurement
of breast density,
you're now able to
do repeat measurements,
which have been found
to also relate to breast cancer risk. Women
who whose breast density does not drop as
fast as
you might expect in, across the population
have actually a higher rate of breast cancer
than women who've not.
Okay. So, you could use your system to
sort of track the differences in density over
time,
possibly
starting at a younger age for the screening,
and then you can
interpret those results. And then,
if it looks like someone's more at risk,
would they then be sent on for mammography
screening afterwards?
Exactly. Yeah. So we
we believe that
what's needed for breast cancer screening
is
early
breast cancer risk assessment.
At the moment, we can do breast cancer
risk assessment
using factors such as history
or even genetics.
But breast density, because at the moment, it's
done
with mammogram based,
imaging,
cannot be done at an earlier age.
So
with our technology,
you could bring breast density assessment
before
screening
such that you can then
plan an onward personalized screening program that's fit
for the individual rather than just using age
based,
screening profiles.
So, I mean, where would you see these
systems being deployed? Would this be something perhaps
that you're just local doctors that it would
be just sort of part of a a
routine test that women would undergo? Like, whilst
they're too young to actually go into the
screening program,
They they could have this,
measurement taken beforehand.
Yeah. So the the technology that we're developing
is
is incredibly accessible. Like I said, it uses
ultrasound, so it doesn't require a dedicated
facility.
It's
aimed to be a desktop sized device, so
small.
And
that opens up the possibility
of screening.
Of
sorry. Breast density assessment
being much more accessible
than it currently is.
So we aim to have these devices in
primary care clinics,
in,
breast cancer screening programs,
in
remote or low resource areas,
and also a part of work workplace
and community health initiatives.
Okay. So,
has the system been tested in patients yet?
It has. The the the the system and
technology actually has
quite a,
long lineage.
Originally,
as I described, we've developed new sensor technology,
a number of years ago, and we've gone
We've evolved from early proof of concept sensors
through to research platforms
and, initially,
measurement validation in in acoustic materials and breast
phantoms.
A couple years ago, we actually did our
first in person testing
to validate these measurements,
in a few people.
At the moment, we're being supported by the
government office for technology
transfer
and also by the UK Innovation and Science
Seed Fund.
And we're developing a proof of concept
prototype
that will initially
conduct preclinical
testing
and later further in person testing.
And the aim of this system really is
to go from what we've had before, which
is a series of research platforms,
something that's much closer to a clinical ready
device in a,
in a configuration where we could do accessible
breast density assessment using through transmission ultrasound.
Okay. And
so this this company, Sonar, is being set
up basically to bring this technology to the
market. I mean,
can you just sort of quickly update on
how that's progressing?
How long do you think it might take
until the these systems are actually ready for
clinical use?
Yeah. So we're we're we're
we're making some great progress. We understand that
it's very challenging
to bring medical technology
to the market, but we are up for
the challenge.
This sort of technology, we think, will be
able to be deployed in '27 2027
or 2028.
That's what we're we're aiming for,
with this year going through a series of
preclinical testing
and next year into clinical trials and clinical
studies where we will compare our ultrasound based
method for breast density assessment with,
traditional mammogram based methods for breast density assessment.
Now, yep, we know there's a lot of
work,
today to get this to the market,
but, but we're not alone. So we've actually,
this year, brought on a great team of
experienced entrepreneurs and world leaders in ultrasound innovation
and product development,
and importantly, breast radiologists as well.
Excellent. Right. Well, thanks very much. It sounds
like a really promising technology.
And thank you for speaking with us today.
That was Daniel Sarno of NPL
and Sona
in conversation
with Physics World's Tammy Freeman.
I'm afraid that's all the time we have
for this week's podcast.
Thanks to Bhaskaran,
Muralidharan,
Daniel Sarno,
and Tammy Freeman for joining me today.
And a special thanks to our producer, Fred
Isles.
We'll be back again next week. See you
then.