Tyler O'Neal, Staff Editor GOVERNMENT

Case Western Reserve researchers use AI with CT scans to predict how well lung cancer patients will respond to expensive treatments

Scientists from the Case Western Reserve University digital imaging lab, already pioneering the use of Artificial Intelligence (AI) to predict whether chemotherapy will be successful, can now determine which lung-cancer patients will benefit from expensive immunotherapy.

And, once again, they're doing it by teaching a computer to find previously unseen changes in patterns in CT scans taken when the lung cancer is first diagnosed compared to scans taken after the first 2-3 cycles of immunotherapy treatment. And, as with previous work, those changes have been discovered both insides--and outside--the tumor, a signature of the lab's recent research.

"This is no flash in the pan--this research really seems to be reflecting something about the very biology of the disease, about which is the more aggressive phenotype, and that's information oncologists do not currently have," said Anant Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) has become a global leader in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI. An illustration of the differences in CT radiomic patterns before and after initiation of checkpoint inhibitor therapy. Also, density of tumor infiltrating lymphocytes, on diagnostic biopsies, was found to be higher in responders as compared to non-responders.{module INSIDE STORY}

Currently, only about 20% of all cancer patients will benefit from immunotherapy, a treatment that differs from chemotherapy in that it uses drugs to help your immune system fight cancer, while chemotherapy uses drugs to directly kill cancer cells, according to the National Cancer Institute.

Madabhushi said the recent work by his lab would help oncologists know which patients would benefit from the therapy, and who would not.

"Even though immunotherapy has changed the entire ecosystem of cancer, it also remains extremely expensive--about $200,000 per patient, per year," Madabhushi said. "That's part of the financial toxicity that comes along with cancer and results in about 42% of all newly diagnosed cancer patients losing their life savings within a year of diagnosis."

Having a tool based on the research being done now by his lab would go a long way toward "doing a better job of matching up which patients will respond to immunotherapy instead of throwing $800,000 down the drain," he added, referencing the four patients out of five who will not benefit, multiplied by annual estimated cost.

New research published

The new research, led by co-authors Mohammadhadi Khorrami and Prateek Prasanna, along with Madabhushi and 10 other collaborators from six different institutions was published this month in the journal Cancer Immunology Research.

Khorrami, a graduate student working at the CCIPD, said one of the more significant advances in the research was the ability of the computer program to note the changes in texture, volume, and shape of a given lesion, not just its size.

"This is important because when a doctor decides based on CT images alone whether a patient has responded to therapy, it is often based on the size of the lesion," Khorrami said. "We have found that textural change is a better predictor of whether the therapy is working.

"Sometimes, for example, the nodule may appear larger after therapy because of another reason, say a broken vessel inside the tumor--but the therapy is working. Now, we have a way of knowing that."

Prasanna, a postdoctoral research associate in Madabhushi's lab, said the study also showed that the results were consistent across scans of patients treated at two different sites and with three different types of immunotherapy agents.

"This is a demonstration of the fundamental value of the program, that our machine-learning model could predict response in patients treated with different immune checkpoint inhibitors," he said. "We are dealing with a fundamental biological principle."

Prasanna said the initial study used CT scans from 50 patients to train the computer and create a mathematical algorithm to identify the changes in the lesion. He said the next step will be to test the program on cases obtained from other sites and across different immunotherapy agents. This research recently won an ASCO 2019 Conquer Cancer Foundation Merit Award.

Additionally, Madabhushi said, researchers were able to show that the patterns on the CT scans which were most associated with a positive response to treatment and with overall patient survival were also later found to be closely associated with the arrangement of immune cells on the original diagnostic biopsies of those patients.

This suggests that those CT scans appear to capture the immune response elicited by the tumors against the invasion of cancer--and that the ones with the strongest immune response were showing the most significant textural change and most importantly, would best respond to the immunotherapy, he said.

Madabhushi established the CCIPD at Case Western Reserve in 2012. The lab now includes nearly 60 researchers.

Some of the lab's most recent work, in collaboration with New York University and Yale University, has used AI to predict which lung cancer patients would benefit from adjuvant chemotherapy based on tissue-slide images. That advancement was named by Prevention Magazine as one of the top 10 medical breakthroughs of 2018.

Russian researchers produce new supercomputer model to understand solar dynamics

Tyler O'Neal, Staff Editor GOVERNMENT

An international group of scientists, in cooperation with a research scientist from Skoltech, has developed a model to describe changes in the solar plasma. This will help comprehend solar dynamics and gives some clues to understanding how to predict space weather events. The results have been published in the Astrophysical Journal.

Plasma β is an important quantity to investigate the interchanging roles of plasma and magnetic pressure in the solar atmosphere. It relates to both the solar magnetic field and driving solar phenomena such as solar wind, coronal mass ejections, and flares; these phenomena affect the Space Weather directly.

Dr. Jenny Rodriguez, a scientist from the Space Center of Skolkovo Institute of Science and Technology (Russia), her colleagues from Leibniz Institut für Sonnenphysik (Germany) and Instituto Nacional de Pesquisas Espaciais (Brazil) have developed a model to estimate how plasma β changes in the solar atmosphere. Specifically, they obtain a description of the plasma β in the solar corona during previous solar cycles (~22 years). They found the strongest influence during both solar cycles from faculae and the quiet Sun regions. 

This is an image in the solar corona at 171 A.{module INSIDE STORY}

The faculae and QS regions drive variations in magnetic and kinetic pressure at coronal heights. It can directly affect space weather and the ability to predict it. These results give an interesting outlook on solar cycle dynamics.

"Plasma β is a very important quantity in the solar atmosphere. The solar atmosphere is a plasma physics laboratory near us; it allows us to know about its dynamics and to understand how many events are happening on the Sun. We believe that our findings will help comprehend the Sun's dynamics and help to forecast the Space Weather," said Dr. Jenny Rodriguez.

Warwick physicists develop sophisticated supercomputing for DUNE project

Tyler O'Neal, Staff Editor GOVERNMENT

The University of Warwick has received over £900,000 to provide essential contributions to the international DUNE experiment, which aims to answer fundamental questions about our universe.

This is part of the latest UK multi-million pound investment in the DUNE global science project that brings together the scientific communities of the UK and 31 countries from Asia, Europe, and the Americas to build the world’s most advanced neutrino observatory. The DUNE project has the potential to lead to profound changes in our understanding of the universe.

DUNE (the Deep Underground Neutrino Experiment) is a flagship international experiment hosted by Fermilab, which will be designed and operated by a collaboration of over 1,000 physicists across 32 countries. dune 2 {module INSIDE STORY}

The investment from UK Research and Innovations’Science and Technology Facilities Council (STFC) is a four-year construction grant to 13 educational institutions and to STFC’s Rutherford Appleton and Daresbury Laboratories. This grant, of £30M, is the first of two stages to support the DUNE construction project in the UK which will run until 2026 and represents a total investment of £45M.

Various elements of the experiment are under construction across the world, with the UK taking a major role in contributing essential expertise and components to the experiment and facility. UK scientists and engineers will design and produce the principle detector components at the core of the DUNE detector, which will comprise four large tanks each containing 17,000 kg of liquid argon. The UK groups are also developing a state-of-the-art, high-speed data acquisition system to record the signals from the detector, together with the sophisticated software needed to interpret the data and provide the answers to the scientific questions.

A team in Warwick, led by Dr. John Marshall, is leading the development of software algorithms capable of automatically reconstructing neutrino interactions in the DUNE detectors. The first phase of funding announced today awards the Warwick group £961,000 for this development work to continue into the construction phase of the project so that when the detector takes first data, from 2026, scientists will be in an optimal position to extract the physics. dune cartoon d6620{module INSIDE STORY}

Head of the University of Warwick experimental particle physics group, Professor Gary Barker, who is also the PI of the DUNE project in the UK, said: “Software developed by the Warwick group applies forefront computational techniques that turn the raw signals from DUNE into physics measurements. This new grant recognizes the world-leading expertise of Warwick in this area and will allow us to continue our leadership role inside the collaboration.”

The DUNE project aims to advance our understanding of the origin and structure of the universe. It will study the behavior of particles called neutrinos and their antimatter counterparts, antineutrinos. This could provide insight as to why we live in a matter-dominated universe while anti-matter has largely disappeared.

DUNE will also watch for supernova neutrinos produced when a star explodes, which will allow the scientists to observe the formation of neutron stars and black holes and will investigate whether protons live forever or eventually decay, bringing us closer to fulfilling Einstein’s dream of a grand unified theory.

Professor Stefan Soldner-Rembold, head of the Particle Physics Group at the University of Manchester as well as DUNE Co-Spokesperson, commented: “DUNE will help to answer fundamental questions that overlap particle physics, astrophysics, and cosmology.”

The UK universities involved in the project are Birmingham, Bristol, Cambridge, Edinburgh, Imperial College London, Lancaster, Liverpool, Manchester, Oxford, Sheffield, Sussex, UCL and Warwick.