Lecture

Role of medical physics in the era of precision medicine; Prof. Robert Jeraj, PhD

We invite you to the 18th Institute colloquium in the academic year 2017/18. The colloquium will be held on Wednesday June 27, 2018 at 1 PM in the main Institute lecture hall, Jamova 39, Ljubljana. To read the abstract click  http://www.ijs.si/ijsw/Koledar_prireditev. Past colloquia are posted on  http://videolectures.net/kolokviji_ijs.

profil_robert

prof. dr. Robert Jeraj

University of Wisconsin, Madison, USA
University of Ljubljana, Ljubljana

 

Role of medical physics in the era of precision medicine

Medical physics is intimately connected with medicine, and is progressing along a similar path. General trend of medicine, particularly oncology, towards personalized treatment by in-depth profiling of the disease, gave rise to so-called “precision medicine”. However, there are severe obstacles to overcome. For example, cancers evolve in time to become harder targets to treat. Understanding treatment resistance, and its development, often connected with the highly heterogeneous nature of the disease, is another key obstacle. Use of multi-modality imaging techniques such as molecular imaging is one of the solutions that medical physics can offer. Examples from clinical trials utilizing advanced molecular imaging, highlighting intra-tumor and inter-tumor heterogeneity will be presented. New understanding of cancer treatment response dynamics will be outlined. Potential for improved patient treatment designs steaming from these novel insights will be discussed. Role of (medical) physics to contribute to advancement of treatment will be highlighted.

Cordially invited!

Lecture upon election to the title of “research fellow”

On Monday, March 5 2018, Urban Simončič will give a lecture upon election to the title of “research fellow” titled Quantification of PET images with kinetic analysis – theory and applications. The lecture starts at 11:00 in the upper lecture room of Reactor Centre Podgorica. Cordially invited!
Urban_Simoncic
Abstract:
Positron emission tomography (PET) is a molecular imaging technique that plays an important role in modern medicine; especially in oncology, neurology and cardiology. Quantitative measures can be derived from PET images by normalizing uptake or kinetic analysis. The advantage of quantification with kinetic analysis compared to normalization of the uptake is in more abundant and more specific results. This seminar will present PET imaging technique, theoretical basis for kinetic analysis, practical implementation and some applications in oncology.

Monday physics colloquium

On Monday, January 8, Matija Milanič will give a lecture titled Hyperspectral imaging and medicine. The lecture will be in the context of promotion to Assistant Professor. You are cordially invited to attend at 16:15 to Faculty of Mathematics and Physics, Jadranska 19, lecture room F1. (There will also be tea before the lecture, so come a few minutes early 🙂 )

Matija Milanič

Abstract:
Hyperspectral imaging (HSI) is a non-contact and non-invasive optical technique which provides both spectral and spatial information in one measurement. The goal of HSI is to find objects, identify materials, or detect processes. As such it became a promising imaging modality for medical applications, especially in disease diagnosis and image-guided surgery.
An overview of the technique will be given, including a review of possible medical applications with focus on evaluation of bruises and detection of small-joint arthritis.

Lecture by Ivan Štajduhar

IS_RI

On Wednesday, May 10th, 2017 at 16:00, assoc. prof. Ivan Štajduhar (Department of Computer Engineering, University of Rijeka – Faculty of Engineering) will give a lecture titled Artificial Intelligence in Medicine. The lecture will be held in lecture hall F2 (first floor) in the physics department building, Jadranska 19, Ljubljana.

Artificial Intelligence in Medicine
Would it be possible to supersede physicians with computers, to some extent, at least? The idea of computer-aided diagnosis in diagnosing and treating illnesses has been around from nineteen-eighties. It was then that scientists discovered that, by applying statistical algorithms on real-world patient data, using so-called machine learning, one can establish useful (almost-)out-of-the-box mathematical models that perform well at describing some problems. In the last decade, significant increases occurred worldwide in the level of informatics-readiness of clinical centres, in the availability of standardised technology for data exchange and storage, and in the abundance of quality medical radiology techniques. This, in turn, resulted in an explosion in the availability of voluminous data, enabling further advances in the field of computer-aided diagnosis and treatment. In this lecture, in addition to some fundamentals related to the field, several topics concerning medical image analysis will be discussed: learning predictive models for diagnosing knee injury, data preprocessing for reducing model complexity and transfer learning in medical radiology domain (“RadiologyNet”, a research project conducted in collaboration with the Clinical Hospital Centre Rijeka, Croatia).

Lecture by prof. Robert Jeraj

On Friday, 31st March 2017, professor Robert Jeraj will present a physics colloquium titled Implications of Tumor Heterogeneity for Precision Medicine. The lecture will start at 12:15 PM at Faculty of Mathematics and Physics, Jadranska 19, lecture hall F1. Tea (and possibly biscuits) will be served before lecture. Hope to see you there!

nniicfmonlhhobnh

Medical physics is intimately connected with medicine, and is progressing along a similar path. General trend of medicine, particularly oncology, towards personalized treatment gave rise to precision medicine, which addresses the highly complex nature of disease. However, there are severe obstacles to overcome. For example, cancers evolve in time to become harder targets to treat. Understanding treatment resistance, and its development, often connected with the highly heterogeneous nature of the disease, is another key obstacle. Use of multi-modality imaging techniques such as molecular imaging is one of the solutions that medical physics can offer. Examples from clinical trials utilizing advanced molecular imaging, highlighting intra-tumor and inter-tumor heterogeneity will be presented. New understanding of cancer treatment response dynamics will be outlined. Potential for improved patient treatment designs steaming from these novel insights will be discussed.

Popular science lectures about mathematics and medical physics

Faculty of mathematics and physics invites to popular science lectures about mathematics and medical physics.

The mathematics lecture will be the third in the series of popular science mathematics lectures “I <3 MAT". Prof. dr. Boris Lavrič will dedicate the lecture to the beauty and exactness of geometry. At the physics lecture, prof. dr. Robert Jeraj will explain why Physics + Medicine = Medical Physics. The lectures will be on Thursday, March 30 at 6 PM and 7 PM, Jadranska 21, lecture room 2.05.

jeegofldmkhpehnn

Monday physics colloquium

On Monday, November 14, Andrej Studen will give a lecture entitled PET imaging with silicon sensors. The lecture will be in the context of promotion to Assistant Professor. You are cordially invited at 16:15 to Faculty of Mathematics and Physics, Jadranska 19, lecture room F1.

Andrej Studen

 

 

 

 

ABSTRACT: Silicon seems an unlikely candidate for imaging in positron emission tomography. However, the ability to provide spatially accurate interaction positions of energetic photons can be exploited to yield significantly improved images. In the presentation, physics of PET imaging will be introduced, focusing on interplay of sensor spatial resolution and final image quality, concluded by potential application of silicon based PET imaging probes.

Lecture: dr. ORLY ALTER (University of Utah, USA)

On Wednesday, June 29th, 2016 at 13:00, dr. ORLY ALTER (Scientific Computing and Imaging Institute and the Huntsman Cancer Institute, University of Utah) will give a lecture entitled Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics. The lecture will be held in the main lecture hall of the Jožef Stefan Institute (JSI), Jamova 39, Ljubljana.

OA_2013_1

Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics

We are developing new mathematical frameworks to do what no others currently can, that is, create a single coherent model from multiple high-dimensional datasets, known as tensors. The frameworks – comparative spectral decompositions – generalize those that underlie the theoretical description of the physical world. We are using the frameworks to compare and contrast datasets recording different aspects of a single disease, such as genomic profiles of multiple cell types from the same set of patients, measured more than once by several different methods. By using the complex structure of the datasets, rather than simplifying them as is commonly done, the frameworks enable the separation of patterns of DNA alterations – which occur only in the tumor genomes – from those that occur in the genomes of normal cells in the body, and from variations caused by experimental inconsistencies. The patterns that we uncover in the data are expected to offer answers to the open question of the relation between a tumor’s genome and a patient’s outcome. For example, recent comparisons of the genomes of tumor and normal cells from the same sets of ovarian and, separately, glioblastoma brain cancer patients uncovered patterns of DNA copy-number alterations that were found to be correlated with a patient’s survival and response to chemotherapy. For three decades prior, the best predictor of ovarian cancer survival was the tumor’s stage; more than a quarter of ovarian tumors are resistant to the platinum-based chemotherapy, the first-line treatment, yet no diagnostic existed to distinguish resistant from sensitive tumors before the treatment. For five decades prior, the best prognostic indicator of glioblastoma was the patient’s age at diagnosis. The ovarian and brain cancer data were published, but the patterns remained unknown until the team applied their comparative spectral decompositions. Pending experimental revalidation, we will bring the patterns that we uncover to the clinic, to be used in personalized diagnostic and prognostic pathology laboratory tests. The tests would predict a patient’s survival and response to therapy, and doctors could tailor treatment accordingly.

Dr. Orly Alter:

Dr. Alter is a USTAR associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah. Inventor of the “eigengene,” she pioneered the matrix and tensor modeling of large-scale molecular biological data, which, as she demonstrated, can be used to correctly predict previously unknown cellular mechanisms. Dr. Alter received her Ph.D. in applied physics at Stanford University, and her B.Sc. magna cum laude in physics at Tel Aviv University. Her Ph.D. thesis on “Quantum Measurement of a Single System,” which was published by Wiley-Interscience as a book, is recognized today as crucial to the field of gravitational wave detection.