Or Perlman

• PhD
• Senior Lecturer (Assistant Professor) at Tel Aviv University

Biophysical model fitting plays a key role in obtaining quantitative parameters from physiological signals and images. However, the model complexity for molecular magnetic resonance imaging (MRI) often translates into excessive computation time, which makes clinical use impractical. Here, we present a generic computational approach for solving the...

Purpose: To develop a method for optimizing pulsed saturation transfer MR fingerprinting (ST MRF) acquisition. Methods: The Cram\'er-Rao bound (CRB) for variance assessment was employed on Bloch-McConnell-based simulated signals, followed by a numerical sequential quadratic programming optimization and basin-hopping avoidance of local minima. Valid...

Biophysical model fitting plays a key role in obtaining quantitative parameters from physiological signals and images. However, the model complexity for molecular magnetic resonance imaging (MRI) often translates into excessive computation time, which makes clinical use impractical. Here, we present a generic computational approach for solving the...

Noninvasive magnetic resonance imaging (MRI) of the relayed nuclear Overhauser effect (rNOE) constitutes a promising approach for gaining biological insights into various pathologies, including brain cancer, kidney injury, ischemic stroke, and liver disease. However, rNOE imaging is time-consuming and prone to biases stemming from the water T1 and...

Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accele...

Magnetic resonance imaging (MRI) relies on radiofrequency (RF) excitation of proton spin. Clinical diagnosis requires a comprehensive collation of biophysical data via multiple MRI contrasts, acquired using a series of RF sequences that lead to lengthy examinations. Here, we developed a vision transformer-based framework that captures the spatiotem...

Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides a comprehensive overview of recent advances in DL for MRI reconstruction, and focuses on various DL approaches and architectures designed to improve image quality, accele...

Noninvasive magnetic resonance imaging (MRI) of the relayed nuclear Overhauser effect (rNOE) constitutes a promising approach for gaining biological insights into various pathologies, including brain cancer, kidney injury, ischemic stroke, and liver disease. However, rNOE imaging is time-consuming and prone to biases stemming from the water T 1 and...

Background Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of...

Deep learning-based saturation-transfer magnetic resonance fingerprinting (MRF) is an emerging approach for noninvasive in vivo imaging of proteins, metabolites, and pH. It involves a series of steps, including (i) sample/subject preparation, (ii) image acquisition schedule design, (iii) biophysical model formulation, (iv) artificial intelligence (...

Progressive gait impairment is common in aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerom...

The utility of chemical exchange saturation transfer (CEST) MRI for monitoring the uptake of glucosamine (GlcN), a safe dietary supplement, has been previously demonstrated in detecting breast cancer in both murine and human subjects. Here, we studied and characterized the detectability of GlcN uptake and metabolism in the brain. Following intraven...

Model-driven analysis of biophysical phenomena is gaining increased attention and utility for medical imaging applications. In magnetic resonance imaging (MRI), the availability of well-established models for describing the relations between the nuclear magnetization, tissue properties, and the externally applied magnetic fields has enabled the pre...

The utility of chemical exchange saturation transfer (CEST) MRI for monitoring the uptake of glucosamine (GlcN), a safe dietary supplement, has been previously demonstrated in detecting breast cancer in both murine and human subjects. Here, we studied and characterized the detectability of GlcN uptake and metabolism in the brain. Following intraven...

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiencey. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Non...

BACKGROUND Wrist worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatio-temporal gait parameters within continuous long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the c...

Model-driven analysis of biophysical phenomena is gaining increased attention and utility for medical imaging applications. In magnetic resonance imaging (MRI), the availability of well-established models for describing the relations between the nuclear magnetization, tissue properties, and the externally applied magnetic fields has enabled the pre...

Over the last decade, artificial intelligence (AI) has made an enormous impact on a wide range of fields, including science, engineering, informatics, finance, and transportation [...]

Here we develop a mechanism of protein optimization using a computational approach known as "genetic programming". We developed an algorithm called Protein Optimization Engineering Tool (POET). Starting from a small library of literature values, the use of this tool allowed us to develop proteins that produce four times more MRI contrast than what...

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noni...

Purpose To substantially shorten the acquisition time required for quantitative three‐dimensional (3D) chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) imaging and allow for rapid chemical exchange parameter map reconstruction. Methods Three‐dimensional CEST and MT magnetic resonance fingerprinting (MRF) datas...

Purpose To develop a clinical CEST MR fingerprinting (CEST‐MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. Methods A CEST‐MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF...

Purpose: To substantially shorten the acquisition time required for quantitative 3D chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) imaging and allow for rapid chemical exchange parameter map reconstruction. Methods: Three-dimensional CEST and MT magnetic resonance fingerprinting (MRF) datasets of L-arginine p...

Proteins are used by scientists to serve a variety of purposes in clinical practice and laboratory research. To optimize proteins for greater function, a variety of techniques have been developed. For the development of reporter genes used in Magnetic Resonance Imaging (MRI) based on Chemical Exchange Saturation Transfer (CEST), these techniques ha...

Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast‐weighted image...

Purpose To develop an automated machine‐learning‐based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols. Methods An MR physics‐governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative recons...

Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with glioblastoma multiforme, the early apoptotic responses to oncolytic virotherapy (characterized by decreas...

Purpose: To develop a clinical chemical exchange saturation transfer magnetic resonance fingerprinting (CEST-MRF) pulse sequence and reconstruction method. Methods: The CEST-MRF pulse sequence was modified to conform to hardware limits on clinical scanners while keeping scan time $\leqslant$ 2 minutes. The measured data was reconstructed using a de...

Purpose: To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols. Methods: An MR physics governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative recon...

Purpose As the field of CEST grows, various novel preparation periods using different parameters are being introduced. At the same time, large, multisite clinical studies require clearly defined protocols, especially across different vendors. Here, we propose a CEST definition standard using the open Pulseq format for a shareable, simple, and exact...

Copper nanostructures offer remarkable therapeutic potential. In particular, copper oxide nanoparticles (CuO NPs) are increasingly studied for diagnostic and therapeutic purposes. Their anticancer potential, as well as contrast-enhancing capabilities for magnetic resonance imaging (MRI) and ultrasound (US), were previously demonstrated. To further...

Reporter gene imaging allows for non-invasive monitoring of molecular processes in living cells, providing insights on the mechanisms underlying pathology and therapy. A lysine-rich protein (LRP) chemical exchange saturation transfer (CEST) MRI reporter gene has previously been developed and used to image tumor cells, cardiac viral gene transfer, a...

Reporter gene imaging allows for non-invasive monitoring of molecular processes in living cells, providing insights on the mechanisms underlying pathology and therapy. A lysine-rich protein (LRP) chemical exchange saturation transfer (CEST) MRI reporter gene has previously been developed and used to image tumor cells, cardiac viral gene transfer, a...

Oncolytic virotherapy is a promising treatment for high mortality cancers. Non-invasive imaging of the underlying molecular processes is an essential tool for therapy optimization and assessment of viral spread, innate immunity, and therapeutic response. However, previous methods for imaging oncolytic viruses did not correlate with late viral activ...

Bimetallic nanostructures can be attractive contrast-enhancing materials for dual-modal imaging, allowing improved diagnosis ability using two different physical phenomena, following administration of a single nano-agent. In this research, the potential of the biocompatible polydopamine (PDA) was explored as a binding matrix to produce a CuO NPs em...

Cancer stem cells, also termed tumor initiating cells (TICs), are a rare population of cells within the tumor mass which initiate tumor growth and metastasis. In pancreatic cancer, TICs significantly contribute to tumor re-growth after therapy, due to their intrinsic resistance. Here we demonstrate that copper oxide nanoparticles (CuO-NPs) are cyto...

Purpose To understand the influence of various acquisition parameters on the ability of CEST MR‐Fingerprinting (MRF) to discriminate different chemical exchange parameters and to provide tools for optimal acquisition schedule design and parameter map reconstruction. Methods Numerical simulations were conducted using a parallel computing implementa...

Purpose: To understand the influence of various acquisition parameters on the ability of CEST MR-Fingerprinting (MRF) to discriminate different chemical exchange parameters and to provide tools for optimal acquisition schedule design and parameter map reconstruction. Methods: Numerical simulations were conducted using a parallel-computing implement...

Copper oxide nanoparticles (CuO-NPs) are increasingly investigated for diagnostic and therapeutic purposes. Recent work have demonstrated their anticancer potential as well as contrast agent capabilities for magnetic resonance imaging (MRI) and through-transmission ultrasound. However, no capabilities of CuO-NPS were demonstrated using conventional...

Magnetic resonance imaging (MRI) and ultrasound (US) are two prominent medical imaging modalities. They are extensively and routinely used in various medical fields, such as cardiology, embryology, neurology, and oncology. In this chapter we describe the application of nanoparticles for MRI and US image enhancement. Moreover, the utilization of nan...

Purpose: The aim of this study was to examine the feasibility of using nanoparticle-enhanced transmission ultrasound (NETUS) as an image-based monitoring modality for microwave hyperthermia treatment. Methods: A dedicated transmission ultrasound imaging system was used to obtain acoustic projections and ultrasound computed tomography images. Initia...

Iron oxide nanoparticles (IONPs) are becoming increasingly used and intensively investigated in the field of medical imaging. They are currently FDA approved for magnetic resonance imaging (MRI), and it would be highly desirable to visualize them by ultrasound as well. Previous reports using the conventional ultrasound B-scan (pulse-echo) imaging t...

Specific supraventricular tachycardia (SVT) classification using surface ECG is considered a challenging task, since the atrial electrical activity (AEA) waves, which are a crucial element for obtaining diagnosis, are frequently hidden. In this paper we present a fully automated SVT classification method that embeds our recently developed hidden AE...

Multimodal medical imaging is gaining increased popularity in the clinic. This stems from the fact that data acquired from different physical phenomena may provide complementary information resulting in a more comprehensive picture of the pathological state. In this context, nano-sized contrast agents may augment the potential sensitivity of each i...

ECG analysis is the method for cardiac arrhythmia diagnosis. During the diagnostic process many features should be taken into consideration, such as regularity and atrial activity. Since in some arrhythmias, the atrial electrical activity (AEA) waves are hidden in other waves, and a precise classification from surface ECG is inapplicable, a confirm...

The fetal ECG can serve as a tool for fetal distress detection. However, the abdominal ECG of a pregnant woman contains mainly the maternal ECG and a relatively small amplitude fetal ECG signal, contaminated by various noises. As part of the 2013 PhysioNet/CinC Challenge, this study aimed to develop an algorithm for noninvasive fetal QRS detection.

Analysis of the ECG signal is the prevalent method for diagnosing cardiac arrhythmia. In order to achieve a precise diagnosis, the physician must carefully examine the quantity, location, and relations between the ECG signal elements, with emphasis given to the atrial electrical activity (AEA) wave characteristics. Nevertheless, in some cases the A...

A significant key for the success of arrhythmia diagnosis using ECG is detecting the atrial electrical activity (AEA). Despite extensive research, there is a diagnostic problem in detecting AEA in some arrhythmias, especially when the AEA-wave is hidden in other waves. Our proposed method utilizes the well-known linear combiner usually used for noi...