Naranamangalam R Jagannathan^1,2,3, R Ravikanth Reddy¹, Arun Kumar Shirshetty⁴, Samsudeen Marwan⁵, Deepak Masanam⁴, and Ananathakrishanan Sivaraman^5
1Dept. of Radiology, Chettinad Hospital & Research Institute, Kelambakkam, India, ²Dept. of Electrical Engineering, Indian Institute of Technology, Chennai, India, ³Radiology, Sri Ramachandra Inst. of Higher Education and Research, Chennai, India, ⁴Dept. of Urology, Chettinad Hospital & Research Institute, Kelambakkam, India, ⁵Chennai Urology and Robotics Institute Hospital, Chennai, India

The present study aims to evaluate a comprehensive metabolic profiling of patients with chronic prostatitis (PT) by investigating their urine samples and compare it with the prostate cancer (PCa) patients and healthy controls (HC) using ¹H nuclear magnetic resonance (NMR) metabolomics. The metabolic profile of chronic prostatitis patients falls between that seen for PCa and HC. This pilot study showed that NMR metabolomics may be useful to differentiate patients with PT from PCa and HC.

Felix N. Harder¹, Kilian Weiss², Thomas Amiel³, Johannes M. Peeters⁴, Robert Tauber³, Marcus R. Makowski¹, Andreas P. Sauter¹, Jürgen E. Gschwend³, Dimitrios C. Karampinos¹, and Rickmer F. Braren^1
1Institute of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany, ²Philips GmbH Market DACH, Hamburg, Germany, ³Department of Urology, Technical University of Munich, School of Medicine, Munich, Germany, ⁴Philips Healthcare, Best, Netherlands

Since prostate MRI is increasingly applied and yet limited by long acquisition times, we prospectively investigated the performance of a novel reconstruction algorithm, combining compressed sensing, parallel imaging and deep learning (C-SENSE AI) in patients with histologically proven prostate cancer. Highly accelerated T2w and DWI sequences were compared to clinical standard of reference T2w and DWI. C-SENSE AI enabled 58% acceleration in T2w imaging and 47% acceleration in DWI of the prostate while obtaining significantly better image quality and tumor detection. C-SENSE AI seems particularly interesting in view of the need for accelerated prostate MRI with preserved high image quality.  

Malwina Molendowska¹, Marco Palombo¹, Fabrizio Fasano^2,3, Derek K. Jones¹, Daniel C. Alexander⁴, Eleftheria Panagiotaki⁴, and Chantal Tax^1,5
1Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, ²Siemens Healthcare Ltd, Camberly, United Kingdom, Camberly, United Kingdom, ³Siemens Healthcare GmbH, Erlangen, Germany, Erlangen, Germany, ⁴Centre for Medical Image Computing, University College London, London, United Kingdom, ⁵Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

This work showcases the first ever use of ultra-strong gradient in ’below the neck’ human MRI. It assesses the benefits, compared to more commonly-available gradient strengths, of 300mT/m gradients for comprehensive characterization of the prostate gland. Leveraging such gradient amplitudes enables unique tissue contrasts, with a potential to improve specificity and/or sensitivity of current MRI methods for prostate cancer characterisation and detection.

Jeremiah Sanders¹, Li Wang², Falk Poenisch³, Narayan Sahoo³, Xiaorong Zhu³, Jingfei Ma¹, Seungtaek Choi⁴, Quynh Nguyen⁴, Henry Mok⁴, Chad Tang⁴, Katina Crabtree⁴, Sean McGuire⁴, Karen Hoffman⁴, Shalin Shah⁴, and Steven Frank^4
1Imaging Physics, UT MD Anderson Cancer Center, Houston, TX, United States, ²Experimental Radiation Oncology, UT MD Anderson Cancer Center, Houston, TX, United States, ³Radiation Physics, UT MD Anderson Cancer Center, Houston, TX, United States, ⁴Radiation Oncology, UT MD Anderson Cancer Center, Houston, TX, United States

Carbon and gold fiducial markers (FMs) are the most commonly used FMs for prostate radiotherapy. However, these markers do not produce positive contrast on MRI, and can cause large magnetic susceptibility artifacts on MRI. These properties of carbon and gold FMs make their identification on MRI challenging and complicate treatment planning processes that use co-image registration of MRI with CT for radiotherapy treatments. A novel multimodality FM has been developed that produces positive contrast on four imaging modalities, including MRI. This work presents the first-in-patient experience using the multimodality FM for proton therapy of prostate cancer.