Magdalena Sokolska¹, Meetakshi Gupta², Björn Eiben³, Julia Markus⁴, Harpreet Hyare⁴, and Michael Kosmin^2
1Medical Physics and Biomedical Engineering, University College London Hospitals, London, United Kingdom, ²Radiotheraphy, University College London Hospitals, London, United Kingdom, ³Department of Medical Physics and Biomedical Engineerin, University College London, London, United Kingdom, ⁴Imaging, University College London Hospitals, London, United Kingdom

This work proposes a framework for monitoring brain perfusion after radiotherapy treatment of glioma in relation to the radiotherapy dose. 

Chunmiao Hu¹, Zhijian Hu², Li Chen³, DeChun Zheng⁴, Yunbin Chen⁴, Xisheng Cao⁴, and Tao Lu^4
1Radiology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China, ²School of Public Health, School of Public Health, Fujian Medical University, Fuzhou Fujian 350122, China, Fuzhou Fujian, China, ³School of Arts and Sciences, School of Arts and Sciences, Fujian Medical University, Fuzhou Fujian 350122, China, Fuzhou Fujian, China, ⁴Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China

This study is the first to adopt post-NACT MR radiomics to predict the recurrence of locally advanced NPC (stages III and IVa). 

Sai Man Cheung¹, Kwok-Shing Chan^1,2, Nicholas Senn¹, Ehab Husain³, Yazan Masannat⁴, Steven D Heys¹, and Jiabao He^1
1Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom, ²Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, ³Pathology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, ⁴Breast Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom

The spatial distribution of lipid composition in breast has a major role in breast cancer prevention, with deregulation of lipid metabolism identified in BRCA1/2 genetic mutation carriers. Neoplastic tubule formation, a key component of grading score, is directly associated with cellularity, with significant implications on prognosis. Lipid composition measurement through biochemical extraction is invasive, while conventional spectroscopic imaging demands long acquisition time. Novel chemical shift-encoded imaging (CSEI) allows lipid composition mapping of the whole breast in a clinically acceptable timeframe. We set out to examine the relationship between peri-tumoural lipid composition and tubule formation using CSEI in breast tumours.

Rachelle Crescenzi^1,2,3, Paula Donahue⁴, Maria Garza⁵, Chelsea A Lee⁶, Niral J Patel⁶, Victoria Gonzalez⁷, Sky Jones⁵, and Manus J Donahue^5,8
1Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ²Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, ³Department of Biomedical Engineering, Vanderbilt University Medical Center, Nashville, TN, United States, ⁴Department of Physical Medicine and Rehabilitation, Vanderbilt University Medical Center, Nashville, TN, United States, ⁵Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States, ⁶Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States, ⁷School of Medicine, The City College of New York, New York, NY, United States, ⁸Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States

The overall goal of this work is to apply Dixon fat-water MRI to test fundamental hypotheses regarding the role of elevated adiposity in breast cancer treatment-related lymphedema (BCRL) condition severity. BCRL is a common co-morbidity of breast cancer therapies, yet factors that contribute to BCRL progression remain incompletely characterized. We observed that adiposity quantified by MRI is elevated in the affected upper extremity and torso of women with BCRL and increases with condition severity. As such, Dixon MRI may provide a surrogate marker of BCRL onset and may help to inform the varied course of lymphedema progression. 

Haimei Chen¹, Jie Zhu¹, Mengsi Li¹, Li Lin¹, Ziying Yin², Jun Chen², Meng Yin², Richard L. Ehman², and Jin Wang^1
1Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong 510630, People’s Republic of China, Guangzhou, China, ²Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester. MN. USA, Rochester, MN, United States

Hepatitis B virus (HBV)-related decompensated cirrhosis is well-known risk factor for developing hepatocellular carcinoma (HCC). Therefore, it is critical to assess the risk of developing HCC in these patients. Magnetic resonance elastography (MRE) has promise in predicting future events in many chronic liver diseases, but its prognostic role in predicting HCC development of HBV-related decompensated cirrhosis remains unclear. In our study, we evaluated the performance of baseline liver stiffness measurement (LSM) by MRE in predicting HCC development in patients with HBV-related decompensated cirrhosis. Our results showed that MRE-based LSM was associated with HCC development and is independently predictive of HCC development in patients with HBV-related decompensated cirrhosis.

Yi Wang¹, Xinqi Wang², Lu Wang², Lizhi Xie³, Qinhe Zhang⁴, and Ailian Liu^4
1Department of Radiology, Dalian Friendship Hospital, Dalian, China, ²School of Medical Imaging, Dalian Medical University, Dalian, China, ³GE Healthcare, MR Research China, Beijing, China, ⁴Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China

This work aimed for diffusion tensor imaging (DTI) quantitative parameter texture features based strategy to identify solid pseudopapillary neoplasm（SPN）and pancreatic neuroendocrine tumors（PNET），which may represent a diagnostic challenge due to many overlapping MRI features. The results showed that Large Area Emphasis (AUC: 0.737, sensitivity: 64.7%, specificity: 80%on FA signal intensity) was the optimal strategy to identify SPN and PNET.

Jie Liu¹, Shujian Li¹, Qinchen Cao¹, Marcel Dominik Nickel², Jingliang Cheng¹, and Jinxia Zhu^3
1the First Affiliated Hospital of Zhengzhou University, Zheng zhou, China, ²MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, ³MR Collaboration, Siemens Healthineers Ltd., Beijing, China

We investigated the feasibility of T1-mapping to predict cervical cancer (CC) recurrence after treatment. Our results show that quantitative T1 values of the primary tumor could effectively predict the CC recurrence after surgery or concurrent chemoradiotherapy (CCRT). These findings suggest that the T1-mapping method could be valuable for evaluating CC recurrence after treatment, and native T1 values of the primary tumor could predict cervical cancer recurrence.

Angela Turnbull¹, N. Jane Taylor², Amish Lakhani², William McGuire², Rachael Bowie², Roberto Alonzi³, and Alan Mcwilliam^4
1Radiotherapy Physics, Mount Vernon Cancer Centre, Northwood, United Kingdom, ²Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, United Kingdom, ³Mount Vernon Cancer Centre, Northwood, United Kingdom, ⁴The Christie NHS Foundation Trust and Division of Cancer Services and University of Manchester, Manchester, United Kingdom

Initial results of a prostate cancer study investigating whether multiparametric MRI (MP-MRI), involving diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI, can predict or assess tumour response to radiotherapy (RT) and potentially support adaptive radiotherapy for high-risk patients.  Adaptive radiotherapy is a treatment technique utilised to minimise radiation related toxicity.  For some cancers it is possible to adapt radiotherapy according to physical changes that occur during treatment.  This is not appropriate for prostate cancer treatment since observable changes are generally due to rectal movement, however it may be possible to use multiparametric MRI (MP-MRI) to measure treatment response.

Wenjun Hu¹, Lihua Chen ¹, Liangjie Lin², Xu Dai², Jiazheng Wang ², and Ailian Liu^1
1Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China, ²Philips Healthcare, Beijing, China

Bone metastasis is an important issue in the management of prostate cancer, and can drastically alter the treatment strategy. PET/CT has been widely used in the diagnosis of bone metastasis; however, the high cost and radiation exposure limit its extensive clinical applications. APT-weighted imaging and IVIM, recent developed function-oriented MRI sequences, allow for a non-invasive visualization of tissue composition and microscopic information without the need for contrast agents. Results of this study indicate the APT value and IVIM parameters can effectively predict bone metastases in prostate cancer. A combination of APT and D* mono can further improve the prediction performance.

Sai Man Cheung¹, Wing Shan Wu¹, Nicholas Senn¹, Ravi Sharma², Trevor McGoldrick², Tanja Gagliardi^1,3, Ehab Husain⁴, Yazan Masannat⁵, and Jiabao He^1
1Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom, ²Oncology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, ³Radiology Department, Royal Marsden Hospital, London, United Kingdom, ⁴Pathology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, ⁵Breast Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom

Breast cancer is a major and expanding health challenge, and neoadjuvant chemotherapy (NACT) is increasingly prescribed to facilitate breast surgery in advanced breast cancer with an ongoing demand for improved imaging methods accurately reflecting disease load. Tissue perfusion, a sensitive marker of cancer metabolism, can be derived from intravoxel incoherent motion (IVIM) model, and recent Bayesian algorithm yields improved sensitivity and precision in breast cancer by us and pancreatic cancer. We therefore hypothesise that IVIM model powered by Bayesian algorithm is able to detect early treatment-induced changes in tumour perfusion and diffusion, with the potential to impact patient care pathway. 

Alberto Colombo¹, Eleonora Giardini², Paul Eugene Summers¹, Paola Pricolo¹, Fabio Zugni¹, Maddalena Belmonte¹, and Giuseppe Petralia^3,4
1Division of Radiology, IEO European Institute of Oncology IRCCS, Milan, Italy, ²Degree course in Medical radiology, imaging and radiotherapy techniques, University of Milan, Milan, Italy, ³Precision Imaging and Research Unit, Department of Medical Imaging and Radiation Sciences, IEO European Institute of Oncology IRCCS, Milan, Italy, ⁴Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy

Evaluating short and long-term apparent diffusion coefficient (ADC) and relative fat fraction (rF%) changes could provide a better understanding of therapy response of bone metastases from breast cancer. Baseline ADC and rF% values computed from whole-body MRI, were compared with those measured at 12 and 36 week evaluations after treatment start. ADC and rF% significantly increased in responders at 12-weeks. At 36-weeks, ADC values range broadened, while rF% further increased. Short-term ADC and rF% changes are consistent with previous reports. Long-term changes highlight two patterns of response in which either high diffusion or fat repopulation prevail.