Debbie Anaby¹, Maria Raitses-Gurevich², Sara Apter^1,3, Yael Inbar^1,3, Hadassa Degani⁴, and Talia Golan^2,3
1Diagnostic Imaging Department, Sheba Medical Center, Ramat Gan, Israel, ²Department of Oncology, Sheba Medical Center, Ramat Gan, Israel, ³Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel, ⁴Life Sciences, Weizmann Institute of Science, Rehovot, Israel

Early detection of pancreatic cancer is challenging but essential to improve its poor prognosis. This preliminary study utilized DT-MRI in pancreas in a clinical setting. DT-MRI was based on two pairs of b-values (0,500 s/mm² and 100,500 s/mm²), such that the existence of a fast diffusing component was observed. We found that pancreatic tumors show similar values of parametric DTI measures (λ₁ and MD-ADC) when using both b-value pairs, suggesting that the fast diffusing component is reduced compared with healthy or cystic pancreatic regions. We conclude that DT-MRI of the pancreas may assist in the detection of pancreatic tumors.

Qi Liu¹, Wei Xing¹, Jilei Zhang², JingGang Zhang¹, Jie Chen¹, and Bei Li^1
1Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China, ²Clinical Science, Philips Healthcare, Shanghai, China

This study explored the feasibility of evaluating fibrosis of patients with PDAC and correlate it with histopathological features using IVIM-DWI compared with DWI. No statistically significant differences were found in ADC and D* values between the high- and low-fibrosis groups. A significant negative correlation between D values and fibrosis and a significant positive correlation between f values and fibrosis were observed. D and ƒ values derived from the IVIM model had high sensitivity and diagnostic performance for grading fibrosis in PDAC compared with the conventional DWI model. IVIM-DWI could serve as an imaging biomarker for predicting the fibrosis grade of PDAC.

Gang FENG¹, Mingxiang Sun¹, Liling Peng¹, Zhaoting Meng¹, and Xin Gao^1
1Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China

To explore the value of assessing pancreatic cancers with integrated positron emission tomography (PET)/magnetic resonance imaging (MRI), fluorine-18 fluorodeoxyglucose (FDG) PET and diffusion weighted imaging (DWI) were applied. Integrated PET/MR is a promising and powerful tool for pancreatic tumor detection and assessment. It is relatively advantageous to combine PET and DWI together to discriminate malignant tumors from benign lesions.

Ravneet Vohra¹, Yak-Nam Wang², Helena Son³, Stephanie Totten², and Donghoon Lee^1
1Radiology, University of Washington, Seattle, WA, United States, ²Applied Physics Laboratory, University of Washington, Seattle, WA, United States, ³Gastroenterology, University of Washington, Seattle, WA, United States

Pancreatic cancer is expected to become the second leading cause of the cancer related deaths in the USA by 2020. A genetically engineered mouse model (KPC) offers an alternative to transplantation models for preclinical therapeutic evaluation as it expresses mutations similar to human pancreatic cell. Magnetic resonance imaging can be used to monitor tumor microenvironment in variety of tumors. The goal of this study was to monitor tumor microenvironment in KPC mouse model during the early stages of tumor development.

Noriko Mori¹, Balaji Krishnamachary¹, Yelena Mironchik¹, and Zaver M. Bhujwalla^1,2,3
1The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, United States, ²The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University, Baltimore, MD, United States, ³Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis due to a combination of late-stage diagnosis and limited response to radiation and chemotherapy.  Effective treatments for PDAC are urgently needed.  Mutant Kras has been reported as a major cause of glutamine (Gln) addiction in PDAC.  Here we investigated the effects of Gln depletion on PDAC cell survival and metabolism.  Our data identified Gln as critical for PDAC cell viability.  Gln depletion significantly altered choline metabolism in the cell lines investigated.

Longshuang Wang¹, Yi Wang², Ailian Liu³, and Qinhe Zhang^3
1School of Medical Imaging,Dalian Medical University,Dalian, China, Dalian Liaoning, China, ²Department of Radiology, Dalian Friendship Hospital, Dalian, China, Dalian Liaoning, China, ³Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian Liaoning, China

It is difficult to differentiate the solid pseudopapillary tumor of the pancreas (SPTP) from pancreatic neuroendocrine tumors (PNET), due to their similar imaging characteristics. Enhanced T2 * weighted angiography (ESWAN) technique can simultaneously obtain amplitude, phase, R2 * and T2 * values, which can quantitatively assess the magnetic sensitivity characteristics of tissues. There was significant difference in R2 * (AUC: 0.707; sensitivity: 91.3%; specificity: 46.7%)and T2*(AUC: 0.829; sensitivity: 73.9%; specificity: 86.7%)between SPTP and PNET. Therefore, ESWAN may be an effective method to identify SPTP and PNET.

Ravneet Vohra¹, Yak-Nam Wang², Helena Son³, Stephanie Totten², and Donghoon Lee^1
1Radiology, University of Washington, Seattle, WA, United States, ²Applied Physics Laboratory, University of Washington, Seattle, WA, United States, ³Gastroenterology, University of Washington, Seattle, WA, United States

Pancreatic cancer is expected to become the second leading cause of the cancer related deaths in the USA by 2020. The goal of all pre-clinical magnetic resonance imaging (MRI) studies is to translate the pre-clinical MR values to the clinical scanners and ultimately to human population. MRI has been proven to be extremely useful in clinical trials for monitoring tumor development and assessing therapeutic effects of novel therapeutic strategies. The aim of this study was to measure (T2) relaxation time and magnetization ratio (MTR) in a mouse model of pancreatic ductal adenocarcinoma (PDA) at pre-clinical (14T) and clinical (3T) scanner.

Raj Kumar Sharma¹, Balaji Krishnamachary¹, Ishwarya Sivakumar¹, Yelena Mironchik¹, Marie-France Penet¹, Paul T Winnard Jr.¹, Santosh K. Bharti¹, and Zaver M. Bhujwalla^1
1Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States

Pancreatic cancer cells are glutamine dependent for growth and proliferation. The glutamine transporter SLC1A5 is upregulated in pancreatic cancer and is being actively investigated as a pharmacological target.  We genetically engineered human pancreatic cancer cells to express SLC1A5 shRNA to downregulate SLC1A5. 1H MRS was used to analyze metabolic differences in SLC1A5 downregulated Pa04C_SLC1A5 pancreatic cancer cells and tumors compared to empty vector cells and tumors.  SLC1A5 downregulation resulted in a significantly lower glutamine/glutamate ratio in Pa04C_SLC1A5 cells.  In Pa04C_SLC1A5  tumors we observed a significant reduction of several metabolites highlighting the metabolic reprogramming that occurred in tumors with SLC1A5 downregulation.  

Yingyu Lin¹, Mengzhu Wang², and Shi-Ting Feng^1
1The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, ²MR Scientific Marketing, Siemens Healthcare, Guangzhou, China

Esophageal cancer ranks seventh in terms of incidence and sixth in mortality among all cancers. Accurate staging of esophageal cancer helps to choose appropriate therapeutic strategy. Current imaging modalities used for evaluating esophageal cancer have their own disadvantages. Therefore, we compared MRI, which is non-invasive, non-radiating and of high soft-tissue resolution, with EUS in preoperative T staging and with PET/CT in preoperative lymphatic metastases of esophageal cancer. In this study, MRI showed higher sensitivity, specificity and accuracy in T staging, while MRI and PET/CT showed similar performance in lymph nodes evaluation.

Yoshihiko Fukukura¹, Yuichi Kumagae¹, Koji Takumi¹, Hiroaki Nagano¹, Masanori Nakajo¹, Kiyohisa Kamimura¹, Takashi Iwanaga², Yuta Akamine³, and Takashi Yoshiura^1
1Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan, ²Kagoshima University Hospital, Kagoshima, Japan, ³Philips Japan, Minatoku, Japan

This study focused on the feasibility of pseudo continuous arterial spin labeling (pCASL) perfusion MRI as a non-invasive tool for predicting the response of locally advanced rectal cancer treated with neoadjuvant chemotherapy in comparison with dynamic contrast-enhanced MRI and diffusion-weighted imaging. Our results showed blood flow derived from pCASL was significantly higher in responders than in non-responders. These results suggested the promise of pCASL as a non-invasive alternative to dynamic contrast-enhanced MRI for predicting the treatment response to NAC in locally advanced rectal cancer.

Yuhui Liu¹, AIlian Liu¹, Anliang Chen¹, Jiazheng Wang², Geli Hu², Wan Dong¹, Qingwei Song¹, Mingxiao Wang¹, Xinru Zhang¹, and Xinao Wang^1
1The First Affiliated Hospital of Dalian Medical University, Dalian, China, Dalian, China, ²Philips Healthcare,Beijing,China, Beijing, China

This study aims to evaluate the value of quantitative T2-mapping in distinguish rectal tubular adenocarcinoma from non-tubular adenocarcinoma, which can provide rich information and help clinical decision-making. The results showed that the quantitative value of T2mapping of rectal tubular adenocarcinoma was significantly different from that of rectal non-tubular adenocarcinoma. Therefore, quantitative T2 mapping can be used as a non-invasive method for diagnosis rectal tubular adenocarcinoma and non-tubular adenocarcinoma.

Xiaoyao Lei¹, Yaxin Niu¹, Longchao Li¹, Min Tang¹, Yanrong Yang¹, Xiaoling Zhang¹, Xin Zhang¹, Juan Li¹, and Xiuzheng Yue^2
1Shaanxi Provincial People's Hospital, Xi-an, China, ²Philips Healthcare, Beijing, China

The study aimed to explore the impact of three methods of delineating region of interest (ROI) methods on the measurement of tumor amide proton transfer-weighted (APTw) values. The result showed that whole volume ROI method was reproducible and could reflect the pathophysiological condition of the tumor.

Yunxing Tang¹, Ailian Liu¹, Jiazheng Wang², Zhiwei Shen², Yunsong Liu¹, Yuhui Liu¹, Anliang Chen¹, and QingWei Song^1
1The First Affiliated Hospital of Dalian Medical University, Dalian, China, ²Philips Healthcare, Beijing, China

Clinical diagnosis and real-time evaluation of chemotherapy response for rectal cancer remain challenging due to the lack of effective non-invasive examinational means. The quantitative T2 mapping technique is an effective method for MRI relaxometry in tissues. In this study, we demonstrated that T2 values were significantly higher in rectal cancer than those in the healthy rectal wall, and significantly increased after chemotherapy. Therefore, quantitative T2 mapping might be a promising non-invasive method in the diagnosis and chemotherapy response tracking of rectal cancer.

Deshuo Dong¹, Ailian liu¹, Jiazheng Wang², Peng Sun², Anliang Chen¹, Wan Dong¹, Yuhui Liu¹, Qingwei Song¹, and Renwang Pu^1
1Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, ²Philips Healthcare, Beijing, China

Rectal cancer with and without vascular invasion differ greatly in terms of biological behavior, treatment, and prognosis. The T2 mapping and DKI allows non-invasive evaluation of tissue composition. In this study, we investigate the performance of the combination of T2 mapping and DKI on differentiating rectal cancer with and without vascular invasion. The results indicate a better differential diagnosis is achieved by the joint use of T2 mapping and DKI.

Mohaddese Mohammadi¹, Elena Kayee¹, Youngwook Kee¹, Jennifer Golia Pernicka ², Iva Petkovska², and Ricardo Otazo ^2
1Medical physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Memorial Sloan Kettering Cancer Center, New York, NY, United States

Deep learning denoising using a convolutional neural network (DnCNN) is proposed to accelerate the acquisition of diffusion-weighted imaging (DWI) data in patients with rectal tumors. 4-fold acceleration was achieved by reducing the number of averages from 16 to 4 and applying the DnCNN to denoise the data. The DnCNN was trained using pairs of noisy (1 average) and reference (16 averages) images from 92 patients. The trained network was then tested with the data from 6 patients and the results were evaluated qualitatively by radiologists. DnCNN represents a powerful approach to improve efficiency of DWI in patients with rectal cancer.

Endre Grøvik^1,2, Darvin Yi³, Franziska Knuth⁴, Sebastian Meltzer⁵, Anne Negård⁵, and Kathrine Røe Redalen^4
1Department for Diagnostic Physics, Oslo University Hospital, Oslo, Norway, ²Faculty of Health Sciences, University of South-Eastern Norway, Drammen, Norway, ³University of Illinois at Chicago, Chicago, IL, United States, ⁴Norwegian University of Science and Technology, Trondheim, Norway, ⁵Akershus University Hospital, Lørenskog, Norway

Treatment of rectal cancer often requires repeated identification of the tumor volume by means of manual delineation by expert radiologists or oncologists. This is a tedious and time-consuming task, particularly with the growing use of multi-sequence 3D imaging. In this work, we have implemented a deep neural network for automatic detection and segmentation of rectal cancer. Our model demonstrates high detection and segmentation performance, equivalent to that of an expert reader, thus illustrating the potential use of deep learning-based segmentation in a clinically relevant setting.

Haidi LU¹, Fu Shen¹, Yuwei Xia², and Jianping Lu^1
1Changhai Hospital, Shanghai, China, ²Huiying Medical Technology Co., Ltd., Beijing, China

Manual delineation of volume of interest (VOI) is widely used in current radiomics analysis, suffering from high variability. The purpose of our study was to investigate the effects of delineation of VOIs on radiomics analysis for the preoperative T staging based on high-resolution T2WI. The result demonstrated that differences in delineation of VOIs affected radiomics analysis, the minimum contour method has better stability in extracting features and the maximum contour method has better diagnostic efficiency in patients with rectal cancer.

Fu Shen¹ and Shaotinng Zhang^1
1Changhai Hospital, Shanghai, China

This study aimed to explore the value of MP-DWI in the preoperative T staging of rectal cancer. 

Ganlu Ouyang¹, Zhebin Chen^2,3, Jitao Zhou¹, Meng Dou^2,3, Xu Luo^2,3, Han Wen^2,3, Yu Yao^2,3, and Xin Wang^1
1Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China, ²Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China, ³University of Chinese Academy of Sciences, Beijing, China

This work aimed for developing a model for predicting sensitivity and response of total neoadjuvant treatment (TNT) for locally advanced rectal cancer (LARC) based on baseline magnetic resonance imaging (MRI) and clinical data by artificial intelligence method. The results showed that the models for predicting high sensitivity and pCR built with radiomics features achieved the mean area under the ROC curve (AUC) of 0.85 respectively, while the other built with deep-learning (DL) method yielded the mean AUC of 0.82 and 0.84 respectively. The models of two methods for predicting high sensitivity and pCR may be valuable in clinical practice.

Martin Buechert¹ and Arnd-Oliver Schäfer^2
1Medizinische Fakultät, Universität Freiburg, Freiburg, Deutschland, Radiologische Klinik, Medizinphysik, Universitätsklinikum Freiburg, Freiburg, Germany, ²Klinik für Radiologie, Klinikum St. Georg Leipzig, Leipzig, Germany

Significant changes of tumor properties during and after neoadjuvant radiochemo therapy are observed in DCE- as well as in DWI-MRI. However heterogneiity of the patient cohort impede more clear results. To overcome this an increase in patient numbers may allow to gain significant results for sharper definied sub groups. This will include combining single results of DCE- and DWI.MRI data in a more integral approach to increase the predictive value.