Gigin Lin¹, Shang-Yueh Tsai², Yu-Chun Lin¹, Chiao-Yun Lin¹, Ren-Chin Wu¹, and Chyong-Huey Lai^1
1Chang Gung Memorial Hospital, Linkou, Taiwan, ²National Chengchi University, Taipei, Taiwan

Endometrial cancer is the most common gynecologic cancer in the developed countries but responses differently to the standard treatment. We aim to investigate and characterize the values of endometrial total choline levels on 1H MR spectroscopy in predicting overall survival, with tissue metabolomics and biochemistry corroboration. We found that increased total choline levels on MRS depicted high-risk cancer group for nodal metastasis, overall survival and disease-free survival for endometrial cancers, supported by increased tissue GPC levels and overexpression of EDI3. 

Yong-Lan He¹, Yuan Li¹, Cheng-Yu Lin¹, Ya-Fei Qi¹, Xiaoqi Wang², Hai-Long Zhou¹, Hua-Dan Xue¹, and Zheng-Yu Jin^1
1Peking Union Medical College Hospital, Beijing, China, ²Philips Healthcare China, Beijing, China

This study demonstrates the first attempt of 3D TSE APTw MR imaging for endometrial carcinoma with excellent inter-observer measurement agreement. APT values on 22 type I endometrial carcinoma lesions were moderately positively correlated with Ki-67 labelling index (r = 0.583, p=0.004). APT values of Ki-67 low-proliferation group were significantly lower than high-proliferation group (p=0.016) with AUC 0.768. However, no correlation was found between IVIM-derived parameters and Ki-67 labeling index (Dt, p=0.717; D* p=0.151; f, p=0.153).
 

Shujian Li¹, Jie Liu¹, Jinxia Zhu², Tobias Kober³, Tom Hilbert³, and Jingliang Cheng^1
1Department of Magnetic Resonance, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, ²MR Collaboration, Siemens Healthcare Ltd, Beijing, China, ³Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland

This study investigated the feasibility of an accelerated T2-mapping sequence to evaluate cervical cancer (CC) pathological type, grade, stage and lymphovascular space invasion (LVSI) status. The results showed that quantitative T2 values can effectively grade and predict the CC LVSI status, and the ADC values can stratify CC grading. The synthetic T2-weighted (T2W) images showed comparable staging accuracy to the morphological T2W images acquired by a conventional sequence. This suggests that this accelerated T2-mapping sequence may facilitate CC staging and grading. Quantitative T2 values may be superior to ADC values in predicting the LVSI status of CC.

Qi Zhang¹, Xiaoduo Yu¹, Jieying Zhang¹, Han Ouyang¹, Xinming Zhao¹, and Lizhi Xie^2
1Department of Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical, Beijing, China, ²GE healthcare, China, Beijing, China

Cervical cancer is the leading cause of death in gynecological malignancy around the world. The most important prognostic factors include stage at diagnosis, histological subtype, tumor differentiation and et al, which are critical to make the optimal treatment strategies. However, there are still huge challenges in accurate assessment tumor characteristics even by clinical examination and biopsy. DWI has showed promising results in assessment tumor characteristics in cervical cancer. Diffusion kurtosis imaging (DKI), an extension of DWI, is more sensitive to tissue heterogeneity and water exchange. This study demonstrated that DKI-derived parameters are helpful in assessment histological features  of cervical cancer.

Nan Meng¹, Xuejia Wang², Dongming Han², Xiaoyue Ma¹, Yan Bai³, Kaiyu Wang⁴, and Meiyun Wang*^3
1Department of Radiology, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China, ²Department of MRI, the First Affiliated Hospital of Xinxiang Medical University, Weihui, China, ³Department of Radiology, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China, ⁴GE Healthcare, MR Research China, Beijing, China

Amide proton transfer-weighted imaging (APTWI) has unique advantages in displaying the metabolism of diseased proteins. Diffusion kurtosis imaging (DKI) can quantify the diffusion state water molecules in tissues with a non-gaussian model, thus correcting the deviation of the DWI model and improving the detection of lesions. Our results show that compared with APTWI, the DKI is more effective in evaluating the pathological and physiological characteristics of uterus cervical cancer (UCC). 

Xing Meng¹, Ailian Liu ¹, Shifeng Tian¹, Zhiwei Shen², Yishi Wang², Yaxin Niu¹, and Wan Dong^1
1Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China, ²Philips Healthcare, Beijing, China

Amide proton transfer (APT) imaging technology has been applied in the diagnosis of central nervous system tumors to some extent. However, it is only used in the diagnosis of cervical carcinoma in uterine tumors, and there is no study on the differentiation of cervical carcinoma and related tumors with APT. We investigated the value of APT in the differential diagnosis of mass cervical carcinoma and typical uterine leiomyoma.

Mandi Wang¹, Jose Angelo Perucho¹, Queenie Chan², and Elaine Lee^1
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, ²Philips Healthcare, Hong Kong, China

MRI texture analysis was performed in 100 patients with cervical carcinoma. TexRAD software was used for texture extraction and analysis on ADC maps and T1c images. Texture features were compared between histological subtypes, tumour grades, FIGO stages and nodal status. Feature selection was achieved with AUC ≥ 0.70. ADC-derived MPP5 was significantly lower in SCC than ACA, Entropy6 derived from both ADC and T1c increased from FIGO I~II to FIGO III~IV, and ADC-derived Entropy3 was higher in positive nodal status than negative. No texture features could differentiate tumour grades with acceptable diagnostic efficiency.

Jing Zhang¹, Zhicong Li², Yang Song¹, Han Wang², Yefeng Yao¹, and Guang Yang^1
1Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, shanghai, China, ²Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, shanghai, China

Patients with adenomyosis can be treated using Magnetic Resonance Imaging (MRI)-guided Focused Ultrasound Surgery (MRgFUS). However, note all patients have a good response to MRgFUS, some even equire pain management such as with Non-Steroidal Anti-inflammatory Drugs (NSAIDs) following MRgFUS. To evaluate the prognosis of MRgFUS using only MRI images, we used radiomics features together with clinical features to build a machine learning model with our homemade open-source software, namely FeAture Explorer (FAE), based on scikit-learn. We obtained a candidate model with AUC of 0.806 in test cohort.