Article
Oncology
Jia Lu, Nannan Jiang, Yuqing Zhang, Daowei Li
Summary: The study aimed to develop and validate a CT-based radiomics nomogram for distinguishing between focal-type autoimmune pancreatitis and pancreatic ductal adenocarcinoma. The results showed that the model could accurately differentiate between the two diseases and had good sensitivity and specificity.
FRONTIERS IN ONCOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jiyeon Ha, Sang Hyun Choi, Jae Ho Byun, Kyung Won Kim, So Yeon Kim, Jin Hee Kim, Hyoung Jung Kim
Summary: This study systematically evaluated the diagnostic performance of CT and MRI in differentiating AIP from PDAC. The results showed that MRI had a higher sensitivity than CT, particularly in distinguishing focal AIP from PDAC.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Seung Bae Yoon, Tae Yeon Jeon, Sung-Hoon Moon, Dong Woo Shin, Sang Min Lee, Moon Hyung Choi, Ji Hye Min, Min-Jeong Kim
Summary: This study identified 11 CT characteristics that can help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC). Enlarged pancreas, delayed homogeneous enhancement, and capsule-like rim were indicative of AIP, while discrete pancreatic mass suggested PDAC.
EUROPEAN RADIOLOGY
(2023)
Article
Oncology
Wen Chen, Tao Zhang, Lin Xu, Liang Zhao, Huan Liu, Liang Rui Gu, Dai Zhong Wang, Ming Zhang
Summary: This study demonstrates the value of contrast-enhanced CT-based radiomics in distinguishing high-grade and low-grade hepatocellular carcinoma before surgery. The SVM model showed promising results in accurately differentiating between the two grades of HCC, with high accuracy and specificity in both the training and test datasets.
FRONTIERS IN ONCOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Zhaobang Liu, Ming Li, Changjing Zuo, Zehong Yang, Xiaokai Yang, Shengnan Ren, Ye Peng, Gaofeng Sun, Jun Shen, Chao Cheng, Xiaodong Yang
Summary: The study aimed to create a radiomics-based prediction model using dual-time PET/CT imaging for the classification of PDAC and AIP lesions. The model showed promising performance for discriminating between benign AIP and malignant PDAC lesions, indicating its potential as a diagnostic tool for clinical decision-making.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jing Li, Fang Liu, Xu Fang, Kai Cao, Yinghao Meng, Hao Zhang, Jieyu Yu, Xiaochen Feng, Qi Li, Yanfang Liu, Li Wang, Hui Jiang, Chengwei Shao, Jianping Lu, Yun Bian
Summary: The study aimed to evaluate the diagnostic performance of the rad-score in differentiating fAIP from PDAC. A rad-score model was developed based on the analysis of MDCT images, which demonstrated high sensitivity and specificity in distinguishing fAIP from PDAC.
ACADEMIC RADIOLOGY
(2022)
Article
Medicine, General & Internal
Xin Fan, Han Zhang, Yuzhen Yin, Jiajia Zhang, Mengdie Yang, Shanshan Qin, Xiaoying Zhang, Fei Yu
Summary: This study evaluated the value of texture analysis combined with machine learning for diagnosing spinal metastases, indicating that texture features had higher diagnostic value for spinal metastases compared to SUVmax. The classification models established showed high accuracy and could be valuable for assisting in the diagnosis. Survival analysis revealed a correlation between intensity and patient survival, highlighting the importance of texture analysis in diagnosing and predicting outcomes of spinal metastases.
FRONTIERS IN MEDICINE
(2021)
Review
Immunology
Yang Li, Hanyi Song, Xiangzhen Meng, Runzhuo Li, Patrick S. C. Leung, M. Eric Gershwin, Shucheng Zhang, Siyu Sun, Junmin Song
Summary: Autoimmune pancreatitis (AIP) is a rare fibro-inflammatory disorder caused by autoimmune/inflammatory reactions. There are two subtypes of AIP (AIP-1 and AIP-2) with distinct clinical and histologic features. AIP-2 is a pancreas-restricted disease without a specific serum marker, making evaluation of histologic features crucial for diagnosis. Treatment with glucocorticoids or anti-tumor necrosis factor-alpha antibodies shows promise for AIP-2 patients.
JOURNAL OF AUTOIMMUNITY
(2023)
Article
Medicine, General & Internal
Bettina Katalin Budai, Robert Stollmayer, Aladar David Ronaszeki, Borbala Kormendy, Zita Zsombor, Lorinc Palotas, Bence Fejer, Attila Szendroi, Eszter Szekely, Pal Maurovich-Horvat, Pal Novak Kaposi
Summary: This study aimed to construct a radiomics-based machine learning model for differentiation between non-clear cell and clear cell renal cell carcinomas. The model is robust against institutional imaging protocols and scanners. By collecting CT scans from 209 patients, 107 radiomics features were extracted and used to train a support vector machine classifier. The model achieved comparable performance with an expert radiologist in differentiating the two types of renal cell carcinomas.
FRONTIERS IN MEDICINE
(2022)
Article
Oncology
Liwei Wei, Yongdi Huang, Zheng Chen, Jinhua Li, Guangyi Huang, Xiaoping Qin, Lihong Cui, Yumin Zhuo
Summary: This study aimed to investigate the clinical and non-clinical characteristics affecting the prognosis of renal collecting duct carcinoma (CDC) and develop an accurate prognostic model. The machine learning model showed the best predictive performance and could potentially assist clinicians in making clinical decisions for CDC patients.
FRONTIERS IN ONCOLOGY
(2022)
Article
Medicine, General & Internal
Junya Sato, Hiroyuki Matsubayashi, Hirotoshi Ishiwatari, Tatsunori Satoh, Junichi Kaneko, Kazuma Ishikawa, Masao Yoshida, Kohei Takizawa, Yohei Yabuuchi, Yoshihiro Kishida, Kenichiro Kishida, Kenichiro Imai, Kinichi Hotta, Katsuhiko Uesaka, Keiko Sasaki, Hiroyuki Ono
Summary: A 70-year-old man was diagnosed with autoimmune pancreatitis (AIP) with IgG4-related pathology spreading along the main pancreatic duct. Preoperatively misdiagnosed as a ductal neoplasm, caution should be exercised by clinicians in handling the various forms of AIP.
Article
Medicine, General & Internal
Hyerim Park, So-Yeon Lee, Jooyeon Lee, Juyoung Pak, Koeun Lee, Seung-Eun Lee, Joon-Yong Jung
Summary: Radiomics analysis shows potential in detecting multiple myeloma infiltration in the bone marrow on CT scans of patients with osteopenia. In this study, a radiomics model was developed and analyzed texture features extracted from the bone marrow. The diagnostic performance of the radiomics model was compared to that of radiologists, demonstrating its feasibility.
Article
Radiology, Nuclear Medicine & Medical Imaging
Adam M. Awe, Michael M. Vanden Heuvel, Tianyuan Yuan, Victoria R. Rendell, Mingren Shen, Agrima Kampani, Shanchao Liang, Dane D. Morgan, Emily R. Winslow, Meghan G. Lubner
Summary: The study aimed to develop and evaluate machine learning algorithms to distinguish mucinous from non-mucinous pancreatic cysts using radiomics. A mucinous phenotype classifier was successfully created using texture features, but model performance did not significantly improve compared to the combined model. SHAP analysis identified specific predictive features in the models.
ABDOMINAL RADIOLOGY
(2022)
Article
Oncology
Takayoshi Suzuki, Satoshi Kano, Masanobu Suzuki, Shinichiro Yasukawa, Takatsugu Mizumachi, Nayuta Tsushima, Kanako C. Hatanaka, Yutaka Hatanaka, Yoshihiro Matsuno, Akihiro Homma
Summary: Salivary duct carcinoma (SDC) shows morphological similarities to breast cancer and often exhibits HER2-overexpression. Assessing gene expression differences in SDCs classified by disease onset, the study found higher expression of VEGFA, ERBB2(HER2), IGF1R, RB1, and XBP1 in Ca-ex-PA, with lower expression of SLIT2 and PTEN. These genes primarily function in angiogenesis and the AKT/PI3K signaling pathway, with VEGFA potentially playing a crucial role in distinguishing Ca-ex-PA and de novo SDCs.
FRONTIERS IN ONCOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Liang Zhu, Jing Guo, Zhengyu Jin, Huadan Xue, Menghua Dai, Wen Zhang, Zhaoyong Sun, Jia Xu, Stephan R. Marticorena Garcia, Patrick Asbach, Bernd Hamm, Ingolf Sack
Summary: Tomoelastography can accurately differentiate between PDAC and AIP by assessing the stiffness and fluidity properties of the pancreas. AIP showed lower stiffness and fluidity compared to PDAC, but higher than healthy pancreas, with no influence from secondary obstructive changes.
EUROPEAN RADIOLOGY
(2021)