Article
Radiology, Nuclear Medicine & Medical Imaging
Yuki Onozato, Takekazu Iwata, Yasufumi Uematsu, Daiki Shimizu, Takayoshi Yamamoto, Yukiko Matsui, Kazuyuki Ogawa, Junpei Kuyama, Yuichi Sakairi, Eiryo Kawakami, Toshihiko Iizasa, Ichiro Yoshino
Summary: This study developed and validated multiple machine learning models using radiomic features from preoperative [F-18]fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) images to predict the pathological invasiveness of lung cancer.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Madhurima R. Chetan, Fergus V. Gleeson
Summary: The review summarized the current status of radiomics research in predicting treatment response in non-small-cell lung cancer, indicating low quality, lack of reproducibility, and limited clinical evaluation. Efforts towards standardization and collaboration are necessary to identify reproducible radiomic predictors of response. Promising radiomic models need external validation and evaluation within the clinical pathway before being implemented for personalized treatment in NSCLC patients.
EUROPEAN RADIOLOGY
(2021)
Review
Health Care Sciences & Services
Michela Gabelloni, Lorenzo Faggioni, Roberta Fusco, Igino Simonetti, Federica De Muzio, Giuliana Giacobbe, Alessandra Borgheresi, Federico Bruno, Diletta Cozzi, Francesca Grassi, Mariano Scaglione, Andrea Giovagnoni, Antonio Barile, Vittorio Miele, Nicoletta Gandolfo, Vincenza Granata
Summary: Due to the rich vascularization and lymphatic drainage of the pulmonary tissue, lung metastases (LM) are not uncommon in patients with cancer. Radiomics, an active research field aimed at extracting quantitative data from diagnostic images, has potential applications in lesion characterization, treatment planning, and prognostic assessment of patients with LM. This article provides a systematic review of the literature to illustrate the current applications, strengths, and weaknesses of radiomics in this field.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Freba Grawe, Franziska Blom, Michael Winkelmann, Caroline Burgard, Christine Schmid-Tannwald, Lena M. Unterrainer, Gabriel T. Sheikh, Paulo L. Pfitzinger, Philipp Kazmierczak, Clemens C. Cyran, Jens Ricke, Christian G. Stief, Peter Bartenstein, Johannes Ruebenthaler, Matthias P. Fabritius, Thomas Geyer
Summary: PSMA-RADS 1.0 is a reliable method for assessing PSMA-PET/CT with strong consistency and agreement among readers. It shows great potential for establishing a standard approach to diagnosing and planning treatment for prostate cancer patients, and can be used confidently even by readers with less experience.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yoshiharu Ohno, Masao Yui, Daisuke Takenaka, Takeshi Yoshikawa, Hisanobu Koyama, Yoshimori Kassai, Kaori Yamamoto, Yuka Oshima, Nayu Hamabuchi, Satomu Hanamatsu, Yuki Obama, Takahiro Ueda, Hirotaka Ikeda, Hidekazu Hattori, Kazuhiro Murayama, Hiroshi Toyama
Summary: cDWI with a b-value of 600 sec/mm² may improve the accuracy of lymph node staging in NSCLC patients compared to aDWI, STIR, and PET/CT.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Chemistry, Multidisciplinary
Abdul Rahaman Wahab Sait
Summary: Lung cancer is the primary cause of cancer-related deaths worldwide. Deep learning-based medical image analysis plays a crucial role in detecting and diagnosing lung cancer. The author proposes a deep learning model using PET/CT images for lung cancer detection. By applying image preprocessing and augmentation techniques, as well as convolutional neural networks and deep autoencoders, along with optimization algorithms, the model achieves high accuracy and reduces the need for computational resources. The experimental results show that the proposed model has high accuracy and stability with fewer parameters.
APPLIED SCIENCES-BASEL
(2023)
Article
Oncology
Jie Wang, Zhonghang Zheng, Yi Zhang, Weiyue Tan, Jing Li, Ligang Xing, Xiaorong Sun
Summary: This study aimed to develop a prediction model for lymphovascular invasion (LVI) on cT(1-2)N(0)M(0) radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[F-18]fluoro-D-glucose ([F-18]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis. The PET/CT radiomics models showed superior performance in predicting LVI on early stage radiologic solid lung cancer. These models can provide valuable support for clinical treatment decisions.
FRONTIERS IN ONCOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Kailin Qiao, Xueting Qin, Shuai Fu, Jiazhong Ren, Jing Jia, Xinying Hu, Yuanyuan Tao, Shuanghu Yuan, Yuchun Wei
Summary: The uptake of [F-18]AlF-NOTA-FAPI-04 and [F-18]FDG imaging tracers varies in malignant and inflammatory lung lesions, with lower uptake observed in inflammatory lesions. This difference in uptake can be valuable for distinguishing between malignancy and various inflammatory findings.
EUROPEAN RADIOLOGY
(2023)
Review
Medicine, General & Internal
Diana Prieto-Pena, Santos Castaneda, Isabel Martinez-Rodriguez, Belen Atienza-Mateo, Ricardo Blanco, Miguel A. Gonzalez-Gay
Summary: Early recognition of giant cell arteritis is crucial to prevent complications, and while traditional diagnostic methods have limitations, imaging techniques have become key in improving diagnostic accuracy.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Immunology
Haipeng Tong, Jinju Sun, Jingqin Fang, Mi Zhang, Huan Liu, Renxiang Xia, Weicheng Zhou, Kaijun Liu, Xiao Chen
Summary: The study established a machine learning model to predict tumor immune status in non-small cell lung cancer (NSCLC) using F-18-FDG PET/CT radiomics and clinical characteristics. The PET/CT radiomics model outperformed the CT model in predicting CD8 expression, and the combined radiomics-clinical model performed the best.
FRONTIERS IN IMMUNOLOGY
(2022)
Review
Oncology
Nasim Vahidfar, Saeed Farzanefar, Hojjat Ahmadzadehfar, Eoin N. Molloy, Elisabeth Eppard
Summary: This literature review provides a brief overview of the role of nuclear medicine in the diagnosis of obstetric and gynecological cancers. Nuclear medicine has proven to be reliable in diagnostic imaging in nuclear medicine and cancer treatment. [F-18]FDG PET/CT imaging plays a crucial role in investigating gynecological cancer.
Review
Medicine, General & Internal
Lorenzo Cereser, Laura Evangelista, Gianluca Giannarini, Rossano Girometti
Summary: In recent years, prostate magnetic resonance imaging (MRI) has become essential in the primary diagnosis of clinically significant prostate cancer (csPCa). While a negative MRI can prevent unnecessary biopsies, a positive examination prompts targeted biopsy samples, leading to increased csPCa diagnosis with high sensitivity and negative predictive value. The limitations of MRI have sparked discussions on how to stratify biopsy decisions and management based on patient risk and accurately estimate it with clinical and/or imaging findings. Next-generation imaging techniques such as radiolabeled Prostate-Specific Membrane Antigen (PSMA)-Positron Emission Tomography (PET) are expanding their indications in primary staging and diagnosis, offering increased sensitivity and serving as problem-solving tools in indeterminate MRI cases. This review summarizes the current evidence on the role of prostate MRI and PSMA-PET in the primary diagnosis of csPCa and their potential interactions.
Article
Gastroenterology & Hepatology
William McGahan, Venkata Chikatamarla, Paul Thomas, David Cavallucci, Nicholas O'Rourke, Matthew Burge
Summary: SUVmax-p on routine FDG-PET/CT can serve as a useful indicator for predicting early post-operative recurrence and guiding additional pre-operative staging or neoadjuvant therapy.
Article
Multidisciplinary Sciences
Ou Yamaguchi, Kyoichi Kaira, Ichiro Naruse, Yukihiro Umeda, Takeshi Honda, Satoshi Watanabe, Kosuke Ichikawa, Kazunari Tateishi, Norimitsu Kasahara, Tetsuya Higuchi, Kosuke Hashimoto, Shun Shinomiya, Yu Miura, Ayako Shiono, Atsuto Mouri, Hisao Imai, Kunihiko Iizuka, Tamotsu Ishizuka, Koichi Minato, Satoshi Suda, Hiroshi Kagamu, Keita Mori, Ichiei Kuji, Nobuhiko Seki
Summary: This study aimed to investigate the clinical relevance of F-18-FDG PET/CT compared to CT in predicting the response to PD-1 blockade in the early phase. The results showed that metabolic assessment by MTV or TLG was superior to morphological changes on CT for predicting the therapeutic response and survival.
SCIENTIFIC REPORTS
(2022)
Article
Oncology
Takeo Nakada, Yusuke Takahashi, Noriaki Sakakura, Hiroshi Iwata, Takashi Ohtsuka, Hiroaki Kuroda
Summary: This study found that prognostic radiological tools and surgical outcomes for radiologically pure solid adenocarcinomas and squamous cell carcinoma in clinical stage IA were similar. SUVmax was useful in predicting recurrence, while tumor diameter and SUVmax were helpful in predicting pathological lymph node metastasis.
Article
Surgery
Ryu Kanzaki, Masayoshi Inoue, Masato Minami, Yasushi Shintani, Soichiro Funaki, Tomohiro Kawamura, Meinoshin Okumura
Article
Surgery
Ryu Kanzaki, Toru Kimura, Tomohiro Kawamura, Soichiro Funaki, Yasushi Shintani, Masato Minami, Meinoshin Okumura
Article
Surgery
Ryu Kanzaki, Toru Kimura, Tomohiro Kawamura, Soichiro Funaki, Yasushi Shintani, Masato Minami, Shigeru Miyagawa, Koichi Toda, Yoshiki Sawa, Meinoshin Okumura
Article
Cardiac & Cardiovascular Systems
Ryu Kanzaki, Toru Kimura, Tomohiro Kawamura, Soichiro Funaki, Yasushi Shintani, Masato Minami, Makoto Yamasaki, Masaki Mori, Yuichiro Doki, Meinoshin Okumura
INTERACTIVE CARDIOVASCULAR AND THORACIC SURGERY
(2017)
Article
Oncology
Soichiro Funaki, Yasushi Shintani, Tomohiro Kawamura, Ryu Kanzaki, Masato Minami, Meinoshin Okumura
Article
Surgery
Ryu Kanzaki, Masayoshi Inoue, Toru Kimura, Tomohiro Kawamura, Soichiro Funaki, Yasushi Shintani, Masato Minami, Ichiro Takemasa, Tsunekazu Mizushima, Masaki Mori, Meinoshin Okumura
Article
Multidisciplinary Sciences
Ryu Kanzaki, Hisamichi Naito, Kazuyoshi Kise, Kazuhiro Takara, Daisuke Eino, Masato Minami, Yasushi Shintani, Soichiro Funaki, Tomohiro Kawamura, Toru Kimura, Meinoshin Okumura, Nobuyuki Takakura
SCIENTIFIC REPORTS
(2017)
Article
Cardiac & Cardiovascular Systems
Yasushi Shintani, Ryu Kanzaki, Tomohiro Kawamura, Soichiro Funaki, Masato Minami, Meinoshin Okumura, Eiji Okura, Yoshihisa Kadota, Mitsunori Ohta
INTERACTIVE CARDIOVASCULAR AND THORACIC SURGERY
(2017)
Editorial Material
Cardiac & Cardiovascular Systems
Yoko Yamamoto, Yasushi Shintani, Soichiro Funaki, Masaki Taira, Takayoshi Ueno, Tomohiro Kawamura, Ryu Kanzaki, Masato Minami, Yoshiki Sawa, Meinoshin Okumura
ANNALS OF THORACIC SURGERY
(2018)
Article
Biochemistry & Molecular Biology
Toru Momozane, Tomohiro Kawamura, Yumi Itoh, Masato Sanosaka, Tsutomu Sasaki, Ryu Kanzaki, Naoko Ose, Soichiro Funaki, Yasushi Shintani, Masato Minami, Meinoshin Okumura, Hiroshi Takemori
BIOCHEMISTRY AND CELL BIOLOGY
(2018)
Review
Urology & Nephrology
Mohammad Abufaraj, Guido Dalbagni, Siamak Daneshmand, Simon Horenblas, Ashish M. Kamat, Ryu Kanzaki, Alexandre R. Zlotta, Shahrokh F. Shariat
Article
Surgery
Ryu Kanzaki, Naoko Ose, Tomohiro Kawamura, Soichiro Funaki, Yasushi Shintani, Masato Minami, Nobuyuki Takakura, Meinoshin Okumura
WORLD JOURNAL OF SURGERY
(2018)
Article
Respiratory System
Yasushi Shintani, Soichiro Funaki, Naoko Ose, Tomohiro Kawamura, Ryu Kanzaki, Masato Minami, Meinoshin Okumura
JOURNAL OF THORACIC DISEASE
(2018)
Article
Cardiac & Cardiovascular Systems
Ryu Kanzaki, Yasushi Shintani, Masayoshi Inoue, Tomohiro Kawamura, Soichiro Funaki, Masato Minami, Meinoshin Okumura
ANNALS OF THORACIC AND CARDIOVASCULAR SURGERY
(2017)
Article
Oncology
Hidenori Kusumoto, Yasushi Shintani, Ryu Kanzaki, Tomohiro Kawamura, Soichiro Funaki, Masato Minami, Izumi Nagatomo, Eiichi Morii, Meinoshin Okumura