Article
Oncology
Qian Lin, Hai Jun Wu, Qi Shi Song, Yu Kai Tang
Summary: In this study, the predictive ability of CT-based radiomics features, clinical features, and deep learning features for a good pathological response (GPR) in NSCLC patients receiving immunotherapy-based neoadjuvant therapy (NAT) was evaluated. The results showed that the entire model had the highest prediction accuracy among the combined radiomics features, clinical characteristics, and deep learning features.
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
Wonjoong Cheon, Seonghoon Jeong, Jong Hwi Jeong, Young Kyung Lim, Dongho Shin, Se Byeong Lee, Doo Yeul Lee, Sung Uk Lee, Yang Gun Suh, Sung Ho Moon, Tae Hyun Kim, Haksoo Kim
Summary: This research introduces a novel IOV prediction network (IOV-Net) that utilizes deep learning to produce high-quality IOV maps, aiming to reduce interobserver variability in oncologists' manual delineation of tumor contours. Experimental results demonstrate that IOV prediction accuracy is high, and clinical feasibility tests show that guidance from IOV maps can significantly reduce IOV and improve radiation therapy efficacy.
Article
Oncology
Hongyue Zhao, Yexin Su, Mengjiao Wang, Zhehao Lyu, Peng Xu, Yuying Jiao, Linhan Zhang, Wei Han, Lin Tian, Peng Fu
Summary: Machine learning models were developed and validated to identify lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) using clinical factors, laboratory metrics, and radiomic features. The models showed good performance in distinguishing between LUAD and LUSC, providing a noninvasive predictive tool for clinical decision-making.
FRONTIERS IN ONCOLOGY
(2022)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Coline Le Meur, Luca Campedel, Dris Kharroubi, Karim Amrane
Summary: This study presents a rare case of relapsed non-small cell lung cancer with pituitary metastasis in a 75-year-old woman. Pituitary metastasis is uncommon, accounting for only approximately 2% of malignant metastases. F-18-FDG PET and cerebral MRI were used to guide the therapeutic strategy due to an atypical pituitary high FDG avidity.
CLINICAL NUCLEAR MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Julie Dewaguet, Marie-Christine Copin, Alain Duhamel, Jean-Baptiste Faivre, Valerie Deken, Martin Sedlmair, Thomas Flohr, Bernhard Schmidt, Alexis Cortot, Eric Wasielewski, Jacques Remy, Martine Remy-Jardin
Summary: This study focused on the perfusion analysis of non-small cell lung cancers using dual-phase, dual-energy CT. The results showed higher perfusion between the tumor edge and lung parenchyma in hypoxic tumors, and functional characteristics of neovascularization were found in mCA IX-positive tumors.
Article
Radiology, Nuclear Medicine & Medical Imaging
Yong Han, Yuan Ma, Zhiyuan Wu, Feng Zhang, Deqiang Zheng, Xiangtong Liu, Lixin Tao, Zhigang Liang, Zhi Yang, Xia Li, Jian Huang, Xiuhua Guo
Summary: This study evaluated the capability of PET/CT images for differentiating histologic subtypes of NSCLC and identified the optimal model from radiomics-based machine learning/deep learning algorithms. Linear discriminant analysis and support vector machine coupled with feature selection method achieved optimal performance for the classification of ADC and SCC. The VGG16 deep learning algorithm outperformed conventional machine learning methods in combination with radiomics for the differential diagnosis of NSCLC subtypes.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2021)
Article
Oncology
Sangjoon Choi, Soo Ick Cho, Minuk Ma, Seonwook Park, Sergio Pereira, Brian Jaehong Aum, Seunghwan Shin, Kyunghyun Paeng, Donggeun Yoo, Wonkyung Jung, Chan-Young Ock, Se-Hoon Lee, Yoon-La Choi, Jin-Haeng Chung, Tony S. Mok, Hyojin Kim, Seokhwi Kim
Summary: The AI-powered TPS analyser assists pathologists in improving consensus and prediction of therapeutic response. The study shows that the revision of TPS with AI assistance increases pathologists' concordance and reduces hazard ratio for overall survival and progression-free survival in immune checkpoint inhibitor treatment.
EUROPEAN JOURNAL OF CANCER
(2022)
Article
Medicine, General & Internal
Silvia Taralli, Valentina Scolozzi, Luca Boldrini, Jacopo Lenkowicz, Armando Pelliccioni, Margherita Lorusso, Ola Attieh, Sara Ricciardi, Francesco Carleo, Giuseppe Cardillo, Maria Lucia Calcagni
Summary: The study evaluated the performance of artificial neural networks in predicting nodal involvement in non-small-cell lung cancer patients using preoperative F-18-FDG PET/CT. Results showed that the neural networks had good performance in predicting nodal involvement, especially in ruling out nodal metastases. The high negative predictive value of the neural networks and PET qualitative assessment suggest their potential for identifying unexpected nodal-metastatic patients in cases of PET-negative images.
FRONTIERS IN MEDICINE
(2021)
Article
Pathology
Ying-Chun Lo, Anna H. Bauer, Igor Odintsov, Stephanie E. Siegmund, Lynette M. Sholl, Fei Dong
Summary: The use of cancer panel sequencing in clinical practice for detecting genetic variants in lung cancer has become common. However, the possibility of unexpected molecular results leading to a reevaluation of the clinical diagnosis has not been systematically evaluated. This study reviewed the sequencing results of 1007 lung cancer patients and found that 12 of them (1.2%) had a final diagnosis of cancer originating from outside the lungs. Integrating clinical, microscopic, and molecular evidence can aid in diagnosis and personalized oncology care.
Letter
Medicine, General & Internal
Hollis Viray, Deepa Rangachari, Daniel B. Costa
Summary: The study reported initial data of trastuzumab deruxtecan in the treatment of lung cancers with ERBB2 mutations, including patients who had previously received ineffective ERBB2 tyrosine kinase inhibitors.
NEW ENGLAND JOURNAL OF MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yunming Xie, Hongguang Zhao, Yan Guo, Fanyang Meng, Xiangchun Liu, Yiying Zhang, Xiaochen Huai, Qianting Wong, Yu Fu, Huimao Zhang
Summary: A PET/CT nomogram incorporating Rad-Score and SUVmax showed significant improvement in predicting lymph node metastasis in patients with NSCLC, with an AUC of 0.881 in the training cohort and 0.872 in the testing cohort. The decision curve analysis also indicated the clinical utility of the nomogram.
EUROPEAN RADIOLOGY
(2021)
Article
Oncology
Chen -Chen Zhang, Wen Yu, Qin Zhang, Xu-Wei Cai, Wen Feng, Xiao-Long Fu
Summary: Postoperative radiotherapy (PORT) is controversial in patients with pathological N2 non-small cell lung cancer. Recent studies have identified potential predictors of PORT. This study developed a decision support framework (DSF) combining risk factors and prognostic index to predict the outcomes of PORT. A specific pN2 subgroup with a high risk of loco-regional recurrence and without certain histological features may benefit from PORT.
RADIOTHERAPY AND ONCOLOGY
(2022)
Review
Genetics & Heredity
Xuhe Liao, Meng Liu, Rongfu Wang, Jianhua Zhang
Summary: This review explores the application of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and the unusual response manifestations they can cause. F-18-FDG PET/CT is shown to be an effective and non-invasive tool for identifying these atypical response patterns, and a series of semi-quantitative parameters derived from this technique are introduced as non-invasive biomarkers for predicting the efficacy of ICIs and the survival of NSCLC patients. The functional criteria based on F-18-FDG PET/CT for immunotherapeutic response assessment are discussed, but further research is needed to validate and improve these assessment systems. Lastly, the review presents the current status and future perspective of novel specific PET probes targeting key molecules relevant to immunotherapy in prediction and response assessment.
FRONTIERS IN GENETICS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Xiaoyu Han, Mingliang Wang, Yuting Zheng, Na Wang, Ying Wu, Chengyu Ding, Xi Jia, Ran Yang, Mingfei Geng, Zhen Chen, Songlin Zhang, Kailu Zhang, Yumin Li, Jia Liu, Jin Gu, Yongde Liao, Jun Fan, Heshui Shi
Summary: The study found that delta-radiomics features have superior diagnostic performance compared to pre-treatment radiomics model and iRECIST criteria in predicting major pathological response to neoadjuvant chemoimmunotherapy for non-small cell lung cancer patients.
EUROPEAN RADIOLOGY
(2023)
Article
Cardiac & Cardiovascular Systems
Katherine J. Bick, Li Ding, Peggy J. Ebner, Anthony W. Kim, Scott M. Atay, Sean C. Wightman, Michael McFadden, Albert J. Farias, Elizabeth A. David
Summary: Patients with multiple high-risk socioeconomic factors in non-small cell lung cancer experience disparities in treatment and survival, which vary by region.
ANNALS OF THORACIC SURGERY
(2022)