Oncology ImagingArchives
Generative AI for spatial tumor growth on MRI: a proof-of-principle study in pediatric diffuse midline glioma
Oncology Imaging 1 min.
Magnetic resonance imaging (MRI) is a cornerstone of non-invasive diagnosis and response monitoring in neuro-oncology, and predictions of spatial tumor progression conditioned on the patients' anatomy are increasingly important. We present a proof-of-principle of personalized spatial tumor progression...
Multimodal deep learning model integrating electronic medical records and CT images for gallbladder cancer diagnosis: a retrospective multicenter study in China
Oncology Imaging 1 min.
Gallbladder cancer (GBC) is a rare gastrointestinal malignancy with a global 5-year survival rate of less than 5%. Early diagnosis is challenging owing to the lack of specific clinical symptoms. Additionally, the high heterogeneity of gallbladder tumors limits the clinical utility of unimodal deep-learning...
Pre-treatment prediction of microsatellite instability in colon cancer: a nomogram model combining clinicopathological features and pre-treatment CT-based radiomics
Oncology Imaging 1 min.
Determining microsatellite instability (MSI) status in colon cancer is crucial for selecting treatment strategies in advanced stages. Thus, accurately identifying MSI status before treatment is essential. Objective: This study aims to evaluate the utility of nomogram model that integrates clinicopathological...
Predictive value of the 68Ga-PSMA-11 PET/CT PRIMARY score for pathological upgrading in patients with ISUP Grade 1 prostate cancer and PSA < 20 ng/mL undergoing radical prostatectomy
Oncology Imaging 1 min.
Pathological upgrading is common in men with ISUP Grade Group (GG) 1 prostate cancer due to sampling limitations. Ga-PSMA-11 PET/CT is promising for characterizing tumor biology. The 5-point PRIMARY score, which considers uptake, focality, and location, has limited data on predicting occult high-grade...
