AIMC Topic: Tumor Burden
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The Desmoid Dilemma: Challenges and Opportunities in Assessing Tumor Burden and Therapeutic Response.
Current oncology (Toronto, Ont.)
May 21, 2025
Desmoid tumors are rare, locally invasive soft-tissue tumors with unpredictable clinical behavior. Imaging plays a crucial role in their diagnosis, measurement of disease burden, and assessment of treatment response. However, desmoid tumors' unique i...
Smart contours: deep learning-driven internal gross tumor volume delineation in non-small cell lung cancer using 4D CT maximum and average intensity projections.
Radiation oncology (London, England)
Apr 18, 2025
BACKGROUND: Delineating the internal gross tumor volume (IGTV) is crucial for the treatment of non-small cell lung cancer (NSCLC). Deep learning (DL) enables the automation of this process; however, current studies focus mainly on multiple phases of ...
Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance.
Neuroradiology
Apr 4, 2025
PURPOSE: To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.
Scientific reports
Mar 31, 2025
Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its a...
Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 22, 2025
BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes a...
A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer.
Cell reports. Medicine
Mar 20, 2025
Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with cancer. Accurate identification and quantification are crucial for effective patient management, including precise diagnosis, prognosis, and therapy evalu...
Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer.
BMC cancer
Mar 13, 2025
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
Interstitial-guided automatic clinical tumor volume segmentation network for cervical cancer brachytherapy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 6, 2025
Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial brachytherapy cervical cancer. However, the prominent differences in gray values due to the interstitial needles bring great challenges on deep learni...
Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.
HPB : the official journal of the International Hepato Pancreato Biliary Association
Mar 4, 2025
BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellular carcinoma (HCC) remains challenging. Nonetheless, effective tools to assess MILS complexity are still lacking. Machine learning (ML) models could i...
Tumor Burden
Hepatectomy
Male
Retrospective Studies
Middle Aged
Carcinoma, Hepatocellular
Female
Risk Assessment
Treatment Outcome
Risk Factors
Humans
Predictive Value of Tests
Liver Neoplasms
Aged
Machine Learning
Minimally Invasive Surgical Procedures
Decision Support Techniques
Databases, Factual
The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.
Scientific reports
Feb 18, 2025
Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis has risen in popularity; however, this is very time and labor intensive limiting its implementation in clinical practice. This study aims to show tha...
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