Innovations in Imaging for Radiation Oncology

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1166

Special Issue Editors


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Guest Editor
Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98105, USA
Interests: radiation oncology; diagnostic imaging; artificial intelligence; radiomics; tumor detection; molecular imaging; treatment planning; radiogenomics

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Guest Editor Assistant
Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98105, USA
Interests: radiation oncology; diagnostic imaging; artificial intelligence; radiomics; tumor detection; molecular imaging; treatment planning; radiogenomics

Special Issue Information

Dear Colleagues,

Radiation oncology, a cornerstone of cancer management, relies heavily on the advancements in radiology for precise treatment planning and monitoring. Imaging modalities like CT, MRI, and PET-CT play a pivotal role in defining tumor boundaries, assessing treatment response, and adapting therapy in real-time.
The field of radiation oncology has witnessed significant advancements in diagnostic techniques, transforming patient care through enhanced precision and accuracy. This Special Issue aims to explore the latest developments in diagnostic imaging, artificial intelligence applications, and molecular imaging techniques that are shaping the future of radiation oncology. Contributions will focus on innovations that improve tumor detection and treatment responses, optimize radiation outcomes, and prevent different complications of radiation. Topics may include, but are not limited to, advanced imaging modalities, AI-based decision support systems, radiomics and radiogenomics, and real-time adaptive imaging techniques. By highlighting these cutting-edge advancements, the issue seeks to bridge the gap between diagnostic imaging and therapeutic applications, fostering interdisciplinary collaboration to enhance cancer treatment outcomes. This issue invites original research, reviews, and case studies from researchers and clinicians who are pioneering these transformative diagnostic approaches.

Dr. Sara Haseli
Dr. Arash Azhideh
Guest Editors

Manuscript Submission Information

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Keywords

  • radiation oncology
  • diagnostic imaging
  • artificial intelligence
  • radiomics
  • tumor detection
  • molecular imaging
  • treatment planning
  • radiogenomics

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Published Papers (1 paper)

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Review

19 pages, 7971 KiB  
Review
Pictorial Review of Soft Tissue Lesions with Calcification
by Zahra Masroori, Peyman Mirghaderi, Sara Haseli, Arash Azhideh, Bahar Mansoori, Eric Chen, Chankue Park and Majid Chalian
Diagnostics 2025, 15(7), 811; https://doi.org/10.3390/diagnostics15070811 - 22 Mar 2025
Viewed by 992
Abstract
Calcifications in soft tissue tumors present critical diagnostic challenges in musculoskeletal imaging. Their presence and morphology can provide key clues for differentiating benign from malignant lesions, influencing both prognosis and management strategies. This pictorial review aims to explore the imaging characteristics, patterns, and [...] Read more.
Calcifications in soft tissue tumors present critical diagnostic challenges in musculoskeletal imaging. Their presence and morphology can provide key clues for differentiating benign from malignant lesions, influencing both prognosis and management strategies. This pictorial review aims to explore the imaging characteristics, patterns, and implications of soft tissue calcifications, with a focus on distinguishing between benign and malignant soft tissue tumors based on the World Health Organization classification. A systematic evaluation of imaging findings in various soft tissue tumor subtypes, including adipocytic, smooth muscle, vascular, chondro-osseous, and tumors of uncertain differentiation, is presented. Additionally, non-neoplastic causes of soft tissue calcifications, such as metabolic and inflammatory conditions, are reviewed for comprehensive differential diagnosis. Our review shows that the presence, distribution, and morphology of calcifications, such as stippled, punctate, coarse, and amorphous patterns, play a crucial role in tumor characterization. Some important examples are phleboliths, which strongly suggest a benign hemangioma, while dystrophic calcification is more commonly associated with malignant entities such as synovial sarcoma and dedifferentiated liposarcoma. Peripheral calcifications with zonal distribution are characteristic of myositis ossificans, whereas central dense calcifications may indicate extra-skeletal osteosarcoma. The review also discusses the significance of calcifications in non-neoplastic conditions, such as calcific tendinitis, tumoral calcinosis, and metabolic diseases, which can mimic soft tissue tumors. Recognizing the imaging characteristics of soft tissue calcifications is essential for accurate tumor classification and appropriate clinical management. This review highlights the importance of integrating radiologic findings with clinical and histopathological data to avoid misdiagnosis and unnecessary interventions. Full article
(This article belongs to the Special Issue Innovations in Imaging for Radiation Oncology)
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