“Radiological Grading” for Preoperative Assessment of Central Cartilaginous Tumors

In the treatment of musculoskeletal tumors, surgeons sometimes experience discrepancies in the histological grade between the preoperative biopsy and resected tumor specimen, and the frequency of the histological discrepancies in cartilaginous tumors is higher than that in other bone tumors. For cartilaginous tumors, new diagnostic tools or methods for the prediction of histological grades are required to determine appropriate surgical procedures for each patient. Several radiological findings have been reported to be useful in differentiating benign cartilaginous tumors, atypical cartilaginous tumors/grade 1 chondrosarcomas, and high-grade chondrosarcomas. Furthermore, recent studies have shown the high accuracy of radiological scoring systems that integrate several radiological findings to predict the histological grades of cartilaginous tumors. Radiomics, which converts features in radiological images into quantitative data, enables the comprehensive analysis of cartilaginous tumors. Recent reports suggest that radiological diagnoses are highly reliable compared with preoperative histological diagnoses for predicting the final histological diagnosis. Based on previous reports, "radiological grading," i.e., the prediction of histological aggressiveness using radiological modalities, can be important for determining the surgical procedure, in addition to "histological grading." This review article discusses radiological findings, integrated radiological scoring systems, and radiomics-based predictions of histological grades in cartilaginous tumors.

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Publication Details

Journal
Cancers
Published
2026-01-07
DOI
https://doi.org/10.3390/cancers18020193
Primary Topic
Bone Tumor Diagnosis and Treatments
Type
article
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article

“Radiological Grading” for Preoperative Assessment of Central Cartilaginous Tumors

Yohei Asano, Katsuhiro Hayashi, Takashi Higuchi, Hirotaka Yonezawa et al.
Cancers
Bone Tumor Diagnosis and Treatments
article

“Radiological Grading” for Preoperative Assessment of Central Cartilaginous Tumors

Yohei Asano, Katsuhiro Hayashi, Takashi Higuchi, Hirotaka Yonezawa, Shinji Miwa, Satoru Demura, Sei Morinaga
article en

Abstract

In the treatment of musculoskeletal tumors, surgeons sometimes experience discrepancies in the histological grade between the preoperative biopsy and resected tumor specimen, and the frequency of the histological discrepancies in cartilaginous tumors is higher than that in other bone tumors. For cartilaginous tumors, new diagnostic tools or methods for the prediction of histological grades are required to determine appropriate surgical procedures for each patient. Several radiological findings have been reported to be useful in differentiating benign cartilaginous tumors, atypical cartilaginous tumors/grade 1 chondrosarcomas, and high-grade chondrosarcomas. Furthermore, recent studies have shown the high accuracy of radiological scoring systems that integrate several radiological findings to predict the histological grades of cartilaginous tumors. Radiomics, which converts features in radiological images into quantitative data, enables the comprehensive analysis of cartilaginous tumors. Recent reports suggest that radiological diagnoses are highly reliable compared with preoperative histological diagnoses for predicting the final histological diagnosis. Based on previous reports, "radiological grading," i.e., the prediction of histological aggressiveness using radiological modalities, can be important for determining the surgical procedure, in addition to "histological grading." This review article discusses radiological findings, integrated radiological scoring systems, and radiomics-based predictions of histological grades in cartilaginous tumors.

CancersVol. 18(2)
Kanazawa University (JP)
Good health and well-being
Openalex Percentile: Top 95%
Bone Tumor Diagnosis and Treatments
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“Radiological Grading” for Preoperative Assessment of Central Cartilaginous Tumors — Yohei Asano, Katsuhiro Hayashi, et al. · Cancers (2026) | TGRS Research Map | TGRS