Differentiating Benign and Malignant Soft Tissue Masses by Magnetic Resonance Imaging: Role of Tissue Component Analysis

Abstract

MRI is useful in determining whether a soft tissue mass is malignant or not. Traditional morphologic assessment was reinforced by detailed component characterization analysis. The parameters favoring malignancy were large lesion size, peritumoral edema, necrosis, and absent calcification, absent fibrosis, and lack of fat rim.

Benign vs malignant soft tissue neoplasms: Limitations of magnetic resonance imaging

“…Absence of heterogeneity is a reliable negative predictive indicator for the presence of malignancy. [12] Chen et al [13] found that positive predictive value of necrosis for malignancy was 84.8% and specificity was 90.9%.…”

“…While, Pang et al [22] found that significant risk factors for predicting malignancy include increasing patient age and lesion size greater than or equal to 5 cm, they also found that the relationship to the fascia was less important as a predictor for malignant potential. Chen et al [13] on the other hand found that the parameters favoring malignancy were large lesion size, peritumoral edema, necrosis, and absence of calcification, absence of fibrosis, and lack of fat rim.…”

Scalp lesion: A presenting feature of squamous cell carcinoma of lung

“…The parameters favoring malignancy over MRI scan include large lesion size, peritumoral edema, necrosis, and absence of calcification, absence of fibrosis, and lack of fat rim. [20] The definite diagnosis of metastatic carcinoma hinges on histopathological evaluation of involved skin; FNA can provide a rapid and accurate diagnosis. [16] Tumors may show characteristics of the underlying tumor, or they may have a more anaplastic appearance.…”

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging

“…Texture analysis of DCE images using a structured fractal-based approach improved differentiation between low- and high-grade gliomas by orders of magnitude (20); however, texture analysis is not limited to enhancement patterns. Measures of heterogeneity in T1-weighted (W), T2W, and DW MRI images can reveal differences in cellular density in tumours, which in turn can be matched to histological findings and aid in distinguishing malignant versus benign soft-tissue masses (21). Similarly, analysis of prostate MRI using T2W and DWI sequences has been successful in discriminating prostate cancer from benign prostate tissue and in providing information on prostate cancer aggressiveness using Gleason scores.…”