Diagnostic hierarchy of radiological features in soft tissue tumours and proposition of a simple diagnostic algorithm to estimate malignant potential of an unknown mass. Issue 95 (October 2017)

• Record Type: Journal Article
• Authors: Gruber, Leonhard; Gruber, Hannes; Luger, Anna K.; Glodny, Bernhard; Henninger, Benjamin; Loizides, Alexander
• Is Part Of: European journal of radiology. Issue 95(2017)
• Page Start: 102
• Page End: 110
• Publication Date: 2017-10
• Subjects: STM soft tissue mass -- STS soft tissue sarcoma -- CR radiography -- CT computed tomography -- US ultrasound -- CE contrast-enhanced -- CEUS contrast-enhanced ultrasound -- STIR short tau inversion recovery -- RI resistive index -- Gd gadolinium -- T1w T1-weighted -- T2w T2-weighted -- SI signal intensity -- CNB core needle biopsy -- PPV positive predictive value -- NPV negative predictive value -- OR odds ratio -- LR likelihood ratio -- NV normalized variance -- AUC area under the curve -- ROC curve receiver-operating characteristics curve; Soft tissue tumours -- Sarcoma -- Features -- Prediction -- Classification; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2017.07.020
• Languages: English
• ISSNs: 0720-048X

Abstract

Abstract: Objective: To quantify the diagnostic utility of imaging features in soft tissue masses (STMs) and to provide a ranked list of predictors for malignancy. Subjects and methods: Imaging features in 260 cases of STMs with verified histology were assessed. Diagnostic properties including sensitivity, specificity, positive and negative predictive values, likelihood/odds ratios (OR) and normalized variance (NV) via random forest analysis were calculated. The diagnostic utility of an 8-item checklist consisting of the highest-ranked features was evaluated through a receiver-operating-characteristics (ROC) curve. Results: The most predictive features ( NV/OR in parentheses ) were heterogeneous contrast-enhancement in ultrasound (297.9/15.1) and MRI (197.3/11.9), lesion roundness (209.8/5.5), diffusion restriction (175.8/9.3), cystic/necrotic intralesional areas (167.1/8.3), higher patient age (159.0/2.6), surrounding oedema (155.4/6.5) and intralesional Doppler hypervascularity (134.4/5.1). A simple 8-item checklist was highly predictive of malignancy in cases with at least 75% positive features (0.90 area under the ROC curve, 87.0% sensitivity, 84.5% specificity, 59.5% positive and 96.1% negative predictive value, 36.5 odds ratio) even in cases with only partial feature availability. Conclusion: Features vary widely in their diagnostic value in STMs; an 8-item checklist based on the eight most decisive features can be a simple tool to assess the likelihood for malignancy in unknown soft tissue masses, even though a stratified approach is certainly still advisable when first confronted with an STM.