Computer-assisted detection of subcutaneous melanomas: feasibility assessment.
RATIONALE AND OBJECTIVES
Subcutaneous melanomas may be missed on computed tomography because of their peripheral location or perceived unimportance, yet they can have clinical significance. The use of a novel computer-assisted detection scheme to locate subcutaneous melanoma lesions in body CT images was investigated.


MATERIALS AND METHODS
The detection software segments subcutaneous fat from the rest of the body and searches for soft tissue density lesions that match a size and shape constraint. Sensitivity and specificity of the proposed method was analyzed by comparing automated lesion detection results in eight patients with 118 subcutaneous melanomas with ground truth data derived from manual tracings of a trained observer.


RESULTS
The sensitivity of subcutaneous melanoma detection was 86%. The false-positive rate was 3.1 per slice. Analysis of the false-positives showed that the most common cause was incorrect classification of muscle as a nodule.


CONCLUSION
This study showed the feasibility of a fully automatic subcutaneous melanoma lesion detection system having good sensitivity. The false-positive rate was high, but avenues for further reduction were identified.