Impact of ROI Positioning and Lesion Morphology on Apparent Diffusion Coefficient Analysis for the Differentiation Between Benign and Malignant Nonfatty Soft-Tissue Lesions.

OBJECTIVE

The objective of our study was to assess the impact of two methods of apparent diffusion coefficient (ADC) selection on the diagnostic performance of DWI in the characterization of nonfatty soft-tissue masses.

SUBJECTS AND METHODS

Sixty-five histologically confirmed soft-tissue tumors imaged from November 2009 through October 2012 were evaluated. The minimal ADC (ADCmin) and average ADC (ADCavg) values for each tumor were obtained using two ROI-positioning methods: manual and semiautomatic. Two readers correlated the findings to lesion histology and morphology on conventional MRI sequences.

RESULTS

The ADCmin values obtained using the manual method presented a better sensitivity with a similar specificity when compared with the ADCmin values obtained using the semiautomatic method (manual vs semiautomatic: 75-83% and 59-63% vs 58-67% and 63% and 63%, respectively). The interobserver agreement for the ADCmin values was similar between the ADC selection methods (intraclass correlation coefficient = 0.81 and 0.87 for manual and semiautomatic methods, respectively). In the subgroup of solid lesions, the ADCavg values obtained using the manual method offered a better sensitivity for benign-malignant differentiation (60-81% vs 60% and 60% for ADCavg and ADCmin, respectively).

CONCLUSION

The ADCmin values obtained with manual ROI positioning offered the best diagnostic performance for tumor characterization. The semiautomatic method yielded similar specificity values. For solid masses, the ADCavg values were better correlated with tumor histology than the ADCmin values.