RESUMO
PURPOSE: To evaluate the value of a browser-based PI-RADS Score Calculator (PCalc) compared to MRI reporting using the official PI-RADS v2.1 document (PDoc) for non-specialized radiologists in terms of reporting efficiency, interrater agreement and diagnostic accuracy for detection of clinically significant prostate cancer (PCa). METHODS: Between 09/2013 and 04/2015, 100 patients (median age, 64.8; range 47.5-78.2) who underwent prostate-MRI at a 3 T scanner and who received transperineal prostate mapping biopsy within <6 months were included in this retrospective study. Two non-specialized radiology residents (R1, R2) attributed a PI-RADS version 2.1 score for the most suspect (i. e. index) lesion (i) using the original PI-RADS v2.1 document only and after a 6-week interval (ii) using a browser-based PCalc. Reading time was measured. Reading time differences were assessed using Wilcoxon signed rank test. Intraclass-correlation Coefficient (ICC) was used to assess interrater agreement (IRA). Parameters of diagnostic accuracy and ROC curves were used for assessment of lesion-based diagnostic accuracy. RESULTS: Cumulative reading time was 32:55 (mm:ss) faster when using the PCalc, the difference being statistically significant for both readers (p < 0.05). The difference in IRA between the image sets (ICC 0.55 [0.40, 0.68]) and 0.75 [0.65, 0.82] for the image set with PDoc and PCalc, respectively) was not statistically significant. There was no statistically significant difference in lesion-based diagnostic accuracy (AUC 0.83 [0.74, 0.92] and 0.82 [95 %CI: 0.74, 0.91]) for images assessed with PDoc as compared to PCalc (AUC 0.82 [0.74, 0.91] and 0.74 [95 %CI: 0.64, 0.83]) for R1 and R2, respectively. CONCLUSION: Non-specialized radiologists may increase reading speed in prostate MRI with the help of a browser-based PI-RADS Score Calculator compared to reporting using the official PI-RADS v2.1 document without impairing interreader agreement or lesion-based diagnostic accuracy for detection of clinically significant PCa.
RESUMO
OBJECTIVES: To compare interreader agreement and diagnostic accuracy of LI-RADS v2018 categorization using quantitative versus qualitative MRI assessment of arterial phase hyperenhancement (APHE) and washout (WO) of focal liver lesions. METHODS: Sixty patients (19 female; mean age, 56 years) at risk for HCC with 71 liver lesions (28 HCCs, 43 benign) who underwent contrast-enhanced MRI were included in this retrospective study. Four blinded radiologists independently assigned a qualitative LI-RADS score per lesion. Two other radiologists placed ROIs within the lesion, adjacent liver parenchyma, and paraspinal musculature on pre- and post-contrast MR images. The percentage of arterial enhancement and the liver-to-lesion contrast ratio were calculated for quantification of APHE and WO. Using these quantitative parameters, a quantitative LI-RADS score was assigned. Interreader agreement and AUCs were calculated. RESULTS: Interreader agreement was similar for qualitative and quantitative LI-RADS (κ = 0.38 vs. 0.40-0.47) with a tendency towards improved agreement for quantitatively assessed APHE (κ = 0.65 vs. 0.81) and WO (κ = 0.53 vs. 0.78). Qualitative LI-RADS showed an AUC of 0.86, 0.94, 0.94, and 0.91 for readers 1, 2, 3, and 4, respectively. The quantitative LI-RADS score where APHE/WO/or both were replaced showed an AUC of 0.89/0.84/0.89, 0.95/0.92/0.92, 0.93/0.91/0.89, and 0.91/0.86/0.88 for readers 1, 2, 3, and 4, respectively. Sensitivity of LR-4/5 slightly increased, while specificity slightly decreased using quantitative APHE. CONCLUSION: Qualitative and quantitative LI-RADS showed similar performance. Quantitatively assessed APHE showed the potential to increase interreader agreement and sensitivity of HCC diagnosis, whereas quantitatively assessed WO had the opposite effect and needs to be redefined. KEY POINTS: ⢠Quantitative assessment of arterial phase hyperenhancement shows the potential to increase interreader agreement and sensitivity to diagnose hepatocellular carcinoma. ⢠Adding quantitative measurements of major LI-RADS features does not improve accuracy over qualitative assessment alone according to the LI-RADS v2018 algorithm.