Using the Kaiser Score as a clinical decision rule for breast lesion classification: Does computer-assisted curve type analysis improve diagnosis?

PURPOSE: We aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI. METHOD: This IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis. RESULTS: In total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787). CONCLUSIONS: The performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.

How much can abbreviated protocols for breast MRI increase patient throughput? a multi-centric evaluation.

PURPOSE: To assess the impact of abbreviated breast MRI protocols on patient throughput considering non-scanning time and differences between in- and out-of-hospital settings. MATERIALS & METHODS: A total of 143 breast MRI exams from four study sites (hospital, three radiology centers) were included in this retrospective study. Total exam time (TET), Table Time (TT), Scan Time (ST), Table Switch Time (TST) and Planning Time (PT) were determined from consecutive breast MRI examinations. Possible number of scans and exams per hour were calculated. Four scan protocols were compared: full diagnostic protocol (n = 34, hospital), split dynamic protocol (n = 109, all sites) and two abbreviated protocols (n = 109, calculated, all sites). Data were described as median and interquartile range (IQR) and compared by Mann-Whitney-U-Test. RESULTS: Non-scanning time increased from 50% to 74% of the TET with a TST of 46% and a PT of 28% in the shortest abbreviated protocol. Number of possible scans per hour increased from 4.7 to 18.8 while number of possible exams per hour only increased from 2.3 to 5.1. Absolute TST (4.7 vs. 5.7 min, p = 0.46) and TET (18 min each, p = 0.35) did not differ significantly between in- and out-of-hospital exams. Absolute (4.4 vs. 2.8 min, p < 0.001) and relative (23 vs. 13%, p < 0.001) PT and TT (13.3 vs. 11.5 min, p = 0.004) was longer and relative TST (27% vs. 34%, p = 0.047) was shorter in hospital. CONCLUSION: TST and PT significantly contribute to TET and challenge the effectiveness of abbreviated protocols for increasing patient throughput. These findings show only low setting-dependent differences.

Impact of PI-QUAL on PI-RADS and cancer yield in an MRI-TRUS fusion biopsy population.

PURPOSE: To test the inter-reader agreement of the Prostate Imaging Quality (PI-QUAL) score for multiparametric prostate MRI and its impact on diagnostic performance in an MRI-ultrasound fusion biopsy population. PATIENTS AND METHODS: Pre-biopsy multiparametric (T2-weighted, DWI, and DCE) prostate MRIs (mpMRI) of 50 patients undergoing transrectal ultrasound-guided MRI-fusion (MRI-TRUS) biopsy were included. Two radiologists independently assigned a PI-QUAL score to each patient and assessed the diagnostic quality of individual sequences. PI-RADS categories were assigned to six regions per prostate (left and right: base/mid-glandular/apex). Inter-reader agreement was calculated using Cohen's kappa and diagnostic performance was compared by the area under the receiver operating characteristics curve (AUC). RESULTS: In 274 diagnostic areas, the malignancy rate was 62.7% (22.5% clinically significant prostate cancer, ISUP ≥ 2). Inter-reader agreement for the diagnostic quality was poor for T2w (kappa 0.19), fair for DWI and DCE (kappa 0.23 and 0.29) and moderate for PI-QUAL (kappa 0.51). For PI-RADS category assignments, inter-reader agreement was very good (kappa 0.86). Overall diagnostic performance did not differ between studies with a PI-QUAL score > 3 compared to a score ≤ 3 (p = 0.552; AUC 0.805 and 0.839). However, the prevalence of prostate cancer was significantly lower when the PI-QUAL score was ≤ 3 (16.7% vs. 30.2%, p = 0.008). CONCLUSION: PI-QUAL has only a limited impact on PI-RADS diagnostic performance in patients scheduled for MRI-TRUS fusion biopsy. However, the lower cancer prevalence in the lower PI-QUAL categories points out a risk of false-positive referrals and unnecessary biopsies if prostate imaging quality is low.