Davenport, Matthew S.

BackgroundUncertainty regarding the reproducibility of the apparent diffusion coefficient (ADC) hampers the use of quantitative diffusion‐weighted imaging (DWI) in evaluation of the prostate with magnetic resonance imaging MRI. The quantitative imaging biomarkers alliance (QIBA) profile for quantitative DWI claims a within‐subject coefficient of variation (wCV) for prostate lesion ADC of 0.17. Improved understanding of ADC reproducibility would aid the use of quantitative diffusion in prostate MRI evaluation.PurposeEvaluation of the repeatability (same‐day) and reproducibility (multi‐day) of whole‐prostate and focal‐lesion ADC assessment in a multi‐site setting.Study TypeProspective multi‐institutional.SubjectsTwenty‐nine males, ages 53 to 80 (median 63) years, following diagnosis of prostate cancer, 10 with focal lesions.Field Strength/Sequence3T, single‐shot spin‐echo diffusion‐weighted echo‐planar sequence with four b‐values.AssessmentSites qualified for the study using an ice‐water phantom with known ADC. Readers performed DWI analyses at visit 1 (“V1”) and visit 2 (“V2,” 2–14 days after V1), where V2 comprised scans before (“V2pre”) and after (“V2post”) a “coffee‐break” interval with subject removal and repositioning. A single reader segmented the whole prostate. Two readers separately placed region‐of‐interests for focal lesions.Statistical TestsReproducibility and repeatability coefficients for whole prostate and focal lesions derived from median pixel ADC. We estimated the wCV and 95% confidence interval using a variance stabilizing transformation and assessed interreader reliability of focal lesion ADC using the intraclass correlation coefficient (ICC).ResultsThe ADC biases from b0–b600 and b0–b800 phantom scans averaged 1.32% and 1.44%, respectively; mean b‐value dependence was 0.188%. Repeatability and reproducibility of whole prostate median pixel ADC both yielded wCVs of 0.033 (N = 29). In 10 subjects with an evaluable focal lesion, the individual reader wCVs were 0.148 and 0.074 (repeatability) and 0.137 and 0.078 (reproducibility). All time points demonstrated good to excellent interreader reliability for focal lesion ADC (ICCV1 = 0.89; ICCV2pre = 0.76; ICCV2post = 0.94).Data ConclusionThis study met the QIBA claim for prostate ADC. Test–retest repeatability and multi‐day reproducibility were largely equivalent. Interreader reliability for focal lesion ADC was high across time points.Level of Evidence1Technical EfficacyStage 2TOC CategoryPelvis

PURPOSE Multiparametric magnetic resonance imaging (mpMRI) is used widely for prostate cancer (PCa) evaluation. Approximately 35% of aggressive tumors, however, are not visible on mpMRI. We sought to identify the molecular alterations associated with mpMRI-invisible tumors and determine whether mpMRI visibility is associated with PCa prognosis. METHODS Discovery and validation cohorts included patients who underwent mpMRI before radical prostatectomy and were found to harbor both mpMRI-visible (Prostate Imaging and Reporting Data System 3 to 5) and -invisible (Prostate Imaging and Reporting Data System 1 or 2) foci on surgical pathology. Next-generation sequencing was performed to determine differential gene expression between mpMRI-visible and -invisible foci. A genetic signature for tumor mpMRI visibility was derived in the discovery cohort and assessed in an independent validation cohort. Its association with long-term oncologic outcomes was evaluated in a separate testing cohort. RESULTS The discovery cohort included 10 patients with 26 distinct PCa foci on surgical pathology, of which 12 (46%) were visible and 14 (54%) were invisible on preoperative mpMRI. Next-generation sequencing detected prioritized genetic mutations in 14 (54%) tumor foci (n = 8 mpMRI visible, n = 6 mpMRI invisible). A nine-gene signature (composed largely of cell organization/structure genes) associated with mpMRI visibility was derived (area under the curve = 0.89), and the signature predicted MRI visibility with 75% sensitivity and 100% specificity (area under the curve = 0.88) in the validation cohort. In the testing cohort (n = 375, median follow-up 8 years) there was no significant difference in biochemical recurrence, distant metastasis, or cancer-specific mortality in patients with predicted mpMRI-visible versus -invisible tumors (all P > .05). CONCLUSION Compared with mpMRI-invisible disease, mpMRI-visible tumors are associated with underexpression of cellular organization genes. mpMRI visibility does not seem to be predictive of long-term cancer outcomes, highlighting the need for biopsy strategies that detect mpMRI-invisible tumors.

432 Background: In clinical trials and clinical practice, tumor response assessment with computed tomography (CT) defines critical end points in patients with metastatic disease treated with systemic agents. Methods to reduce errors and improve efficiency in tumor response assessment could improve patient care. Methods: Eleven readers from 10 different institutions independently categorized tumor response according to three different therapeutic response criteria using paired baseline and initial post-therapy CT studies from 20 randomly selected patients with metastatic renal cell carcinoma treated with sunitinib as part of a completed phase III multi-institutional study. Images were evaluated with a manual tumor response evaluation method (standard-of-care) and with computer-assisted response evaluation (CARE) that included stepwise guidance, interactive error-identification and correction methods, automated tumor metric extraction, calculations, response categorization, and data/image archival. A cross-over design, patient randomization, and two-week washout period were used to reduce recall bias. Comparative effectiveness metrics included error rate and mean patient evaluation time. Results: The standard-of-care method was on average associated with one or more errors in 30.5% (6.1/20) of patients while CARE had a 0.0% (0.0/20) error rate (p<0.001). The most common errors were related to data transfer and arithmetic calculation. In patients with errors, the median number of error types was 1 (range 1-3). Mean patient evaluation time with CARE was twice as fast as the standard-of-care method (6.4 vs. 13.1 minutes, p<0.001). Conclusions: Computer-assisted tumor response evaluation reduced errors and time of evaluation, indicating better overall effectiveness than manual tumor response evaluation methods that are the current standard-of-care.