Dataset Information

Voxel Level Radiologic-Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer.

ABSTRACT: Restriction spectrum imaging (RSI-MRI), an advanced diffusion imaging technique, can potentially circumvent current limitations in tumor conspicuity, in vivo characterization, and location demonstrated by multiparametric magnetic resonance imaging (MP-MRI) techniques in prostate cancer detection. Prior reports show that the quantitative signal derived from RSI-MRI, the cellularity index, is associated with aggressive prostate cancer as measured by Gleason grade (GG). We evaluated the reliability of RSI-MRI to predict variance with GG at the voxel-level within clinically demarcated prostate cancer regions.Ten cases were processed using whole mount sectioning after radical prostatectomy. Regions of tumor were identified by an uropathologist. Stained prostate sections were scanned at high resolution (75 ?m/pixel). A grid of tiles corresponding to voxel dimensions was graded using the GG system. RSI-MRI cellularity index was calculated from presurgical prostate MR scans and presented as normalized z-score maps. In total, 2,795 tiles were analyzed and compared with RSI-MRI cellularity.RSI-MRI cellularity index was found to distinguish between prostate cancer and benign tumor (t = 25.48, P < 0.00001). Significant differences were also found between benign tissue and prostate cancer classified as low-grade (GG = 3; t = 11.56, P < 0.001) or high-grade (GG ? 4; t = 24.03, P < 0.001). Furthermore, RSI-MRI differentiated between low and high-grade prostate cancer (t = 3.23; P = 0.003).Building on our previous findings of correlation between GG and the RSI-MRI among whole tumors, our current study reveals a similar correlation at voxel resolution within tumors. Because it can detect variations in tumor grade with voxel-level precision, RSI-MRI may become an option for planning targeted procedures where identifying the area with the most aggressive disease is important. Clin Cancer Res; 22(11); 2668-74. ©2016 AACR.

SUBMITTER: Yamin G

PROVIDER: S-EPMC4896066 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Voxel Level Radiologic-Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer.

Yamin Ghiam G Schenker-Ahmed Natalie M NM Shabaik Ahmed A Adams Dennis D Bartsch Hauke H Kuperman Joshua J White Nathan S NS Rakow-Penner Rebecca A RA McCammack Kevin K Parsons J Kellogg JK Kane Christopher J CJ Dale Anders M AM Karow David S DS

Clinical cancer research : an official journal of the American Association for Cancer Research 20160601 11

<h4>Purpose</h4>Restriction spectrum imaging (RSI-MRI), an advanced diffusion imaging technique, can potentially circumvent current limitations in tumor conspicuity, in vivo characterization, and location demonstrated by multiparametric magnetic resonance imaging (MP-MRI) techniques in prostate cancer detection. Prior reports show that the quantitative signal derived from RSI-MRI, the cellularity index, is associated with aggressive prostate cancer as measured by Gleason grade (GG). We evaluated ...[more]

PMID: 27250935

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Project description:PurposeWe evaluate a novel magnetic resonance imaging (MRI) technique to improve detection of aggressive prostate cancer (PCa).Materials and methodsWe performed a retrospective analysis of pre-surgical prostate MRI scans using an advanced diffusion-weighted imaging technique called restriction spectrum imaging (RSI), which can be presented as a normalized z-score statistic. Scans were acquired prior to radical prostatectomy. Prostatectomy specimens were processed using whole-mount sectioning and regions of interest (ROIs) were drawn around individual PCa tumors. Corresponding ROIs were drawn on the MRI imaging and paired with ROIs in regions with no pathology. RSI z-score and conventional apparent diffusion coefficient (ADC) values were recorded for each ROI. Paired t-test, ANOVA, and logistic regression analyses were performed.ResultsWe evaluated 28 patients with 64 ROIs (28 benign and 36 PCa). The mean difference in RSI z-score (PCa ROI-Benign ROI) was 2.17 (SE = 0.11; p < 0.001) and in ADC was 551 mm(2)/s (SE = 80 mm(2)/s; paired t-test, p < 0.001). The differences in the means among all groups (benign, primary Gleason 3, and primary Gleason 4) was significant for both RSI z-score (F 3,64 = 97.7, p < 0.001) and ADC (F 3,64 = 13.9, p < 0.001). A t-test was performed on only PCa tumor ROIs (n = 36) to determine PCa aggressiveness (Gleason 3 vs. Gleason 4) revealing that RSI z-score was still significant (p = 0.03), whereas, ADC values were no longer significant (p = 0.08). In multivariable analysis adjusting for age and race, RSI z-score was associated with PCa aggressiveness (OR 10.3, 95% CI: 1.4-78.0, p = 0.02) while ADC trended to significance (p = 0.07).ConclusionThe RSI-derived normalized cellularity index is associated with aggressive PCa as determined by pathologic Gleason scores. Further utilization of RSI techniques may serve to enhance standardized reporting systems for PCa in the future.

Project description:BackgroundDiffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI4 ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4 -C1 , yielded greatest tumor conspicuity.PurposeTo evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI4 -C1 ) as a quantitative voxel-level classifier of PCa.Study typeRetrospective.SubjectsForty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa.Field strength/sequenceA 3 T, multishell diffusion-weighted and axial T2-weighted sequences.AssessmentHigh-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI4 -C1 and conventional ADC. Classifier images were also generated.Statistical testsVoxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI4 -C1 was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR90 ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05.ResultsRSI4 -C1 outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR90 (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05).Data conclusionRSI4 -C1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning.Evidence level3 TECHNICAL EFFICACY: Stage 2.

Project description:To determine whether computed tomographic (CT) attenuation values correlate with the histologic measurements of a lung cancer manifesting as a nonsolid nodule and to quantify the extent to which the tumor replaces the airspace within the nodule.Informed consent was obtained to analyze images from CT and pathologic examination under an institutional review board-approved protocol. Fifteen patients who had undergone resection of nonsolid lung cancer were evaluated. On the basis of the CT attenuation values of nonsolid nodules, nonneoplastic lung, soft tissue, and air, the overall proportion of soft tissue in the nodule and nonneoplastic lung and the difference between these two measures were calculated. The analogous measures were obtained from a representative digitized histologic slide. The area of each nodule and the proportion of air within it were measured, and the proportion of soft tissue in the nodule and nonneoplastic lung and the difference between the two were calculated. The difference between the two proportions at CT and histologic examination are the proportions attributable to the cancer on the basis of CT and histologic examinations, respectively. Linear regression was performed to assess the relationship between these measures.The average proportions of soft tissue in the nodule at CT and histologic examination were 48% and 69%, respectively, and they showed significant correlation with each other (P = .02); in addition, each showed significant correlation with the attenuation of the nodule (P < .0001 and P = .02, respectively). The difference between the proportions of soft tissue in nodule and nonneoplastic lung at CT and histologic examination were 37% and 30%, respectively, and both were independent of the tumor diameter (P = .26 and P = .41).The proportion of soft tissue within a nonsolid nodule is correlated with attenuation at CT. This allows for measurement of change within the nodule. An increase of 100 HU in nodule attenuation represents an approximately 10% increase in tumor volume.

Dataset Information

Voxel Level Radiologic-Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer.

Publications

Voxel Level Radiologic-Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer.

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