Characterization and stratification of prostate lesions based on comprehensive multiparametric MRI using detailed whole-mount histopathology as a reference standard.

The purpose of this study was to characterize prostate cancer (PCa) based on multiparametric MR (mpMR) measures derived from MRI, diffusion, spectroscopy, and dynamic contrast-enhanced (DCE) MRI, and to validate mpMRI in detecting PCa and predicting PCa aggressiveness by correlating mpMRI findings with whole-mount histopathology. Seventy-eight men with untreated PCa received 3 T mpMR scans prior to radical prostatectomy. Cancerous regions were outlined, graded, and cancer amount estimated on whole-mount histology. Regions of interest were manually drawn on T2 -weighted images based on histopathology. Logistic regression was used to identify optimal combinations of parameters for the peripheral zone and transition zone to separate: (i) benign from malignant tissues; (ii) Gleason score (GS) ≤3 + 3 disease from ≥GS3 + 4; and (iii) ≤ GS3 + 4 from ≥GS4 + 3 cancers. The performance of the models was assessed using repeated fourfold cross-validation. Additionally, the performance of the logistic regression models created under the assumption that one or more modality has not been acquired was evaluated. Logistic regression models yielded areas under the curve (AUCs) of 1.0 and 0.99 when separating benign from malignant tissues in the peripheral zone and the transition zone, respectively. Within the peripheral zone, combining choline, maximal enhancement slope, apparent diffusion coefficient (ADC), and citrate measures for separating ≤GS3 + 3 from ≥GS3 + 4 PCa yielded AUC = 0.84. Combining creatine, choline, and washout slope yielded AUC = 0.81 for discriminating ≤GS3 + 4 from ≥GS4 + 3 disease. Within the transition zone, combining washout slope, ADC, and creatine yielded AUC = 0.93 for discriminating ≤GS3 + 3 and ≥GS3 + 4 cancers. When separating ≤GS3 + 4 from ≥GS4 + 3 PCa, combining choline and washout slope yielded AUC = 0.92. MpMRI provides excellent separation between benign tissues and PCa, and across PCa tissues of different aggressiveness. The final models prominently feature spectroscopy and DCE-derived metrics, underlining their value within a comprehensive mpMRI examination.

Semiautomatic registration of digital histopathology images to in vivo MR images in molded and unmolded prostates.

PURPOSE: To evaluate a semiautomatic software-based method of registering in vivo prostate MR images to digital histopathology images using two approaches: (i) in which the prostates were molded to simulate distortion due to the endorectal imaging coil before fixation, and (ii) in which the prostates were not molded. MATERIALS AND METHODS: T2-weighted MR images and digitized whole-mount histopathology images were acquired for 26 patients with biopsy-confirmed prostate cancer who underwent radical prostatectomy. Ten excised prostates were molded before fixation. A semiautomatic method was used to align MR images to histopathology. Percent overlap between MR and histopathology images, as well as distances between corresponding anatomical landmarks were calculated and used to evaluate the registration technique for molded and unmolded cases. RESULTS: The software successfully morphed histology-based prostate images into corresponding MR images. Percent overlap improved from 80.4 ± 5.8% before morphing to 99.7 ± 0.62% post morphing. Molded prostates had a smaller distance between landmarks (1.91 ± 0.75 mm) versus unmolded (2.34 ± 0.68 mm), P < 0.08. CONCLUSION: Molding a prostate before fixation provided a better alignment of internal structures within the prostate, but this did not reach statistical significance. Software-based morphing allowed for nearly complete overlap between the pathology slides and the MR images.

A model for the design and construction of a resource for the validation of prognostic prostate cancer biomarkers: the Canary Prostate Cancer Tissue Microarray.

Tissue microarrays (TMAs) provide unique resources for rapid evaluation and validation of tissue biomarkers. The Canary Foundation Retrospective Prostate Tissue Microarray Resource used a rigorous statistical design, quota sampling, a variation of the case-cohort study, to select patients for inclusion in a multicenter, retrospective prostate cancer TMA cohort. The study is designed to definitively validate tissue biomarkers of prostate cancer recurrence after radical prostatectomy. Tissue samples from over 1000 participants treated for prostate cancer with radical prostatectomy between 1995 and 2004 were selected at 6 participating institutions in the United States and Canada. This design captured the heterogeneity of screening and clinical practices in the contemporary North American population. Standardized clinical data were collected in a centralized database. The project has been informative in several respects. The scale and complexity of assembling TMAs with over 200 cases at each of 6 sites involved unanticipated levels of effort and time. Our statistical design promises to provide a model for outcome-based studies where tissue localization methods are applied to high-density TMAs.

Measurements of T(1) -relaxation in ex vivo prostate tissue at 132 µT.

The proton T(1) was measured at 132 µT in ex vivo prostate tissue specimens from radical prostatectomies of 35 patients with prostate cancer. Each patient provided two specimens. The NMR and MRI measurements involved proton repolarization, a field of typically 150 mT and detection of the 5.6-kHz signal with a superconducting quantum interference device. Values of T(1) varied from 41 to 86 ms. Subsequently, the percentages of tissue types were determined histologically. The theoretical image contrast is quantified for each case by δ = [1 - T(1) (more cancer)/T(1) (less cancer)]. A linear fit of δ versus difference in percentage cancer yields T(1) (100% cancer)/T(1) (0% cancer) = 0.70 ± 0.05 with correlation coefficient R(2) = 0.30. Two-dimensional T(1) maps for four specimens demonstrate variation within a single specimen. These results suggest that MR images with T(1) contrast established at ultra-low fields may discriminate prostate cancer from normal prostate tissue in vivo without a contrast agent.

Driver mutations among never smoking female lung cancer tissues in China identify unique EGFR and KRAS mutation pattern associated with household coal burning.

Lung cancer in never smokers, which has been partially attributed to household solid fuel use (i.e., coal), is etiologically and clinically different from lung cancer attributed to tobacco smoking. To explore the spectrum of driver mutations among lung cancer tissues from never smokers, specifically in a population where high lung cancer rates have been attributed to indoor air pollution from domestic coal use, multiplexed assays were used to detect >40 point mutations, insertions, and deletions (EGFR, KRAS, BRAF, HER2, NRAS, PIK3CA, MEK1, AKT1, and PTEN) among the lung tumors of confirmed never smoking females from Xuanwei, China [32 adenocarcinomas (ADCs), 7 squamous cell carcinomas (SCCs), 1 adenosquamous carcinoma (ADSC)]. EGFR mutations were detected in 35% of tumors. 46% of these involved EGFR exon 18 G719X, while 14% were exon 21 L858R mutations. KRAS mutations, all of which were G12C_34G>T, were observed in 15% of tumors. EGFR and KRAS mutations were mutually exclusive, and no mutations were observed in the other tested genes. Most point mutations were transversions and were also found in tumors from patients who used coal in their homes. Our high mutation frequencies in EGFR exon 18 and KRAS and low mutation frequency in EGFR exon 21 are strikingly divergent from those in other smoking and never smoking populations from Asia. Given that our subjects live in a region where coal is typically burned indoors, our findings provide new insights into the pathogenesis of lung cancer among never smoking females exposed to indoor air pollution from coal.

Regional cell proliferation in microdissected human prostate specimens after heavy water labeling in vivo: correlation with prostate epithelial cells isolated from seminal fluid.

PURPOSE: Prostate cancer is detected with increasing frequency but has a highly variable natural history and prognosis and active surveillance of men with low-risk prostate cancer would benefit greatly from minimally invasive methods to identify progression. We describe here two novel in vivo metrics of cell proliferation in men with prostate neoplasia. EXPERIMENTAL DESIGN: Three groups of men drank heavy water, a nonradioactive, stable isotopic tracer for 14 to 28 days: (i) healthy men, (ii) men scheduled for transrectal core needle biopsy, and (iii) men scheduled for radical prostatectomy. Prostate epithelial cells (PEC) were isolated from ejaculated seminal fluid in all subjects. Histologically graded lesions were microdissected from tissue slides obtained from subjects undergoing surgery and proliferation rates were measured from isolated cells via mass spectrometry. RESULTS: Proliferation rates of seminal PEC in healthy men (0.10%-0.27%/d) were stable on repeat sampling. Rates above 0.34%/d were seen only in patients with cancer where rates increased progressively from normal tissue through benign prostate hyperplasia, prostate intraepithelial neoplasia, and tumor grades III and IV in all subjects. Seminal PEC kinetics correlated highly with the most proliferative microdissected region in each subject (r(2) = 0.94). CONCLUSIONS: Prostate cell proliferation can be measured in vivo from microdissected histopathology sections or noninvasively from seminal fluid where the latter reflects the most proliferative region of the gland. This approach may allow monitoring of progression in men with low-risk prostate cancer.