Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions.

Purpose: Two-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions. Experimental Design: 2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs. Results: Integrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 ± 6.1% sensitivity and 72.3 ± 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 ± 12.0%) and specificity (77.5 ± 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-µm from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers. Conclusion: Label-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers.

Restoration of metabolic functional metrics from label-free, two-photon human tissue images using multiscale deep-learning-based denoising algorithms.

Significance: Label-free, two-photon excited fluorescence (TPEF) imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, noise and other artifacts present in these images severely complicate the extraction of biologically useful information. Aim: We aim to employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-signal-to-noise ratio (SNR), TPEF images. Approach: TPEF images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used to assess the impact of various denoising models, preprocessing methods, and data on metrics of image quality and the recovery of six metrics of metabolic function from the images relative to ground truth images. Results: Optimized recovery of the redox ratio and mitochondrial organization is achieved using a novel algorithm based on deep denoising in the wavelet transform domain. This algorithm also leads to significant improvements in peak-SNR (PSNR) and structural similarity index measure (SSIM) for all images. Interestingly, other models yield even higher PSNR and SSIM improvements, but they are not optimal for recovery of metabolic function metrics. Conclusions: Denoising algorithms can recover diagnostically useful information from low SNR label-free TPEF images and will be useful for the clinical translation of such imaging.

Restoration of metabolic functional metrics from label-free, two-photon cervical tissue images using multiscale deep-learning-based denoising algorithms.

Label-free, two-photon imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, this modality suffers from low signal arising from limitations imposed by the maximum permissible dose of illumination and the need for rapid image acquisition to avoid motion artifacts. Recently, deep learning methods have been developed to facilitate the extraction of quantitative information from such images. Here, we employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-SNR, two-photon images. Two-photon excited fluorescence (TPEF) images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used. We assess the impact of the specific denoising model, loss function, data transformation, and training dataset on established metrics of image restoration when comparing denoised single frame images with corresponding six frame averages, considered as the ground truth. We further assess the restoration accuracy of six metrics of metabolic function from the denoised images relative to ground truth images. Using a novel algorithm based on deep denoising in the wavelet transform domain, we demonstrate optimal recovery of metabolic function metrics. Our results highlight the promise of denoising algorithms to recover diagnostically useful information from low SNR label-free two-photon images and their potential importance in the clinical translation of such imaging.

Gland context networks: A novel approach for improving prostate cancer identification.

Prostate cancer (PCa) is a pervasive condition that is manifested in a wide range of histologic patterns in biopsy samples. Given the importance of identifying abnormal prostate tissue to improve prognosis, many computerized methodologies aimed at assisting pathologists in diagnosis have been developed. It is often argued that improved diagnosis of a tissue region can be obtained by considering measurements that can take into account several properties of its surroundings, therefore providing a more robust context for the analysis. Here we propose a novel methodology that can be used for systematically defining contextual features regarding prostate glands. This is done by defining a Gland Context Network (GCN), a representation of the prostate sample containing information about the spatial relationship between glands as well as the similarity between their appearance. We show that such a network can be used for establishing contextual features at any spatial scale, therefore providing information that is not easily obtained from traditional shape and textural features. Furthermore, it is shown that even basic features derived from a GCN can lead to state-of-the-art classification performance regarding PCa. All in all, GCNs can assist in defining more effective approaches for PCa grading.

Empirical ordering of stains in cytology-are we saving or losing?

INTRODUCTION: Bronchoalveolar lavage (BAL) and body cavity fluids (pleural and peritoneal) have a useful role in the detection of infectious diseases, especially when combined with ancillary stains (Grocott methenamine silver, acid-fast bacilli, Fite, and cytomegalovirus). However, empirical ordering of stains and duplicate testing by concurrent microbiology cultures leads to unnecessary wastage of resources. The aim of our study was to optimize the use of resources. MATERIALS AND METHODS: We performed a retrospective review of all BALs and body cavity fluids from 2016 to 2018 to determine the baseline stain order rate, which was then used in conjunction with clinical information to create a reasonable target for 2019. The methods implemented included communication with the clinical team to modify current ordering practice, monitoring stain orders prospectively through 2019, and updating the cytology requisition form to limit upfront ordering of ancillary stains. RESULTS: From 2016 to 2018, of the 1270 specimens reviewed, 323 (55%) were BALs and 108 (16%) were body cavity fluids that had had ≥2 stains preordered. This was reduced by the end of 2019 to 10% of BALs and 3.4% of body cavity fluids, leading to $25,935.24 in costs savings (including 275 hours of technician time and 39.3 hours of pathologist time). CONCLUSIONS: We found that ancillary microorganism stains have limited utility in cytology specimens and should only be ordered when indicated after a review of the initial smears. In today's era of cost savings, upfront ordering of ancillary stains can lead to significant wastage of resources that can be prevented by improving workflow.

Diagnosis of "cribriform" prostatic adenocarcinoma: an interobserver reproducibility study among urologic pathologists with recommendations.

Accurate diagnosis of cribriform Gleason pattern 4 (CrP4) prostate adenocarcinoma (PCa) is important due to its independent association with adverse clinical outcomes and as a growing body of evidence suggests that it impacts clinical decision making in PCa management. To identify reproducible features for diagnosis of CrP4, we assessed interobserver agreement among 27 experienced urologic pathologists of 60 digital images from 44 radical prostatectomies (RP) that represented a broad spectrum of potential CrP4. The following morphologic features were correlated with the consensus diagnosis (defined as 75% agreement) for each image: partial vs. transluminal glandular bridging, intraglandular stroma, <12 vs. ≥12 lumina, well vs. poorly formed lumina, mucin (mucinous fibroplasia, extravasation, or extracellular pool), size (compared to benign glands and number of lumina), number of attachments with gland border by tumor cells forming a "glomeruloid-like" pattern, a clear luminal space along the periphery of gland occupying <50% of glandular circumference, central nerve, dense (cell mass occupying >50% of luminal space) vs. loose, and regular vs. irregular contour. Interobserver reproducibility for the overall diagnostic agreement was fair (k=0.40). Large CrP4 had better agreement (k=0.49) compared to small CrP4 (k=0.40). Transluminal bridging, dense cellular proliferation, a clear luminal space along the periphery of gland occupying <50% of gland circumference, lack of intraglandular mucin, and lack of contact between the majority of intraglandular cells with stroma were significantly associated with consensus for CrP4. In contrast, partial bridging, majority of intraglandular cells in contact with stroma, mucinous fibroplasia, only one attachment to the gland border by tumor cells forming a "glomeruloid-like" pattern, and a clear luminal space along the periphery of gland accounting for >50% of the glandular circumference were associated with consensus against CrP4. In summary, we identified reproducible morphological features for and against CrP4 diagnosis, which could be used to refine and standardize the diagnostic criteria for CrP4.

High-grade Urothelial Carcinoma with Malignant Melanocytic Differentiation.

Urothelial carcinoma usually shows divergent differentiation and variant histology with squamous and glandular morphology being most common. In this report, we present a case of divergent malignant melanocytic differentiation in a high-grade urothelial carcinoma. A 98-year-old East Asian woman with an anterior bladder wall mass underwent resection, which revealed a high-grade poorly differentiated tumor. A minor component of high-grade papillary urothelial carcinoma and carcinoma in situ is also present. The majority of the tumor cells are morphologically and immunohistochemically consistent with melanoma, a minority of cells are positive for urothelial markers, and rare cells coexpress both melanocytic and urothelial markers. Cells that express melanocytic markers or urothelial markers are intimately admixed together. Taken together, a diagnosis of high-grade urothelial carcinoma with malignant melanocytic differentiation was rendered. This is the first report in the literature of malignant melanocytic differentiation in a high-grade urothelial carcinoma, a finding that may have important diagnostic and therapeutic implications.

Label-free, High-Resolution Optical Metabolic Imaging of Human Cervical Precancers Reveals Potential for Intraepithelial Neoplasia Diagnosis.

While metabolic changes are considered a cancer hallmark, their assessment has not been incorporated in the detection of early or precancers, when treatment is most effective. Here, we demonstrate that metabolic changes are detected in freshly excised human cervical precancerous tissues using label-free, non-destructive imaging of the entire epithelium. The images rely on two-photon excited fluorescence from two metabolic co-enzymes, NAD(P)H and FAD, and have micron-level resolution, enabling sensitive assessments of the redox ratio and mitochondrial fragmentation, which yield metrics of metabolic function and heterogeneity. Simultaneous characterization of morphological features, such as the depth-dependent variation of the nuclear:cytoplasmic ratio, is demonstrated. Multi-parametric analysis combining several metabolic metrics with morphological ones enhances significantly the diagnostic accuracy of identifying high-grade squamous intraepithelial lesions. Our results motivate the translation of such functional metabolic imaging to in vivo studies, which may enable improved identification of cervical lesions, and other precancers, at the bedside.

Two-photon images reveal unique texture features for label-free identification of ovarian cancer peritoneal metastases.

For cancer patients, treatment selection fundamentally relies on staging, with "under-staging" considered a common problem. Imaging modalities that can complement conventional white-light laparoscopy are needed to detect more accurately small metastatic lesions in patients undergoing operative cancer care. Biopsies from healthy parietal peritoneum and ovarian peritoneal metastases obtained from 8 patients were imaged employing a two-photon laser scanning microscope to generate collagen-second harmonic generation (SHG) and fluorescence images at 755 nm and 900 nm excitation and 460 ± 20 nm and 525 ± 25 nm emission. Forty-one images were analyzed by automated image processing algorithms and statistical textural analysis techniques, namely gray level co-occurrence matrices. Two textural features (contrast and correlation) were employed to describe the spatial intensity variations within the captured images and outcomes were used for discriminant analysis. We found that healthy tissues displayed large variations in contrast and correlation features as a function of distance, corresponding to repetitive, increased local intensity fluctuations. Metastatic tissue images exhibited decreased contrast and correlation related values, representing more uniform intensity patterns and smaller fibers, indicating the destruction of the healthy stroma by the cancerous infiltration. The textural outcomes resulted in high classification accuracy as evaluated quantitatively by discriminant analysis.

The significance of histologic examination of gastrectomy specimens: a clinicopathologic study of 511 cases.

BACKGROUND: Sleeve gastrectomy (SG) is quickly becoming the preferred procedure for bariatric surgery. According to the American Society for Metabolic and Bariatric Surgery guidelines, routine preoperative upper gastrointestinal endoscopies are not recommended universally for bariatric surgery. Some studies have shown that the histologic examination of SG specimens is insignificant and not a cost-effective practice. However, some speculate SG examination may unveil pertinent findings and prevent further progression of precursor lesions. OBJECTIVES: This study aims to explore the clinically significant or actionable lesions that can be revealed with SG examination. SETTING: Tufts Medical Center, Boston, USA. RESULTS: We analyzed 511 SG specimens obtained during bariatric surgery. Incidental findings were grouped in 2 categories: clinically significant/actionable and minor lesions. The clinically significant lesions accounted for 5.8%. This category included 5 cases of gastrointestinal stromal tumor; one case of MALT lymphoma; 4 cases of autoimmune gastritis with concomitant pancreatic metaplasia or neuroendocrine dysplasia. Intestinal metaplasia without dysplasia was identified in 3 cases; 14 cases of Helicobacter pylori associated active gastritis; 1 case of iron pill induced gastritis and 1 case of gastric glandular siderosis. The minor lesions accounted for 6.3%, showing findings other than chronic gastritis. This category included 19 cases of fundic polyps and 1 case of hyperplastic polyp; one case of leiomyoma; 11 cases of H pylori negative active gastritis. CONCLUSIONS: The majority of histopathology results after SG showed no significant changes. However, a few cases had clinically significant lesions in seemingly healthy patients, altering patient's postoperative management.

Gleason Misclassification Rate Is Independent of Number of Biopsy Cores in Systematic Biopsy.

OBJECTIVE: To compare the utility of saturation core biopsy and 12-core biopsy in detecting true Gleason grades, using final pathology in prostatectomy specimens as outcome measures, with a particular interest in Gleason upgrading. PATIENTS AND METHODS: We compared the concordance rates of Gleason grades diagnosed on biopsies and prostatectomy specimens in 375 consecutive patients, including 106 saturation biopsies (18-33 cores, median = 20 cores) and 269 12-core biopsies. Grading bias was addressed by a central rereview of all cases that had discordance in reporting high Gleason grades (Gleason grade ≥ 4) on biopsies and prostatectomy specimens. RESULTS: For patients with high Gleason grades on final pathology, saturation and 12-core biopsy schemes had a comparable sensitivity, specificity, negative and positive predictive values (72.5% vs 69.5%, 91.9% vs 97.6%, 64.2% vs 58.4%, and 94.3% vs 98.5%, respectively) in detecting high Gleason grades. On multivariate analysis, prebiopsy serum prostate-specific antigen and clinical T stage independently predicted Gleason upgrading; saturation biopsy was not a significant predictor. Approximately one-third of cases where high Gleason grade was not present in the biopsy were attributed to the confinement of high-grade tumors to unusual anatomic locations such as anterior lobes, apex, bladder neck, and parasagittal zones. CONCLUSION: Our study showed that Gleason misclassification rate is independent of the number of biopsy cores in systematic biopsy. One of the reasons for missing high Gleason grade tumors on systematic biopsy was unusual tumor location outside of the biopsy grid, supporting the need for improved detection technique such as magnetic resonance imaging-guided targeted biopsies.

Differential Expression of PD-L1 between Primary and Metastatic Sites in Clear-Cell Renal Cell Carcinoma.

PD-L1 expression in primary clear-cell renal cell carcinoma (ccRCC) increases the likelihood of response to anti-PD-1 inhibition, but fails to identify all responders. We hypothesized that PD-L1 levels assessed in randomly selected areas of the primary tumors may not accurately reflect expression levels in metastatic lesions, which are the target of systemic therapy. Therefore, we compared PD-L1 expression in a series of primary ccRCC and their metastases. Tissue blocks from 53 primary ccRCCs and 76 corresponding metastases were retrieved. Areas with predominant and highest nuclear grade were selected. Slides were immunostained with a validated anti-PD-L1 antibody (405.9A11). Membranous expression in tumor cells was quantified using H-score. Expression in tumor-infiltrating mononuclear cells (TIMC) was quantified using a combined score. Discordant tumor cell PD-L1 staining between primary tumors and metastases was observed in 11 of 53 cases (20.8%). Overall, tumor cell PD-L1 levels were not different in primary tumors and metastases (P = 0.51). Tumor cell PD-L1 positivity was associated with higher T stage (P = 0.03) and higher Fuhrman nuclear grade (P < 0.01). Within individual lesions, PD-L1 positivity was heterogeneous and almost exclusively detected in high nuclear grade areas (P < 0.001). No difference was found in PD-L1 levels in TIMCs between primary tumors and metastases (P = 0.82). The heterogeneity of PD-L1 expression in ccRCC suggests that its assessment as a predictive biomarker for PD-1 blockade may require analysis of metastatic lesions. Notably, because PD-L1 expression was mostly detected in high nuclear grade areas, to avoid false-negative results, these areas should be specifically selected for assessment.

Sentinel Lymph Node Mapping of Liver.

BACKGROUND: Although the sentinel lymph node (SLN) hypothesis has been applied to many tissues and organs, liver has remained unstudied. Currently, it is unclear whether hepatic SLNs even exist. If so, they could alter the management of intrahepatic cholangiocarcinoma and other hepatic malignancies by minimizing the extent of surgery while still providing precise nodal staging. This study investigated whether invisible yet tissue-penetrating near-infrared (NIR) fluorescent light can provide simultaneous identification of both the SLN and all other regional lymph nodes (RLNs) in the liver. METHODS: In 25 Yorkshire pigs, this study determined whether SLNs exist in liver and compared the effectiveness of two clinically available NIR fluorophores [methylene blue and indocyanine green (ICG)], and two novel NIR fluorophores previously described by our group (ESNF14 and ZW800-3C) for SLN and RLN mapping. RESULTS: In this study, ESNF14 showed the highest signal-to-background ratio and the longest retention time in SLNs without leakage to second-tier lymph nodes. The findings showed that ICG had apparent leakage to second-tier nodes, and ZW800-3C had poor migration after intraparenchymal injection. However, when injected intravenously, ZW800-3C was able to highlight all RLNs in liver during a 4- to 6-h period. Simultaneous dual-channel imaging of SLN (ESNF14) and RLN (ZW800-3C) permitted unambiguous identification and image-guided resection of SLNs and RLNs in liver. CONCLUSION: The NIR imaging technology enables real-time intraoperative identification of SLNs and RLNs in the liver of swine. If these results are confirmed in patients, new strategies for the surgical management of intrahepatic malignancies should be possible.

Update for the practicing pathologist: The International Consultation On Urologic Disease-European association of urology consultation on bladder cancer.

The International Consultations on Urological Diseases are international consensus meetings, supported by the World Health Organization and the Union Internationale Contre le Cancer, which have occurred since 1981. Each consultation has the goal of convening experts to review data and provide evidence-based recommendations to improve practice. In 2012, the selected subject was bladder cancer, a disease which remains a major public health problem with little improvement in many years. The proceedings of the 2nd International Consultation on Bladder Cancer, which included a 'Pathology of Bladder Cancer Work Group,' have recently been published; herein, we provide a summary of developments and consensus relevant to the practicing pathologist. Although the published proceedings have tackled a comprehensive set of issues regarding the pathology of bladder cancer, this update summarizes the recommendations regarding selected issues for the practicing pathologist. These include guidelines for classification and grading of urothelial neoplasia, with particular emphasis on the approach to inverted lesions, the handling of incipient papillary lesions frequently seen during surveillance of bladder cancer patients, descriptions of newer variants, and terminology for urine cytology reporting.

Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors.

PURPOSE: To identify computer-extracted features for central gland and peripheral zone prostate cancer localization on multiparametric magnetic resonance imaging (MRI). MATERIALS AND METHODS: Preoperative T2-weighted (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI were acquired from 23 men with confirmed prostate cancer. Following radical prostatectomy, the cancer extent was delineated by a pathologist on ex vivo histology and mapped to MRI by nonlinear registration of histology and corresponding MRI slices. In all, 244 computer-extracted features were extracted from MRI, and principal component analysis (PCA) was employed to reduce the data dimensionality so that a generalizable classifier could be constructed. A novel variable importance on projection (VIP) measure for PCA (PCA-VIP) was leveraged to identify computer-extracted MRI features that discriminate between cancer and normal prostate, and these features were used to construct classifiers for cancer localization. RESULTS: Classifiers using features selected by PCA-VIP yielded an area under the curve (AUC) of 0.79 and 0.85 for peripheral zone and central gland tumors, respectively. For tumor localization in the central gland, T2w, DCE, and DWI MRI features contributed 71.6%, 18.1%, and 10.2%, respectively; for peripheral zone tumors T2w, DCE, and DWI MRI contributed 29.6%, 21.7%, and 48.7%, respectively. CONCLUSION: PCA-VIP identified relatively stable subsets of MRI features that performed well in localizing prostate cancer on MRI.

Prostatome: a combined anatomical and disease based MRI atlas of the prostate.

PURPOSE: In this work, the authors introduce a novel framework, the anatomically constrained registration (AnCoR) scheme and apply it to create a fused anatomic-disease atlas of the prostate which the authors refer to as the prostatome. The prostatome combines a MRI based anatomic and a histology based disease atlas. Statistical imaging atlases allow for the integration of information across multiple scales and imaging modalities into a single canonical representation, in turn enabling a fused anatomical-disease representation which may facilitate the characterization of disease appearance relative to anatomic structures. While statistical atlases have been extensively developed and studied for the brain, approaches that have attempted to combine pathology and imaging data for study of prostate pathology are not extant. This works seeks to address this gap. METHODS: The AnCoR framework optimizes a scoring function composed of two surface (prostate and central gland) misalignment measures and one intensity-based similarity term. This ensures the correct mapping of anatomic regions into the atlas, even when regional MRI intensities are inconsistent or highly variable between subjects. The framework allows for creation of an anatomic imaging and a disease atlas, while enabling their fusion into the anatomic imaging-disease atlas. The atlas presented here was constructed using 83 subjects with biopsy confirmed cancer who had pre-operative MRI (collected at two institutions) followed by radical prostatectomy. The imaging atlas results from mapping thein vivo MRI into the canonical space, while the anatomic regions serve as domain constraints. Elastic co-registration MRI and corresponding ex vivo histology provides "ground truth" mapping of cancer extent on in vivo imaging for 23 subjects. RESULTS: AnCoR was evaluated relative to alternative construction strategies that use either MRI intensities or the prostate surface alone for registration. The AnCoR framework yielded a central gland Dice similarity coefficient (DSC) of 90%, and prostate DSC of 88%, while the misalignment of the urethra and verumontanum was found to be 3.45 mm, and 4.73 mm, respectively, which were measured to be significantly smaller compared to the alternative strategies. As might have been anticipated from our limited cohort of biopsy confirmed cancers, the disease atlas showed that most of the tumor extent was limited to the peripheral zone. Moreover, central gland tumors were typically larger in size, possibly because they are only discernible at a much later stage. CONCLUSIONS: The authors presented the AnCoR framework to explicitly model anatomic constraints for the construction of a fused anatomic imaging-disease atlas. The framework was applied to constructing a preliminary version of an anatomic-disease atlas of the prostate, the prostatome. The prostatome could facilitate the quantitative characterization of gland morphology and imaging features of prostate cancer. These techniques, may be applied on a large sample size data set to create a fully developed prostatome that could serve as a spatial prior for targeted biopsies by urologists. Additionally, the AnCoR framework could allow for incorporation of complementary imaging and molecular data, thereby enabling their careful correlation for population based radio-omics studies.

Tumor necrosis on magnetic resonance imaging correlates with aggressive histology and disease progression in clear cell renal cell carcinoma.

OBJECTIVE: The study objective was to correlate the magnetic resonance imaging (MRI) features of clear cell renal cell carcinoma (ccRCC) with the histopathologic features and disease progression. METHODS: Institutional review board approval for this retrospective study was obtained; patient consent was not required. The initial staging MRI scans of 75 patients with histologically confirmed ccRCC were retrospectively reviewed. The imaging was assessed by 2 radiologists for the presence of tumor necrosis, cystic degeneration, intracellular fat, hemorrhage, retroperitoneal collaterals, and renal vein thrombosis. Quantitative analysis for the MRI presence of intracellular lipid within tumors was performed. MRI findings were correlated with histopathologic findings of clear cell percentage, alveolar and tubular growth pattern, and disease progression. Statistical associations were evaluated with nonparametric univariable analyses and multivariable logistic regression models. RESULTS: Correlation between MRI and histopathologic features was performed in 75 patients, whereas follow-up data were available for progression analysis in 68 patients. The presence of tumor necrosis, retroperitoneal collaterals, and renal vein thrombosis on MRI was significantly associated with a low percentage of tumor cells with clear cytoplasm (P < .01) and metastatic disease at presentation or disease progression (P < .01). At multivariable analysis, necrosis remained the only feature statistically associated with disease progression (P = .03; adjusted odds ratio, 27.7; 95% confidence interval, 1.4-554.7 for reader 1 and P = .02; adjusted odds ratio, 29.3; 95% confidence interval, 1.7-520.8 for reader 2). CONCLUSIONS: Necrosis in ccRCC on MRI correlates with the histopathologic finding of lower percentage of tumor cells with clear cytoplasm and is a poor prognostic indicator irrespective of tumor size.

Diagnosis of relevant prostate cancer using supplementary cores from magnetic resonance imaging-prompted areas following multiple failed biopsies.

OBJECTIVES: To establish the value of MRI in targeting re-biopsy for undiagnosed prostate cancer despite multiple negative biopsies and determine clinical relevance of detected tumors. MATERIALS AND METHODS: Thirty-eight patients who underwent MRI after 2 or more negative biopsies due to continued clinical suspicion and later underwent TRUS-guided biopsy supplemented by biopsy of suspicious areas depicted by MRI were identified. Diagnostic performance of endorectal 3T MRI in diagnosing missed cancer foci was assessed using biopsy results as the standard of reference. Ratio of positive biopsies using systematic versus MRI-prompted approaches was compared. Gleason scores of detected cancers were used as surrogate for clinical relevance. RESULTS: Thirty-four percent of patients who underwent MRI before re-biopsy had prostate cancer on subsequent biopsy. The positive biopsy yield with systematic sampling was 23% versus 92% with MRI-prompted biopsies(p<0.0001). Seventy-seven percent of tumors were detected exclusively in the MRI-prompted zones. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of MRI to provide a positive biopsy were 92%, 60%, 55%, 94% and 71%, respectively. The anterior gland and apical regions contained most tumors; 75% of cancers detected by MRI-prompted biopsy had Gleason score≥7. CONCLUSIONS: Clinically relevant tumors missed by multiple TRUS-guided biopsies can be detected by a MRI-prompted approach.