185 research outputs found
Intraductal carcinoma of the prostate: a critical re-appraisal
Intraductal carcinoma of the prostate gland (IDCP), which is now categorised as a distinct entity by WHO 2016, includes two biologically distinct diseases. IDCP associated with invasive carcinoma (IDCP-inv) generally represents a growth pattern of invasive prostatic adenocarcinoma while the rarely encountered pure IDCP is a precursor of prostate cancer. This review highlights issues that require further discussion and clarification. The diagnostic criterion ânuclear size at least 6 times normalâ is ambiguous as âsizeâ could refer to either nuclear area or diameter. If area, then this criterion could be re-defined as nuclear diameter at least three times normal as it is difficult to visually compare area of nuclei. It is also unclear whether IDCP could also include tumours with ductal morphology. There is no consensus whether pure IDCP in needle biopsies should be managed with re-biopsy or radical therapy. A pragmatic approach would be to recommend radical therapy only for extensive pure IDCP that is morphologically unequivocal for high-grade prostate cancer. Active surveillance is not appropriate when low-grade invasive cancer is associated with IDCP, as such patients usually have unsampled high-grade prostatic adenocarcinoma. It is generally recommended that IDCP component of IDCP-inv should be included in tumour extent but not grade. However, there are good arguments in favour of grading IDCP associated with invasive cancer. All historical as well as contemporary Gleason outcome data are based on morphology and would have included an associated IDCP component in the tumour grade. WHO 2016 recommends that IDCP should not be graded, but it is unclear whether this applies to both pure IDCP and IDCP-inv
Biomarkers in renal cancer
Treatment options for primary and metastatic renal cancer are increasing. Accurate data from the pathological examination of renal cancer specimens aid clinicians in stratifying patients for surveillance and adjuvant therapies. This review focuses on biomarkers in diagnosis, prognosis and prediction of the biologic behavior of renal tumors which should be recorded in pathology reports and which are under investigation. Special emphasis is given to the use of immunohistochemical markers in differential diagnosis of various renal tumor subtypes. The relevance of cytogenetic and molecular findings is also discussed. The review includes the 2012 International Society for Urological Pathology Consensus conference recommendations
Detection of perineural invasion in prostate needle biopsies with deep neural networks
The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97-0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen's kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.</p
Detection of perineural invasion in prostate needle biopsies with deep neural networks
The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97â0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohenâs kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.publishedVersionPeer reviewe
Molecular Genetic Evidence for the Independent Origin of Multifocal Papillary Tumors in Patients with Papillary Renal Cell Carcinomas
Abstract
Purpose: In patients with papillary renal cell carcinoma, it is not uncommon to find two or more anatomically distinct and histologically similar tumors at radical nephrectomy. Whether these multiple papillary lesions result from intrarenal metastasis or arise independently is unknown. Previous studies have shown that multifocal clear cell renal cell carcinomas express identical allelic loss and shift patterns in the different tumors within the same kidney, consistent with a clonal origin. However, similar clonality assays for multifocal papillary renal cell neoplasia have not been done. Molecular analysis of microsatellite and chromosome alterations and X-chromosome inactivation status in separate tumors in the same patient can be used to study the genetic relationships among the coexisting multiple tumors.
Experimental Design: We examined specimens from 21 patients who underwent radical nephrectomy for renal cell carcinoma. All patients had multiple separate papillary lesions (ranging from 2 to 5). Eighteen patients had multiple papillary renal cell carcinomas. Seven had one or more papillary renal cell carcinomas with coexisting papillary adenomas. Genomic DNA samples were prepared from formalin-fixed, paraffin-embedded tissue sections using laser-capture microdissection. Loss of heterozygosity assays were done for six microsatellite polymorphic markers for putative tumor suppressor genes on chromosomes 3p14 (D3S1285), 7q31 (D7S522), 9p21 (D9S171), 16q23 (D16S507), 17q21 (D17S1795), and 17p13 (TP53). X-chromosome inactivation analyses were done on the papillary kidney tumors from three female patients. Fluorescence in situ hybridization analysis was done on the tumors of selected patients showing allelic loss at loci on chromosome 7 and/or chromosome 17.
Results: Twenty of 21 (95%) cases showed allelic loss in one or more of the papillary lesions in at least one of the six polymorphic markers analyzed. A concordant allelic loss pattern between each coexisting kidney tumor was seen in only 1 of 21 (5%) cases. A concordant pattern of nonrandom X-chromosome inactivation in the coexisting multiple papillary lesions was seen in two of three female patients. A discordant pattern of X-chromosome inactivation was seen in the tumors of the other female patient. Fluorescence in situ hybridization showed that the majority of tumors analyzed had gains of chromosomes 7 and 17. Two patients had one tumor with chromosomal gain and another separate tumor that did not.
Conclusion: Our data suggest that, unlike multifocal clear cell renal cell carcinomas, the multiple tumors in patients with papillary renal cell carcinoma arise independently. Thus, intrarenal metastasis does not seem to play an important role in the spread of papillary renal cell carcinoma, a finding that has surgical, therapeutic, and prognostic implications
Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies
Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67-0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization
Validation of 34betaE12 immunoexpression in clear cell papillary renal cell carcinoma as a sensitive biomarker
Clear cell papillary renal cell carcinoma (CCPRCC) is a recently recognised neoplasm with a broad spectrum of morphological characteristics, thus representing a challenging differential diagnosis, especially with the low malignant potential multicystic renal cell neoplasms and clear cell renal cell carcinoma. We selected 14 cases of CCPRCC with a wide spectrum of morphological features diagnosed on morphology and CK7 immunoreactivity and analysed them using a panel of immunohistochemical markers, focusing on 34 beta E12 and related CKs 1,5,10 and 14 and several molecular analyses such as fluorescence in situ hybridisation (FISH), array comparative genomic hybridisation (aCGH), VHL methylation, VHL and TCEB1 sequencing and multiplex ligation-dependent probe amplification (MLPA). Twelve of 13 (92%) CCPRCC tumours were positive for 34 beta E12. One tumour without 3p alteration by FISH revealed VHL mutation and 3p deletion at aCGH; thus, it was re-classified as clear cell RCC. We concluded that: (1) immunohistochemical expression of CK7 is necessary for diagnostic purposes, but may not be sufficient to identify CCPRCC, while 34 beta E12, in part due to the presence of CK14 antigen expression, can be extremely useful for the recognition of this tumour; and (2) further molecular analysis of chromosome 3p should be considered to support of CCPRCC diagnosis, when FISH analysis does not evidence the common loss of chromosome 3p.Peer reviewe
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological diagnosis and grading of prostate biopsies as example. We digitized 7788 prostate biopsies from 1192 men in the STHLM3 diagnostic study, used for training, and 3059 biopsies from 676 men used for testing. With conformal prediction, 1 in 794 (0.1%) predictions is incorrect for cancer diagnosis (compared to 14 errors [2%] without conformal prediction) while 175 (22%) of the predictions are flagged as unreliable when the AI-system is presented with new data from the same lab and scanner that it was trained on. Conformal prediction could with small samples (N = 49 for external scanner, N = 10 for external lab and scanner, and N = 12 for external lab, scanner and pathology assessment) detect systematic differences in external data leading to worse predictive performance. The AI-system with conformal prediction commits 3 (2%) errors for cancer detection in cases of atypical prostate tissue compared to 44 (25%) without conformal prediction, while the system flags 143 (80%) unreliable predictions. We conclude that conformal prediction can increase patient safety of AI-systems.publishedVersionPeer reviewe
Gleason Grade 4 Prostate Adenocarcinoma Patterns: An Inter-observer Agreement Study among Genitourinary Pathologists
Aims
To assess the interobserver reproducibility of individual Gleason grade 4 growth patterns.
Methods and results
Twenty-three genitourinary pathologists participated in the evaluation of 60 selected high-magnification photographs. The selection included 10 cases of Gleason grade 3, 40 of Gleason grade 4 (10 per growth pattern), and 10 of Gleason grade 5. Participants were asked to select a single predominant Gleason grade per case (3, 4, or 5), and to indicate the predominant Gleason grade 4 growth pattern, if present. âConsensusâ was defined as at least 80% agreement, and âfavouredâ as 60â80% agreement. Consensus on Gleason grading was reached in 47 of 60 (78%) cases, 35 of which were assigned to grade 4. In the 13 non-consensus cases, ill-formed (6/13, 46%) and fused (7/13, 54%) patterns were involved in the disagreement. Among the 20 cases where at least one pathologist assigned the ill-formed growth pattern, none (0%, 0/20) reached consensus. Consensus for fused, cribriform and glomeruloid glands was reached in 2%, 23% and 38% of cases, respectively. In nine of 35 (26%) consensus Gleason grade 4 cases, participants disagreed on the growth pattern. Six of these were characterized by large epithelial proliferations with delicate intervening fibrovascular cores, which were alternatively given the designation fused or cribriform growth pattern (âcomplex fusedâ).
Conclusions
Consensus on Gleason grade 4 growth pattern was predominantly reached on cribriform and glomeruloid patterns, but rarely on ill-formed and fused glands. The complex fused glands seem to constitute a borderline pattern of unknown prognostic significance on which a consensus could not be reached
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