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1.
Mod Pathol ; 33(11): 2115-2127, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32572154

RESUMO

Remote digital pathology allows healthcare systems to maintain pathology operations during public health emergencies. Existing Clinical Laboratory Improvement Amendments regulations require pathologists to electronically verify patient reports from a certified facility. During the 2019 pandemic of COVID-19 disease, caused by the SAR-CoV-2 virus, this requirement potentially exposes pathologists, their colleagues, and household members to the risk of becoming infected. Relaxation of government enforcement of this regulation allows pathologists to review and report pathology specimens from a remote, non-CLIA certified facility. The availability of digital pathology systems can facilitate remote microscopic diagnosis, although formal comprehensive (case-based) validation of remote digital diagnosis has not been reported. All glass slides representing routine clinical signout workload in surgical pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on an Aperio GT450 at ×40 equivalent resolution (0.26 µm/pixel). Twelve pathologists from nine surgical pathology subspecialties remotely reviewed and reported complete pathology cases using a digital pathology system from a non-CLIA certified facility through a secure connection. Whole slide images were integrated to and launched within the laboratory information system to a custom vendor-agnostic, whole slide image viewer. Remote signouts utilized consumer-grade computers and monitors (monitor size, 13.3-42 in.; resolution, 1280 × 800-3840 × 2160 pixels) connecting to an institution clinical workstation via secure virtual private network. Pathologists subsequently reviewed all corresponding glass slides using a light microscope within the CLIA-certified department. Intraobserver concordance metrics included reporting elements of top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and ancillary testing. The median whole slide image file size was 1.3 GB; scan time/slide averaged 90 s; and scanned tissue area averaged 612 mm2. Signout sessions included a total of 108 cases, comprised of 254 individual parts and 1196 slides. Major diagnostic equivalency was 100% between digital and glass slide diagnoses; and overall concordance was 98.8% (251/254). This study reports validation of primary diagnostic review and reporting of complete pathology cases from a remote site during a public health emergency. Our experience shows high (100%) intraobserver digital to glass slide major diagnostic concordance when reporting from a remote site. This randomized, prospective study successfully validated remote use of a digital pathology system including operational feasibility supporting remote review and reporting of pathology specimens, and evaluation of remote access performance and usability for remote signout.


Assuntos
Infecções por Coronavirus , Pandemias , Patologia Cirúrgica , Pneumonia Viral , Telepatologia , Betacoronavirus , COVID-19 , Humanos , Processamento de Imagem Assistida por Computador/métodos , Patologia Cirúrgica/instrumentação , Patologia Cirúrgica/métodos , Patologia Cirúrgica/organização & administração , SARS-CoV-2 , Telepatologia/instrumentação , Telepatologia/métodos , Telepatologia/organização & administração , Fluxo de Trabalho
2.
Mod Pathol ; 32(7): 916-928, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30778169

RESUMO

Whole slide imaging is Food and Drug Administration-approved for primary diagnosis in the United States of America; however, relatively few pathology departments in the country have fully implemented an enterprise wide digital pathology system enabled for primary diagnosis. Digital pathology has significant potential to transform pathology practice with several published studies documenting some level of diagnostic equivalence between digital and conventional systems. However, whole slide imaging also has significant potential to disrupt pathology practice, due to the differences in efficiency of manipulating digital images vis-à-vis glass slides, and studies on the efficiency of actual digital pathology workload are lacking. Our randomized, equivalency and efficiency study aimed to replicate clinical workflow, comparing conventional microscopy to a complete digital pathology signout using whole slide images, evaluating the equivalency and efficiency of glass slide to whole slide image reporting, reflective of true pathology practice workloads in the clinical setting. All glass slides representing an entire day's routine clinical signout workload for six different anatomic pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on Leica Aperio AT2 at ×40 (0.25 µm/pixel). Integration of whole slide images for each accessioned case is through an interface between the Leica eSlide manager database and the laboratory information system, Cerner CoPathPlus. Pathologists utilized a standard institution computer workstation and viewed whole slide images through an internally developed, vendor agnostic whole slide image viewer, named the "MSK Slide Viewer". Subspecialized pathologists first reported on glass slides from surgical pathology cases using routine clinical workflow. Glass slides were de-identified, scanned, and re-accessioned in the laboratory information system test environment. After a washout period of 13 weeks, pathologists reported the same clinical workload using whole slide image integrated within the laboratory information system. Intraobserver equivalency metrics included top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and the need to order ancillary testing (i.e., recuts, immunohistochemistry). Turnaround time (efficiency) evaluation was defined by the start of each case when opened in the laboratory information system and when the case was completed for that day (i.e., case sent to signout queue or pending ancillary studies). Eight pathologists participated from the following subspecialties: bone and soft tissue, genitourinary, gastrointestinal, breast, gynecologic, and dermatopathology. Glass slides signouts comprised of 204 cases, encompassing 2091 glass slides; and digital signouts comprised of 199 cases, encompassing 2073 whole slide images. The median whole slide image file size was 1.54 GB; scan time/slide, 6 min 24 s; and scan area 32.1 × 18.52 mm. Overall diagnostic equivalency (e.g., top-line diagnosis) was 99.3% between digital and glass slide signout; however, signout using whole slide images showed a median overall 19% decrease in efficiency per case. No significant difference by reader, subspecialty, or specimen type was identified. Our experience is the most comprehensive study to date and shows high intraobserver whole slide image to glass slide equivalence in reporting of true clinical workflows and workloads. Efficiency needs to improve for digital pathology to gain more traction among pathologists.


Assuntos
Patologia Clínica/métodos , Patologia Cirúrgica/métodos , Telepatologia/métodos , Humanos , Processamento de Imagem Assistida por Computador , Microscopia/métodos , Reprodutibilidade dos Testes
3.
Nat Methods ; 11(4): 417-22, 2014 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-24584193

RESUMO

Mass cytometry enables high-dimensional, single-cell analysis of cell type and state. In mass cytometry, rare earth metals are used as reporters on antibodies. Analysis of metal abundances using the mass cytometer allows determination of marker expression in individual cells. Mass cytometry has previously been applied only to cell suspensions. To gain spatial information, we have coupled immunohistochemical and immunocytochemical methods with high-resolution laser ablation to CyTOF mass cytometry. This approach enables the simultaneous imaging of 32 proteins and protein modifications at subcellular resolution; with the availability of additional isotopes, measurement of over 100 markers will be possible. We applied imaging mass cytometry to human breast cancer samples, allowing delineation of cell subpopulations and cell-cell interactions and highlighting tumor heterogeneity. Imaging mass cytometry complements existing imaging approaches. It will enable basic studies of tissue heterogeneity and function and support the transition of medicine toward individualized molecularly targeted diagnosis and therapies.


Assuntos
Neoplasias da Mama/metabolismo , Citometria por Imagem/métodos , Proteínas de Neoplasias/metabolismo , Linhagem Celular , Células Epiteliais/citologia , Células Epiteliais/metabolismo , Feminino , Regulação Neoplásica da Expressão Gênica/fisiologia , Humanos , Proteínas de Neoplasias/genética
4.
Cytometry A ; 87(10): 936-42, 2015 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-26147066

RESUMO

The combination of mass cytometry and immunohistochemistry (IHC) enables new histopathological imaging methods in which dozens of proteins and protein modifications can be visualized simultaneously in a single tissue section. The power of multiplexing combined with spatial information and quantification was recently illustrated on breast cancer tissue and was described as next-generation IHC. Robust, accurate, and high-throughput cell segmentation is crucial for the analysis of this new generation of IHC data. To this end, we propose a watershed-based cell segmentation, which uses a nuclear marker and multiple membrane markers, the latter automatically selected based on their correlation. In comparison with the state-of-the-art segmentation pipelines, which are only using a single marker for object detection, we could show that the use of multiple markers can significantly increase the segmentation power, and thus, multiplexed information should be used and not ignored during the segmentation. Furthermore, we provide a novel, user-friendly open-source toolbox for the automatic segmentation of multiplexed histopathological images.


Assuntos
Neoplasias da Mama/diagnóstico , Diagnóstico por Imagem/métodos , Citometria de Fluxo/métodos , Análise de Célula Única , Neoplasias da Mama/patologia , Feminino , Humanos , Imuno-Histoquímica
5.
Comput Biol Med ; 173: 108306, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38554659

RESUMO

The incidence of colorectal cancer (CRC), one of the deadliest cancers around the world, is increasing. Tissue microenvironment (TME) features such as tumor-infiltrating lymphocytes (TILs) can have a crucial impact on diagnosis or decision-making for treating patients with CRC. While clinical studies showed that TILs improve the host immune response, leading to a better prognosis, inter-observer agreement for quantifying TILs is not perfect. Incorporating machine learning (ML) based applications in clinical routine may promote diagnosis reliability. Recently, ML has shown potential for making progress in routine clinical procedures. We aim to systematically review the TILs analysis based on ML in CRC histological images. Deep learning (DL) and non-DL techniques can aid pathologists in identifying TILs, and automated TILs are associated with patient outcomes. However, a large multi-institutional CRC dataset with a diverse and multi-ethnic population is necessary to generalize ML methods.


Assuntos
Neoplasias Colorretais , Linfócitos do Interstício Tumoral , Aprendizado de Máquina , Humanos , Neoplasias Colorretais/patologia , Neoplasias Colorretais/imunologia , Linfócitos do Interstício Tumoral/imunologia , Microambiente Tumoral/imunologia
6.
Pathologie (Heidelb) ; 45(2): 98-105, 2024 Mar.
Artigo em Alemão | MEDLINE | ID: mdl-38189845

RESUMO

The implementation of digital histopathology in the laboratory marks a crucial milestone in the overall digital transformation of pathology. This shift offers a range of new possibilities, including access to extensive datasets for AI-assisted analyses, the flexibility of remote work and home office arrangements for specialists, and the expedited and simplified sharing of images and data for research, conferences, and tumor boards. However, the transition to a fully digital workflow involves significant technological and personnel-related efforts. It necessitates careful and adaptable change management to minimize disruptions, particularly in the personnel domain, and to prevent the loss of valuable potential from employees who may be resistant to change. This article consolidates our institute's experiences, highlighting technical and personnel-related challenges encountered during the transition to digital pathology. It also presents a comprehensive overview of potential difficulties at various interfaces when converting routine operations to a digital workflow.


Assuntos
Laboratórios Clínicos , Patologia , Fluxo de Trabalho , Patologia/organização & administração , Laboratórios Clínicos/organização & administração
7.
Diagnostics (Basel) ; 13(14)2023 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-37510083

RESUMO

BACKGROUND: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers' estimations. METHODS: Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen's kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. To investigate the association between biomarkers and patient data, Pearson's correlation analysis was applied. RESULTS: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35-0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32-0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35-0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032-0.51), p-value = 0.03). CONCLUSIONS: The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements.

8.
Arch Pathol Lab Med ; 147(10): 1178-1185, 2023 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-36538386

RESUMO

CONTEXT.­: Prostate cancer diagnosis rests on accurate assessment of tissue by a pathologist. The application of artificial intelligence (AI) to digitized whole slide images (WSIs) can aid pathologists in cancer diagnosis, but robust, diverse evidence in a simulated clinical setting is lacking. OBJECTIVE.­: To compare the diagnostic accuracy of pathologists reading WSIs of prostatic biopsy specimens with and without AI assistance. DESIGN.­: Eighteen pathologists, 2 of whom were genitourinary subspecialists, evaluated 610 prostate needle core biopsy WSIs prepared at 218 institutions, with the option for deferral. Two evaluations were performed sequentially for each WSI: initially without assistance, and immediately thereafter aided by Paige Prostate (PaPr), a deep learning-based system that provides a WSI-level binary classification of suspicious for cancer or benign and pinpoints the location that has the greatest probability of harboring cancer on suspicious WSIs. Pathologists' changes in sensitivity and specificity between the assisted and unassisted modalities were assessed, together with the impact of PaPr output on the assisted reads. RESULTS.­: Using PaPr, pathologists improved their sensitivity and specificity across all histologic grades and tumor sizes. Accuracy gains on both benign and cancerous WSIs could be attributed to PaPr, which correctly classified 100% of the WSIs showing corrected diagnoses in the PaPr-assisted phase. CONCLUSIONS.­: This study demonstrates the effectiveness and safety of an AI tool for pathologists in simulated diagnostic practice, bridging the gap between computational pathology research and its clinical application, and resulted in the first US Food and Drug Administration authorization of an AI system in pathology.


Assuntos
Inteligência Artificial , Neoplasias da Próstata , Masculino , Humanos , Próstata/patologia , Interpretação de Imagem Assistida por Computador/métodos , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/patologia , Biópsia por Agulha
9.
Arch Pathol Lab Med ; 146(10): 1273-1280, 2022 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-34979569

RESUMO

CONTEXT.­: Wide adoption of digital pathology requires efficient visualization and navigation in Web-based digital slide viewers, which is poorly defined. OBJECTIVE.­: To define and quantify relevant performance metrics for efficient visualization of cases and slides in digital slide viewers. DESIGN.­: With a universal slide viewer used in clinical routine diagnostics, we evaluated the impact of slide caching, compression type, tile, and block size of whole slide images generated from Philips, Leica, and 3DHistech scanners on streaming performance on case, slide, and field of view levels. RESULTS.­: Two hundred thirty-nine pathologists routinely reviewed 60 080 whole slide images over 3 months. The median time to open a case's slides from the laboratory information system was less than 4 seconds, the time to change to a slide within the case was less than 1 second, and the time to render the adjacent field of view when navigating the slide was less than one-quarter of a second. A whole slide image's block size and a viewer tile size of 1024 pixels showed best performance to display a field of view and was preferrable over smaller tiles due to fewer mosaic effects. For Philips, fastest median slide streaming pace was 238 ms per field of view and for 3DHistech, 125 ms. For Leica, the fastest pace of 108 ms per field of view was established with block serving without decompression. CONCLUSIONS.­: This is the first study to systematically assess user-centric slide visualization performance metrics for digital viewers, including time to open a case, time to change a slide, and time to change a field of view. These metrics help to improve the viewer's configuration, leading to an efficient visualization baseline that is widely accepted among pathologists using routine digital pathology.


Assuntos
Sistemas de Informação em Laboratório Clínico , Telepatologia , Humanos , Internet , Software , Telepatologia/métodos
10.
Curr Oncol ; 29(10): 7245-7256, 2022 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-36290848

RESUMO

Prostate cancer represents one of the most common malignant tumors in male patients in Germany. The pathological reporting of radical prostatectomy specimens following a structured process constitutes an excellent prototype for the introduction of software-based standardized structured reporting in pathology. This can lead to reports of higher quality and could create a fundamental improvement for future AI applications. A software-based reporting template was used to generate standardized structured pathological reports of radical prostatectomy specimens of patients treated at the University Hospital Klinikum rechts der Isar of Technische Universität München, Germany. Narrative reports (NR) and standardized structured reports (SSR) were analyzed with regard to completeness, and clinicians' satisfaction with each report type was evaluated. SSR show considerably higher completeness than NR. A total of 10 categories out of 32 were significantly more complete in SSR than in NR (p < 0.05). Clinicians awarded overall high scores in NR and SSR reports. One rater acknowledged a significantly higher level of clarity and time saving when comparing SSR to NR. Our findings highlight that the standardized structured reporting of radical prostatectomy specimens, qualifying as level 5 reports, significantly increases objectively measured content quality and the level of completeness. The implementation of nationwide SSR in Germany, particularly in oncologic pathology, can serve pathologists, clinicians, and patients.


Assuntos
Comunicação Interdisciplinar , Prostatectomia , Humanos , Masculino , Relatório de Pesquisa , Eletrônica , Hospitais
11.
J Pathol Inform ; 12: 9, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34012713

RESUMO

BACKGROUND: The development of artificial intelligence (AI) in pathology frequently relies on digitally annotated whole slide images (WSI). The creation of these annotations - manually drawn by pathologists in digital slide viewers - is time consuming and expensive. At the same time, pathologists routinely annotate glass slides with a pen to outline cancerous regions, for example, for molecular assessment of the tissue. These pen annotations are currently considered artifacts and excluded from computational modeling. METHODS: We propose a novel method to segment and fill hand-drawn pen annotations and convert them into a digital format to make them accessible for computational models. Our method is implemented in Python as an open source, publicly available software tool. RESULTS: Our method is able to extract pen annotations from WSI and save them as annotation masks. On a data set of 319 WSI with pen markers, we validate our algorithm segmenting the annotations with an overall Dice metric of 0.942, Precision of 0.955, and Recall of 0.943. Processing all images takes 15 min in contrast to 5 h manual digital annotation time. Further, the approach is robust against text annotations. CONCLUSIONS: We envision that our method can take advantage of already pen-annotated slides in scenarios in which the annotations would be helpful for training computational models. We conclude that, considering the large archives of many pathology departments that are currently being digitized, our method will help to collect large numbers of training samples from those data.

12.
J Pathol Inform ; 12: 31, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34760328

RESUMO

BACKGROUND: Web-based digital slide viewers for pathology commonly use OpenSlide and OpenSeadragon (OSD) to access, visualize, and navigate whole-slide images (WSI). Their standard settings represent WSI as deep zoom images (DZI), a generic image pyramid structure that differs from the proprietary pyramid structure in the WSI files. The transformation from WSI to DZI is an additional, time-consuming step when rendering digital slides in the viewer, and inefficiency of digital slide viewers is a major criticism for digital pathology. AIMS: To increase efficiency of digital slide visualization by serving tiles directly from the native WSI pyramid, making the transformation from WSI to DZI obsolete. METHODS: We implemented a new flexible tile source for OSD that accepts arbitrary native pyramid structures instead of DZI levels. We measured its performance on a data set of 8104 WSI reviewed by 207 pathologists over 40 days in a web-based digital slide viewer used for routine diagnostics. RESULTS: The new FlexTileSource accelerates the display of a field of view in general by 67 ms and even by 117 ms if the block size of the WSI and the tile size of the viewer is increased to 1024 px. We provide the code of our open-source library freely on https://github.com/schuefflerlab/openseadragon. CONCLUSIONS: This is the first study to quantify visualization performance on a web-based slide viewer at scale, taking block size and tile size of digital slides into account. Quantifying performance will enable to compare and improve web-based viewers and therewith facilitate the adoption of digital pathology.

13.
J Am Med Inform Assoc ; 28(9): 1874-1884, 2021 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-34260720

RESUMO

OBJECTIVE: Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. MATERIALS AND METHODS: We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. RESULTS: The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. CONCLUSIONS: We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.


Assuntos
COVID-19 , Informática Médica/tendências , Neoplasias , Patologia Clínica , Centros Médicos Acadêmicos , Inteligência Artificial , COVID-19/diagnóstico , Humanos , Masculino , Neoplasias/diagnóstico , Pandemias , Patologia Clínica/tendências
14.
IEEE J Biomed Health Inform ; 25(2): 429-440, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33216724

RESUMO

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated using metrics using the precision, accuracy, sensitivity, specificity, and DICE coefficient (DC). The DC ranged from 0.7354 ±0.1149 to 0.8372 ±0.0858. The DC of the best method was close to the inter-observer agreement (0.8398 ±0.0890). All methods were based on deep learning and categorized into two groups: multi-model method and single model method. In general, multi-model methods were significantly better (p 0.01) than single model methods, with mean DC of 0.7966 and 0.7544, respectively. Deep learning based methods could potentially help pathologists find suspicious regions for further analysis of lung cancer in WSI.


Assuntos
Aprendizado Profundo , Neoplasias Pulmonares , Diagnóstico por Computador , Humanos , Neoplasias Pulmonares/diagnóstico por imagem
15.
BMC Cancer ; 9: 217, 2009 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-19570204

RESUMO

BACKGROUND: Secreted Wnt signaling antagonists have recently been described as frequent targets of epigenetic inactivation in human tumor entities. Since gene silencing of certain Wnt antagonists was found to be correlated with adverse patient survival in cancer, we aimed at investigating a potential prognostic impact of the two Wnt antagonizing molecules WIF1 and DKK3 in breast cancer, which are frequently silenced by promoter methylation in this disease. METHODS: WIF1 and DKK3 promoter methylation were assessed by methylation-specific PCR with bisulfite-converted DNA from 19 normal breast tissues and 150 primary breast carcinomas. Promoter methylation was interpreted in a qualitative, binary fashion. Statistical evaluations included two-sided Fisher's exact tests, univariate log-rank tests of Kaplan-Meier curves as well as multivariate Cox regression analyses. RESULTS: WIF1 and DKK3 promoter methylation were detected in 63.3% (95/150) and 61.3% (92/150) of breast carcinoma samples, respectively. In normal breast tissues, WIF1 methylation was present in 0% (0/19) and DKK3 methylation in 5.3% (1/19) of samples. In breast carcinomas, WIF1 methylation was significantly associated with methylation of DKK3 (p = 0.009). Methylation of either gene was not associated with clinicopathological parameters, except for DKK3 methylation being associated with patient age (p = 0.007). In univariate analysis, WIF1 methylation was not associated with clinical patient outcome. In contrast, DKK3 methylation was a prognostic factor in patient overall survival (OS) and disease-free survival (DFS). Estimated OS rates after 10 years were 54% for patients with DKK3-methylated tumors, in contrast to patients without DKK3 methylation in the tumor, who had a favorable 97% OS after 10 years (p < 0.001). Likewise, DFS at 10 years for patients harboring DKK3 methylation in the tumor was 58%, compared with 78% for patients with unmethylated DKK3 (p = 0.037). Multivariate analyses revealed that DKK3 methylation was an independent prognostic factor predicting poor OS (hazard ratio (HR): 14.4; 95% confidence interval (CI): 1.9-111.6; p = 0.011), and short DFS (HR: 2.5; 95% CI: 1.0-6.0; p = 0.047) in breast cancer. CONCLUSION: Although the Wnt antagonist genes WIF1 and DKK3 show a very similar frequency of promoter methylation in human breast cancer, only DKK3 methylation proves as a novel prognostic marker potentially useful in the clinical management of this disease.


Assuntos
Neoplasias da Mama/genética , Metilação de DNA , Peptídeos e Proteínas de Sinalização Intercelular/genética , Regiões Promotoras Genéticas , Proteína Wnt1/genética , Proteínas Adaptadoras de Transdução de Sinal , Neoplasias da Mama/diagnóstico , Quimiocinas , Epigênese Genética , Inativação Gênica , Marcadores Genéticos , Humanos , Análise Multivariada , Reação em Cadeia da Polimerase , Prognóstico , Modelos de Riscos Proporcionais , Fatores de Risco , Transdução de Sinais
16.
Abdom Radiol (NY) ; 44(2): 398-405, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30109377

RESUMO

PURPOSE: The purpose of the study was to compare the performance of contrast-enhanced (CE)-MRI and diffusion-weighted imaging (DW)-MRI in grading Crohn's disease activity of the terminal ileum. METHODS: Three readers evaluated CE-MRI, DW-MRI, and their combinations (CE/DW-MRI and DW/CE-MRI, depending on which protocol was used at the start of evaluation). Disease severity grading scores were correlated to the Crohn's Disease Endoscopic Index of Severity (CDEIS). Diagnostic accuracy, severity grading, and levels of confidence were compared between imaging protocols and interobserver agreement was calculated. RESULTS: Sixty-one patients were included (30 female, median age 36). Diagnostic accuracy for active disease for CE-MRI, DW-MRI, CE/DW-MRI, and DW/CE-MRI ranged between 0.82 and 0.85, 0.75 and 0.83, 0.79 and 0.84, and 0.74 and 0.82, respectively. Severity grading correlation to CDEIS ranged between 0.70 and 0.74, 0.66 and 0.70, 0.69 and 0.75, and 0.67 and 0.74, respectively. For each reader, CE-MRI values were consistently higher than DW-MRI, albeit not significantly. Confidence levels for all readers were significantly higher for CE-MRI compared to DW-MRI (P < 0.001). Further increased confidence was seen when using combined imaging protocols. CONCLUSIONS: There was no significant difference of CE-MRI and DW-MRI in determining disease activity, but the higher confidence levels may favor CE-MRI. DW-MRI is a good alternative in cases with relative contraindications for the use of intravenous contrast medium.


Assuntos
Meios de Contraste , Doença de Crohn/diagnóstico por imagem , Imagem de Difusão por Ressonância Magnética/métodos , Íleo/diagnóstico por imagem , Aumento da Imagem/métodos , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Reprodutibilidade dos Testes , Índice de Gravidade de Doença
17.
Am J Surg Pathol ; 43(10): 1377-1383, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31219817

RESUMO

False-negative (FN) intraoperative frozen section (FS) results of sentinel lymph nodes (SLN) have been reported to be more common after neoadjuvant chemotherapy (NAC) in the primary surgical setting. We evaluated SLN FS assessment in breast cancer patients treated with NAC to determine the FN rate and the histomorphologic factors associated with FN results. Patients who had FS SLN assessment following NAC from July 2008 to July 2017 were identified. Of the 711 SLN FS cases, 522 were negative, 181 positive, and 8 deferred. The FN rate was 5.4% (28/522). There were no false-positive results. Of the 8 deferred cases, 5 were positive on permanent section and 3 were negative. There was a higher frequency of micrometastasis and isolated tumor cells in FN cases (P<0.001). There was a significant increase in tissue surface area present on permanent section slides compared with FS slides (P<0.001), highlighting the inherent technical limitations of FS and histologic under-sampling of tissue which leads to most FN results. The majority (25/28, 89%) of FN cases had metastatic foci identified exclusively on permanent sections and were not due to a true diagnostic interpretation error. FN cases were more frequently estrogen receptor positive (P<0.001), progesterone receptor positive (P=0.001), human epidermal growth factor receptor-2 negative (P=0.009) and histologic grade 1 (P=0.015), which most likely reflects the lower rates of pathologic complete response in these tumors. Despite its limitations, FS is a reliable modality to assess the presence of SLN metastases in NAC treated patients.


Assuntos
Neoplasias da Mama/terapia , Carcinoma/terapia , Secções Congeladas , Mastectomia , Terapia Neoadjuvante , Biópsia de Linfonodo Sentinela , Linfonodo Sentinela/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Neoplasias da Mama/patologia , Carcinoma/secundário , Quimioterapia Adjuvante , Bases de Dados Factuais , Reações Falso-Negativas , Feminino , Humanos , Cuidados Intraoperatórios , Metástase Linfática , Pessoa de Meia-Idade , Micrometástase de Neoplasia , Valor Preditivo dos Testes , Reprodutibilidade dos Testes , Adulto Jovem
18.
Comput Med Imaging Graph ; 65: 142-151, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-29241972

RESUMO

Pathology is on the verge of a profound change from an analog and qualitative to a digital and quantitative discipline. This change is mostly driven by the high-throughput scanning of microscope slides in modern pathology departments, reaching tens of thousands of digital slides per month. The resulting vast digital archives form the basis of clinical use in digital pathology and allow large scale machine learning in computational pathology. One of the most crucial bottlenecks of high-throughput scanning is quality control (QC). Currently, digital slides are screened manually to detected out-of-focus regions, to compensate for the limitations of scanner software. We present a solution to this problem by introducing a benchmark dataset for blur detection, an in-depth comparison of state-of-the art sharpness descriptors and their prediction performance within a random forest framework. Furthermore, we show that convolution neural networks, like residual networks, can be used to train blur detectors from scratch. We thoroughly evaluate the accuracy of feature based and deep learning based approaches for sharpness classification (99.74% accuracy) and regression (MSE 0.004) and additionally compare them to domain experts in a comprehensive human perception study. Our pipeline outputs spacial heatmaps enabling to quantify and localize blurred areas on a slide. Finally, we tested the proposed framework in the clinical setting and demonstrate superior performance over the state-of-the-art QC pipeline comprising commercial software and human expert inspection by reducing the error rate from 17% to 4.7%.


Assuntos
Benchmarking , Diagnóstico por Imagem , Aumento da Imagem/normas , Aprendizado de Máquina , Controle de Qualidade , Redes Neurais de Computação
19.
Oncotarget ; 9(12): 10284-10293, 2018 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-29535806

RESUMO

BACKGROUND: We aimed to analyze the frequency and distribution of PD-L1 expression in specimens from prostate cancer (PC) patients using two different anti-PD-L1 antibodies (E1L3N, SP263). MATERIALS AND METHODS: PD-L1 immunohistochemistry was performed in a tissue microarray consisting of 82 castration-resistant prostate cancer (CRPC) specimens, 70 benign prostate hyperplasia (BPH) specimens, 96 localized PC cases, and 3 PC cell lines, using two different antibodies (clones E1L3N, and SP263). Staining images for CD4, CD8, PD-L1, and PanCK of a single PD-L1 positive case were compared, using a newly developed dot-wise correlation method for digital images to objectively test for co-expression. RESULTS: Depending on the antibody used, in tumor cells (TC) only five (E1L3N: 6%) and three (SP263: 3.7%) samples were positive. In infiltrating immune cells (IC) 12 (SP263: 14.6%) and 8 (E1L3N: 9.9%) specimens showed PD-L1 expression. Two PC cell lines (PC3, LnCaP) also displayed membranous immunoreactivity. All localized PCs or BPH samples tested were negative. Dot-wise digital correlation of expression patterns revealed a moderate positive correlation between PD-L1 and PanCK expression, whereas both PanCK and PD-L1 showed a weak negative Pearson correlation coefficient between CD4 and CD8. CONCLUSIONS: PD-L1 was not expressed in localized PC or BPH, and was only found in a minority of CRPC tumors and infiltrating immune cells. Protein expression maps and systematic dot-wise comparison could be a useful objective way to describe the relationship between immuno- and tumor-related proteins in the future, without the need to develop multiplex staining methods.

20.
Acad Radiol ; 25(8): 1038-1045, 2018 08.
Artigo em Inglês | MEDLINE | ID: mdl-29428210

RESUMO

RATIONALE AND OBJECTIVES: The objective of this study was to develop and validate a predictive magnetic resonance imaging (MRI) activity score for ileocolonic Crohn disease activity based on both subjective and semiautomatic MRI features. MATERIALS AND METHODS: An MRI activity score (the "virtual gastrointestinal tract [VIGOR]" score) was developed from 27 validated magnetic resonance enterography datasets, including subjective radiologist observation of mural T2 signal and semiautomatic measurements of bowel wall thickness, excess volume, and dynamic contrast enhancement (initial slope of increase). A second subjective score was developed based on only radiologist observations. For validation, two observers applied both scores and three existing scores to a prospective dataset of 106 patients (59 women, median age 33) with known Crohn disease, using the endoscopic Crohn's Disease Endoscopic Index of Severity (CDEIS) as a reference standard. RESULTS: The VIGOR score (17.1 × initial slope of increase + 0.2 × excess volume + 2.3 × mural T2) and other activity scores all had comparable correlation to the CDEIS scores (observer 1: r = 0.58 and 0.59, and observer 2: r = 0.34-0.40 and 0.43-0.51, respectively). The VIGOR score, however, improved interobserver agreement compared to the other activity scores (intraclass correlation coefficient = 0.81 vs 0.44-0.59). A diagnostic accuracy of 80%-81% was seen for the VIGOR score, similar to the other scores. CONCLUSIONS: The VIGOR score achieves comparable accuracy to conventional MRI activity scores, but with significantly improved reproducibility, favoring its use for disease monitoring and therapy evaluation.


Assuntos
Colo/diagnóstico por imagem , Doença de Crohn/diagnóstico por imagem , Íleo/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética , Adulto , Feminino , Humanos , Masculino , Variações Dependentes do Observador , Estudos Prospectivos , Reprodutibilidade dos Testes , Índice de Gravidade de Doença
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