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van Diest PJ, Flach RN, van Dooijeweert C, Makineli S, Breimer GE, Stathonikos N, Pham P, Nguyen TQ, Veta M. Pros and cons of artificial intelligence implementation in diagnostic pathology. Histopathology 2024; 84:924-934. [PMID: 38433288 DOI: 10.1111/his.15153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/29/2023] [Accepted: 01/19/2024] [Indexed: 03/05/2024]
Abstract
The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.
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Affiliation(s)
- Paul J van Diest
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Rachel N Flach
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Oncological Urology, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - Seher Makineli
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Gerben E Breimer
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Nikolas Stathonikos
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Paul Pham
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tri Q Nguyen
- Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Mitko Veta
- Department of Oncological Urology, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
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Khalifa MA, Gagner B, Chen L, Murugan P, Klein ME, Racila E, Amin K, Miller D, Stewart J, Ding Y, Farooqui M, Dasaraju S, Adeyi OA. Immunohistochemistry and immunofluorescence utilization audit by subspecialty in an academic setting: A step toward stewardship. Ann Diagn Pathol 2023; 67:152214. [PMID: 37783147 DOI: 10.1016/j.anndiagpath.2023.152214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/04/2023]
Abstract
There are immunohistochemistry (IHC) and immunofluorescence (IF) panels described in the literature and established by personal and institutional experiences that are in common use by pathologists in their daily practice. Stewardship is a difficult discussion because IHC utilization is influenced by many factors including the pathologist's experience, background, practice setting, personal bias, and medicolegal culture. We developed the methodology to audit the IHC/IF utilization in our academic subspecialty practice. We aim to share this methodology and to provide our data that can be used for consideration by other subspecialized academic practices. This analysis included a total of 63,157 specimens that were accessioned during 2022, representing 38,612 cases. The likelihood of ordering IHC/IF ranged from 1 % (in genitourinary pathology) to 59 % (in renal pathology). The average percentage of specimens with IHC/IF was 21 % for the entire practice. In cases where IHC/IF was ordered, the number of stained slides averaged 4.9 per specimen for the entire practice. The number of IHC/IF slides per specimen ranged from 1.9 (in gastrointestinal pathology) to 12.2 (in renal pathology). The highest number of antibodies ordered for a single specimen by subspecialty ranged from 11 (in cardiac pathology) to 63 (in dermatopathology). Renal pathology was the only subspecialty that had an average number of IHC/IF slides that was statistically significantly different from all other subspecialties. We described the various patterns of utilization by subspecialty and rationalized their subtle differences. We also analyzed the types of cases that exceeded the reimbursement limits set by the Centers for Medicare and Medicaid Services (CMS).
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Affiliation(s)
- Mahmoud A Khalifa
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America.
| | - Brooke Gagner
- MHealth Fairview Laboratories, Minneapolis, MN, United States of America
| | - Liam Chen
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Paari Murugan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Molly E Klein
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Emilian Racila
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Khalid Amin
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Daniel Miller
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Jimmie Stewart
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Yanli Ding
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Mariya Farooqui
- MHealth Fairview Laboratories, Minneapolis, MN, United States of America
| | - Sandhyarani Dasaraju
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Oyedele A Adeyi
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America
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Chatrian A, Colling RT, Browning L, Alham NK, Sirinukunwattana K, Malacrino S, Haghighat M, Aberdeen A, Monks A, Moxley-Wyles B, Rakha E, Snead DRJ, Rittscher J, Verrill C. Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies. Mod Pathol 2021; 34:1780-1794. [PMID: 34017063 PMCID: PMC8376647 DOI: 10.1038/s41379-021-00826-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/29/2022]
Abstract
The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request. We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide-level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by threefold cross-validation. Validation was conducted on a separate validation dataset of 222 images. Non IHC-requested cases were diagnosed in 17.9 min on average, while IHC-requested cases took 33.4 min over multiple reporting sessions. We estimated 11 min could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80. We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.
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Affiliation(s)
- Andrea Chatrian
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK.
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.
| | - Richard T Colling
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nasullah Khalid Alham
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Korsuk Sirinukunwattana
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Stefano Malacrino
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Maryam Haghighat
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Alan Aberdeen
- Ground Truth Labs, 9400 Garsington Road, Oxford Business Park, Oxford, UK
| | - Amelia Monks
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
| | - Benjamin Moxley-Wyles
- Department of Cellular Pathology, Buckinghamshire Healthcare NHS Trust, Amersham, UK
| | - Emad Rakha
- School of Medicine, University of Nottingham, Nottingham, Nottinghamshire, UK
| | - David R J Snead
- Department of Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, West Midlands, UK
| | - Jens Rittscher
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK.
- Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK.
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK.
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK.
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Alshaikh S, Lapadat R, Atieh MK, Mehrotra S, Barkan GA, Wojcik EM, Pambuccian SE. The utilization and utility of immunostains in body fluid cytology. Cancer Cytopathol 2020; 128:384-391. [PMID: 32163239 DOI: 10.1002/cncy.22256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 11/06/2019] [Accepted: 11/25/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND Body fluid cytology (BFC) is an important tool in the diagnosis and staging of malignancy and is aided by the judicious use of immunohistochemistry (IHC). The aim of this study was to determine the usage rates of IHC stains in BFC, their type and indications, and their diagnostic impact. We also attempted to estimate the optimal rate of IHC use in BFC by comparing the entire laboratory's and each individual cytopathologist's IHC use rates with their respective indeterminate and malignant diagnosis rates. METHODS We conducted a retrospective study of IHC stain use in BFC during a 5.5-year interval (2013-2018) and determined the laboratory's and each individual cytopathologist's IHC usage patterns according to the final diagnosis, site, and indications for their use. RESULTS A total of 477 out of 4144 (11.5%) BFC cases had 2128 individual immunostains performed, with an average of 4.5 immunostains per case. Individual cytopathologists used IHC stains on 6.7% to 22% of their BFC cases. Pathologists with higher rates of IHC stain use than the laboratory's mean were less experienced and had higher rates of indeterminate but not of malignant diagnoses. The most common indication for the use of IHC stains was differentiating mesothelial from malignant cells. MOC31, calretinin, Ber-EP4, CD68, and D2-40 were the most commonly used of the 67 different IHC stains used in BFC. CONCLUSIONS The laboratory's mean may represent the optimal IHC use rate, as higher IHC use rates did not lead to more diagnostic certainty or higher pickup rates of malignant cells.
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Affiliation(s)
| | - Razvan Lapadat
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
| | - Mohammed K Atieh
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
| | - Swati Mehrotra
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
| | - Güliz A Barkan
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
| | - Eva M Wojcik
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
| | - Stefan E Pambuccian
- Department of Pathology and Laboratory Medicine, Loyola University Medical Center, Maywood, Illinois
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Compton ML, Hogan M, Reisenbichler ES. Differences in immunohistochemistry utilization by general and breast subspecialty pathologists at a large academic institution. Ann Diagn Pathol 2019; 42:92-95. [PMID: 31445409 DOI: 10.1016/j.anndiagpath.2019.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/15/2019] [Accepted: 08/16/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Immunohistochemistry (IHC) can be a useful adjunct in diagnostic breast pathology, but best practices have not been clearly established. We sought to compare the patterns of p63 utilization between general pathologists (GP) and subspecialized breast pathologists (BP), analyze diagnostic discrepancy rates, and identify types of lesions requiring immunohistochemistry. METHODS The pathology database was searched over 6-year period to identify breast needle core biopsy cases utilizing p63 and subsequent excision results. RESULTS P63 was ordered more frequently by BP (2.3% of cores) compared to GP (1.1% of cores, p = 0.0005). The most frequent utilization of p63 by GP for benign lesions (44.0%) followed by invasive carcinomas (36.0%) while BP most frequently ordered p63 on invasive carcinomas (49.5%) and DCIS (26.6%). CONCLUSIONS While IHC use may be thought to be most helpful to those with less experience or knowledge in breast pathology, these results suggest that utilization is increased with subspecialty training.
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Affiliation(s)
- Margaret L Compton
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, 1161 21st Avenue South, MCN CC3322, Nashville, TN 37232-2561, United States of America.
| | - Melissa Hogan
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, United States of America
| | - Emily S Reisenbichler
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, United States of America; Department of Pathology, Yale-New Haven Health System, United States of America
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Verhoef EI, van Cappellen WA, Slotman JA, Kremers GJ, Ewing-Graham PC, Houtsmuller AB, van Royen ME, van Leenders GJLH. Three-dimensional architecture of common benign and precancerous prostate epithelial lesions. Histopathology 2019; 74:1036-1044. [PMID: 30815904 PMCID: PMC6849837 DOI: 10.1111/his.13848] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 02/25/2019] [Indexed: 12/12/2022]
Abstract
Aims Many glandular lesions can mimic prostate cancer microscopically, including atrophic glands, adenosis and prostatic intraepithelial neoplasia. While the characteristic histopathological and immunohistochemical features of these lesions have been well established, little is known about their three‐dimensional architecture. Our objective was to evaluate the three‐dimensional organisation of common prostate epithelial lesions. Methods and results 500 μm‐thick punches (n = 42) were taken from radical prostatectomy specimens, and stained with antibodies targeting keratin 8–18 and keratin 5 for identification of luminal and basal cells, respectively. Tissue samples were optically cleared in benzyl alcohol:benzyl benzoate and imaged using a confocal laser scanning microscope. The three‐dimensional architecture of peripheral and transition zone glands was acinar, composed of interconnecting and blind‐ending saccular tubules. In simple atrophy, partial atrophy and post‐atrophic hyperplasia, the acinar structure was attenuated with branching blind‐ending tubules from parental tubular structures. Three‐dimensional imaging revealed a novel variant of prostate atrophy characterised by large Golgi‐like atrophic spaces parallel to the prostate surface, which were represented by thin, elongated tubular structures on haematoxylin and eosin (H&E) slides. Conversely, adenosis lacked acinar organisation, so that it closely mimicked low‐grade prostate cancer. High‐grade prostatic intraepithelial neoplasia displayed prominent papillary intraluminal protrusions but retained an acinar organisation, whereas intraductal carcinoma predominantly consisted of cribriform proliferations with either spheroid, ellipsoid or complex interconnecting lumens. Conclusions While various prostate epithelial lesions might mimic malignancy on H&E slides, their three‐dimensional architecture is acinar and clearly different from the tubular structure of prostate cancer, with adenosis as an exception.
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Affiliation(s)
- Esther I Verhoef
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Wiggert A van Cappellen
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Optical Imaging Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Johan A Slotman
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Optical Imaging Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Gert-Jan Kremers
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Optical Imaging Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Patricia C Ewing-Graham
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Adriaan B Houtsmuller
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Optical Imaging Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Martin E van Royen
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Optical Imaging Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Geert J L H van Leenders
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
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Wu Y, Meng Q, Yang Z, Shi L, Hu R, Zhang P, Wei J, Ren J, Leng B, Xu D, Jiang GQ. Circulating HER-2 mRNA in the peripheral blood as a potential diagnostic and prognostic biomarker in females with breast cancer. Oncol Lett 2018; 16:3726-3734. [PMID: 30127983 PMCID: PMC6096115 DOI: 10.3892/ol.2018.9091] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 05/04/2018] [Indexed: 01/04/2023] Open
Abstract
Breast cancer is a prevalent malignant cancer worldwide, and a lack of defined biomarkers for early prognostication contributes to its high associated mortality rate, especially in human epidermal growth factor receptor 2 (HER-2)-positive breast cancer. In the present study, HER-2 mRNA levels in patients were detected prior to surgery and during neoadjuvant chemotherapy to explore its potential diagnostic and prognostic value. Blood samples were collected from 70 patients with breast cancer, including 50 HER-2-negative and 20 HER-2-positive patients, prior to and following surgery (postoperative, n=13; neoadjuvant chemotherapy, n=5); the control group included 35 samples from healthy individuals. The relative mRNA level of HER-2 in blood was determined by one-step reverse transcription-quantitative polymerase chain reaction. HER-2 expression curves of measurements taken during neoadjuvant chemotherapy were compared with the tumor size. A significant difference in the blood HER-2 mRNA level was observed between healthy women and patients with breast cancer (P<0.0001). A cutoff value of 1.512 was established for the circulating HER-2 level in healthy subjects based on the upper 95% confidence interval value of samples from the control group. The level of HER-2 mRNA in blood was associated with the HER-2 status, Ki-67 expression, and lymphovascular invasion in primary tumor tissue samples; however, there was no association with the lymph node status, tumor stage, tumor grade, tumor size, patient age, estrogen or progesterone receptor status of the primary tumor. HER-2 mRNA levels were associated with the response rate, as determined by primary tumor size, in patients who received neoadjuvant chemotherapy. In conclusion, baseline and early changes in peripheral blood HER-2 mRNA indicated that HER-2 mRNA may be a potential diagnostic biomarker for breast cancer and a prognostic marker for predicting the efficacy of neoadjuvant therapy.
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Affiliation(s)
- Yanlin Wu
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Qiping Meng
- GenePharma Limited Liability Company, Suzhou, Jiangsu 215125, P.R. China
| | - Zhixue Yang
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Lili Shi
- GenePharma Limited Liability Company, Suzhou, Jiangsu 215125, P.R. China
| | - Rongkuan Hu
- GenePharma Limited Liability Company, Suzhou, Jiangsu 215125, P.R. China
| | - Peizhuo Zhang
- GenePharma Limited Liability Company, Suzhou, Jiangsu 215125, P.R. China
| | - Jinrong Wei
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Jie Ren
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Bingjing Leng
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Dong Xu
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
| | - Guo-Qin Jiang
- Department of General Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, P.R. China
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Shah MD, Parwani AV, Zynger DL. Impact of the Pathologist on Prostate Biopsy Diagnosis and Immunohistochemical Stain Usage Within a Single Institution. Am J Clin Pathol 2017; 148:494-501. [PMID: 29165567 DOI: 10.1093/ajcp/aqx103] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES To determine whether pathologists in a tertiary care institution vary in diagnosis and immunohistochemical stain usage in prostate biopsy specimens. METHODS Men who underwent prostate needle biopsies between 2008 and 2013 were included. RESULTS In total, 1,777 prostate biopsy specimens diagnosed by nine pathologists showed variation in diagnostic reporting (atypical small acinar proliferation, 2.0%-8.0%; high-grade prostatic intraepithelial neoplasia, 2.0%-8.5%; nonneoplastic, 30.2%-48.3%; adenocarcinoma, 46.2%-55.3%; P < .001). Variation in Gleason scoring was observed (P < .001), with the 4 + 3 = 7 category having the greatest variability (6.9%-30.3%). A blinded review from the most outlying pathologist in this category revealed 45% grading discrepancies. The mean number of immunostains performed per case (0.3-1.2) differed between pathologists (P < .001), and one pathologist used immunostains at twice the rate of the remaining cohort. CONCLUSIONS Case pathologist significantly affects prostate biopsy diagnosis and immunohistochemical workup. We recommend evaluation for outlying practice patterns to provide consistent and efficient patient care.
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Affiliation(s)
- Mit D Shah
- Department of Pathology, The Ohio State University Medical Center, Columbus
| | - Anil V Parwani
- Department of Pathology, The Ohio State University Medical Center, Columbus
| | - Debra L Zynger
- Department of Pathology, The Ohio State University Medical Center, Columbus
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9
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Pelosi G, Sonzogni A, Harari S, Albini A, Bresaola E, Marchiò C, Massa F, Righi L, Gatti G, Papanikolaou N, Vijayvergia N, Calabrese F, Papotti M. Classification of pulmonary neuroendocrine tumors: new insights. Transl Lung Cancer Res 2017; 6:513-529. [PMID: 29114468 PMCID: PMC5653522 DOI: 10.21037/tlcr.2017.09.04] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 09/12/2017] [Indexed: 12/11/2022]
Abstract
Neuroendocrine tumors of the lung (Lu-NETs) embrace a heterogeneous family of neoplasms classified into four histological variants, namely typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). Defining criteria on resection specimens include mitotic count in 2 mm2 and the presence or absence of necrosis, alongside a constellation of cytological and histological traits including cell size and shape, nuclear features and overall architecture. Clinically, TC are low-grade malignant tumors, AC intermediate-grade malignant tumors and SCLC/LCNEC high-grade malignant full-blown carcinomas with no significant differences in survival between them. Homologous tumors arise in the thymus that occasionally have some difficulties in differentiating from the lung counterparts when presented with large unresectable or metastatic lesions. Immunohistochemistry (IHC) helps refine NE diagnosis at various anatomical sites, particularly on small-sized tissue material, in which only TC and small cell carcinoma categories can be recognized easily on hematoxylin & eosin stain, while AC and LCNEC can only be suggested on such material. The Ki-67 labeling index effectively separates carcinoids from small cell carcinoma and may prove useful for the clinical management of a metastatic disease to help the therapeutic decision-making process. Although carcinoids and high-grade neuroendocrine carcinomas in the lung and elsewhere make up separate tumor categories on molecular grounds, emerging data supports the concept of secondary high-grade NETs arising in the preexisting carcinoids, whose clinical and biological relevance will have to be placed into the proper context for the optimal management of these patients. In this review, we will discuss the selected, recent literature with a focus on current issues regarding Lu-NET nosology, i.e., classification, derivation and tumor evolution.
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Affiliation(s)
- Giuseppe Pelosi
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy
- Inter-hospital Pathology Division, Science & Technology Park, IRCCS MultiMedica Group, Milan, Italy
| | - Angelica Sonzogni
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy
| | - Sergio Harari
- Department of Medical Sciences and Division of Pneumology, San Giuseppe Hospital, Science & Technology Park, IRCCS MultiMedica Group, Milan, Italy
| | - Adriana Albini
- Laboratory of Vascular Biology and Angiogenesis, Science & Technology Park, IRCCS MultiMedica Group, Milan, Italy
| | - Enrica Bresaola
- Department of Pathology and Laboratory Medicine, European Institute of Oncology, Milan, Italy
| | - Caterina Marchiò
- Department of Medical Sciences, University of Turin, and Pathology Division, AOU Città della Salute e della Scienza, Turin, Italy
| | - Federica Massa
- Department of Oncology, University of Turin, and Pathology Division, AOU Città della Salute e della Scienza, Turin, Italy
| | - Luisella Righi
- Department of Oncology, University of Turin, Pathology Division, San Luigi Hospital, University of Turin, Turin, Italy
| | - Gaia Gatti
- Department of Oncology, University of Turin, Pathology Division, San Luigi Hospital, University of Turin, Turin, Italy
| | - Nikolaos Papanikolaou
- Inter-hospital Pathology Division, Science & Technology Park, IRCCS MultiMedica Group, Milan, Italy
| | - Namrata Vijayvergia
- Department of Hematology and Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Fiorella Calabrese
- Department of Cardiac, Thoracic and Vascular Sciences, University of Padua, Padova, Italy
| | - Mauro Papotti
- Department of Oncology, University of Turin, and Pathology Division, AOU Città della Salute e della Scienza, Turin, Italy
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