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Article ; Online: Clear Cell Renal Cell Carcinoma with Prominent Micropapillary Pattern: A Case Report of a Previously Undescribed Morphology.

Fahoum, Ibrahim / Hershkovitz, Dov / Erental, Ariel / Argani, Pedram

International journal of surgical pathology

2023 , Page(s) 10668969231195071

Abstract: The classic morphology of clear cell renal cell carcinoma consists of nests of cells with clear cytoplasm. Nevertheless, other histologic patterns may be seen including cells with eosinophilic cytoplasm, bizarre multinucleated giant tumor cells and ... ...

Abstract	The classic morphology of clear cell renal cell carcinoma consists of nests of cells with clear cytoplasm. Nevertheless, other histologic patterns may be seen including cells with eosinophilic cytoplasm, bizarre multinucleated giant tumor cells and pseudopapillary structures. In this article, we present the first case of clear cell renal cell carcinoma with a prominent micropapillary pattern.
Language	English
Publishing date	2023-10-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	1336393-1
ISSN	1940-2465 ; 1066-8969
ISSN (online)	1940-2465
ISSN	1066-8969
DOI	10.1177/10668969231195071
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Article ; Online: Perineural invasion detection in pancreatic ductal adenocarcinoma using artificial intelligence.

Borsekofsky, Sarah / Tsuriel, Shlomo / Hagege, Rami R / Hershkovitz, Dov

Scientific reports

2023 Volume 13, Issue 1, Page(s) 13628

Abstract: Perineural invasion (PNI) refers to the presence of cancer cells around or within nerves, raising the risk of residual tumor. Linked to worse prognosis in pancreatic ductal adenocarcinoma (PDAC), PNI is also being explored as a therapeutic target. The ... ...

Abstract	Perineural invasion (PNI) refers to the presence of cancer cells around or within nerves, raising the risk of residual tumor. Linked to worse prognosis in pancreatic ductal adenocarcinoma (PDAC), PNI is also being explored as a therapeutic target. The purpose of this work was to build a PNI detection algorithm to enhance accuracy and efficiency in identifying PNI in PDAC specimens. Training used 260 manually segmented nerve and tumor HD images from 6 scanned PDAC cases; Analytical performance analysis used 168 additional images; clinical analysis used 59 PDAC cases. The algorithm pinpointed key areas of tumor-nerve proximity for pathologist confirmation. Analytical performance reached sensitivity of 88% and 54%, and specificity of 78% and 85% for the detection of nerve and tumor, respectively. Incorporating tumor-nerve distance in clinical evaluation raised PNI detection from 52 to 81% of all cases. Interestingly, pathologist analysis required an average of only 24 s per case. This time-efficient tool accurately identifies PNI in PDAC, even with a small training cohort, by imitating pathologist thought processes.
MeSH term(s)	Humans ; Artificial Intelligence ; Pancreatic Neoplasms/diagnosis ; Carcinoma, Pancreatic Ductal/diagnosis ; Algorithms ; Pancreatic Neoplasms
Language	English
Publishing date	2023-08-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-40833-y
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Article ; Online: Algorithm-assisted diagnosis of Hirschsprung's disease - evaluation of robustness and comparative image analysis on data from various labs and slide scanners.

Greenberg, Ariel / Samueli, Benzion / Farkash, Shai / Zohar, Yaniv / Ish-Shalom, Shahar / Hagege, Rami R / Hershkovitz, Dov

Diagnostic pathology

2024 Volume 19, Issue 1, Page(s) 26

Abstract: Background: Differences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. Algorithm-assisted tools must be able to contend with this variability in order to be applicable in clinical ... ...

Abstract	Background: Differences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. Algorithm-assisted tools must be able to contend with this variability in order to be applicable in clinical practice. In a previous study, a decision support algorithm was developed to assist in the diagnosis of Hirschsprung's disease. In the current study, we tested the robustness of this algorithm while assessing for pre-analytic factors which may affect its performance. Methods: The decision support algorithm was used on digital pathology slides obtained from four different medical centers (A-D) and scanned by three different scanner models (by Philips, Hamamatsu and 3DHISTECH). A total of 192 cases and 1782 slides were used in this study. RGB histograms were constructed to compare images from the various medical centers and scanner models and highlight the differences in color and contrast. Results: The algorithm was able to correctly identify ganglion cells in 99.2% of cases, from all medical centers (All scanned by the Philips slide scanner) as well as 95.5% and 100% of the slides scanned by the 3DHISTECH and Hamamatsu brand slide scanners, respectively. The total error rate for center D was lower than the other medical centers (3.9% vs 7.1%, 10.8% and 6% for centers A-C, respectively), the vast majority of errors being false positives (3.45% vs 0.45% false negatives). The other medical centers showed a higher rate of false negatives in relation to false positives (6.81% vs 0.29%, 9.8% vs 1.2% and 5.37% vs 0.63% for centers A-C, respectively). The total error rates for the Philips, Hamamatsu and 3DHISTECH brand scanners were 3.9%, 3.2% and 9.8%, respectively. RGB histograms demonstrated significant differences in pixel value distribution between the four medical centers, as well as between the 3DHISTECH brand scanner when compared to the Philips and Hamamatsu brand scanners. Conclusions: The results reported in this paper suggest that the algorithm-based decision support system has sufficient robustness to be applicable for clinical practice. In addition, the novel method used in its development - Hierarchial-Contexual Analysis (HCA) may be applicable to the development of algorithm-assisted tools in other diseases, for which available datasets are limited. Validation of any given algorithm-assisted support system should nonetheless include data from as many medical centers and scanner models as possible.
MeSH term(s)	Humans ; Hirschsprung Disease ; Image Processing, Computer-Assisted/methods ; Algorithms ; Microscopy
Language	English
Publishing date	2024-02-06
Publishing country	England
Document type	Journal Article
ZDB-ID	2210518-9
ISSN	1746-1596 ; 1746-1596
ISSN (online)	1746-1596
ISSN	1746-1596
DOI	10.1186/s13000-024-01452-x
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Article ; Online: Digital PCR-Based Method for Detecting CDKN2A Loss in Brain Tumours.

Tsuriel, Shlomo / Hannes, Victoria / Hasona, Asala / Raz, Michal / Hershkovitz, Dov

Molecular diagnosis & therapy

2022 Volume 26, Issue 6, Page(s) 689–698

Abstract: Introduction: CDKN2A is a key tumour suppressor gene and loss of CDKN2A can be found in many tumours. In astrocytoma grade IV, CDKN2A is deleted in more than 50% of tumours. In many instances, low-grade gliomas with homozygous loss of CDKN2A behave like ...

Abstract	Introduction: CDKN2A is a key tumour suppressor gene and loss of CDKN2A can be found in many tumours. In astrocytoma grade IV, CDKN2A is deleted in more than 50% of tumours. In many instances, low-grade gliomas with homozygous loss of CDKN2A behave like high grade tumours. The available techniques for CDKN2A loss are laborious, expensive, unreliable, or unavailable in most pathology institutes. Therefore, although it is essential for accurate brain tumour diagnosis, the routine diagnosis does not include testing for CDKN2A deletion. Methods: We developed a digital polymerase chain reaction (dPCR) assay for CDKN2A loss detection. The assay is based on counting the copy number of CDKN2A gene and of a reference gene on the same chromosome. It was tested for the detection limit with regard to tumour content and minimal DNA quantity. It was then tested on 24 clinical samples with known CDKN2A status. Additionally, we tested 44 gliomas with unknown CDKN2A status. Results: We found that the newly developed assay is reliable in tissue with more than 50% tumour content and more than 0.4 ng of DNA. The validation cohort showed complete concordance, and we were able to detect homozygous loss in 16 gliomas with unknown CDKN2A status. Discussion: The method presented can give a fast, cost-effective, clinically reliable evaluation of CDKN2A loss in tissue with more than 50% tumour content. Its ability to work with old samples and with low amounts of DNA makes it the favoured assay in cases where other techniques fail.
MeSH term(s)	Humans ; Brain Neoplasms/genetics ; Glioma/genetics ; Genes, p16 ; Astrocytoma/genetics ; Polymerase Chain Reaction ; Gene Deletion ; Cyclin-Dependent Kinase Inhibitor p16
Chemical Substances	CDKN2A protein, human ; Cyclin-Dependent Kinase Inhibitor p16
Language	English
Publishing date	2022-09-21
Publishing country	New Zealand
Document type	Journal Article
ZDB-ID	2232796-4
ISSN	1179-2000 ; 1177-1062
ISSN (online)	1179-2000
ISSN	1177-1062
DOI	10.1007/s40291-022-00610-5
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Zs.A 5202: Show issues

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Article: Image-Based Deep Learning Detection of High-Grade B-Cell Lymphomas Directly from Hematoxylin and Eosin Images.

Perry, Chava / Greenberg, Orli / Haberman, Shira / Herskovitz, Neta / Gazy, Inbal / Avinoam, Assaf / Paz-Yaacov, Nurit / Hershkovitz, Dov / Avivi, Irit

Cancers

2023 Volume 15, Issue 21

Abstract: Deep learning applications are emerging as promising new tools that can support the diagnosis and classification of different cancer types. While such solutions hold great potential for hematological malignancies, there have been limited studies ... ...

Abstract	Deep learning applications are emerging as promising new tools that can support the diagnosis and classification of different cancer types. While such solutions hold great potential for hematological malignancies, there have been limited studies describing the use of such applications in this field. The rapid diagnosis of double/triple-hit lymphomas (DHLs/THLs) involving
Language	English
Publishing date	2023-10-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers15215205
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Article ; Online: Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report.

Waissengrin, Barliz / Garasimov, Alexandra / Bainhoren, Or / Merimsky, Ofer / Shamai, Sivan / Erental, Ariel / Wolf, Ido / Hershkovitz, Dov

Journal of clinical pathology

2023 Volume 76, Issue 11, Page(s) 790–792

Abstract: Leptomeningeal involvement among non-small cell lung cancer (NSCLC) patients is an aggressive form of disease that requires quick and efficient treatment. In this case report, we describe a woman in her 40s with a presenting symptom of headache that ... ...

Abstract	Leptomeningeal involvement among non-small cell lung cancer (NSCLC) patients is an aggressive form of disease that requires quick and efficient treatment. In this case report, we describe a woman in her 40s with a presenting symptom of headache that ultimately was diagnosed as leptomeningeal spread from NSCLC adenocarcinoma. We identified EGFR mutation in less than 48 hours from the biopsy using imagene-artificial intelligence's real-time algorithmic solution on the pathological diagnostic slide.
MeSH term(s)	Female ; Humans ; Adenocarcinoma/genetics ; Adenocarcinoma/therapy ; Artificial Intelligence ; Carcinoma, Non-Small-Cell Lung/genetics ; Carcinoma, Non-Small-Cell Lung/therapy ; Carcinoma, Non-Small-Cell Lung/pathology ; ErbB Receptors/genetics ; Lung Neoplasms/genetics ; Lung Neoplasms/therapy ; Lung Neoplasms/diagnosis ; Mutation ; Adult
Chemical Substances	ErbB Receptors (EC 2.7.10.1)
Language	English
Publishing date	2023-07-18
Publishing country	England
Document type	Case Reports ; Journal Article
ZDB-ID	80261-x
ISSN	1472-4146 ; 0021-9746
ISSN (online)	1472-4146
ISSN	0021-9746
DOI	10.1136/jcp-2023-208991
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Article: Association between Nuclear Morphometry Parameters and Gleason Grade in Patients with Prostatic Cancer.

Malshy, Kamil / Amiel, Gilad E / Hershkovitz, Dov / Sabo, Edmond / Hoffman, Azik

Diagnostics (Basel, Switzerland)

2022 Volume 12, Issue 6

Abstract: Objective: Gleason scoring system remains the pathological method of choice for prostate cancer (Pca) grading. However, this method of tumor tissue architectural structure grading is still affected by subjective assessment and might succumb to several ... ...

Abstract	Objective: Gleason scoring system remains the pathological method of choice for prostate cancer (Pca) grading. However, this method of tumor tissue architectural structure grading is still affected by subjective assessment and might succumb to several disadvantages, mainly inter-observer variability. These limitations might be diminished by determining characteristic cellular heterogeneity parameters which might improve Gleason scoring homogeneity. One of the quantitative tools of tumor assessment is the morphometric characterization of tumor cell nuclei. We aimed to test the relationship between various morphometric measures and the Gleason score assigned to different prostate cancer samples. Materials and Methods: We reviewed 60 prostate biopsy samples performed at a tertiary uro-oncology center. Each slide was assigned a Gleason grade according to the International Society of Urological Pathology contemporary grading system by a single experienced uro-pathologist. Samples were assigned into groups from grades 3 to 5. Next, the samples were digitally scanned (×400 magnification) and sampled on a computer using Image-Pro-Plus software©. Manual segmentation of approximately 100 selected tumor cells per sample was performed, and a computerized measurement of 54 predetermined morphometric properties of each cell nuclei was recorded. These characteristics were used to compare the pathological group grades assigned to each specimen. Results: Initially, of the 54 morphometric parameters evaluated, 38 were predictive of Gleason grade (p < 0.05). On multivariate analysis, 7 independent parameters were found to be discriminative of different Pca grades: minimum radius shape, intensity—minimal gray level, intensity—maximal gray level, character—gray level (green), character—gray level (blue), chromatin color, fractal dimension, and chromatin texture. A formula to predict the presence of Gleason grade 3 vs. grades 4 or 5 was developed (97.2% sensitivity, 100% specificity). Discussion: The suggested morphometry method based on seven selected parameters is highly sensitive and specific in predicting Gleason score ≥ 4. Since discriminating Gleason score 3 from ≥4 is essential for proper treatment selection, this method might be beneficial in addition to standard pathological tissue analysis in reducing variability among pathologists.
Language	English
Publishing date	2022-05-31
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics12061356
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Article ; Online: The risk of PD-L1 expression misclassification in triple-negative breast cancer.

Ben Dori, Shani / Aizic, Asaf / Zubkov, Asia / Tsuriel, Shlomo / Sabo, Edmond / Hershkovitz, Dov

Breast cancer research and treatment

2022 Volume 194, Issue 2, Page(s) 297–305

Abstract: Purpose: Stratification of patients with triple-negative breast cancer (TNBC) for anti-PD-L1 therapy is based on PD-L1 expression in tumor biopsies. This study sought to evaluate the risk of PD-L1 misclassification.: Methods: We conducted a high- ... ...

Abstract	Purpose: Stratification of patients with triple-negative breast cancer (TNBC) for anti-PD-L1 therapy is based on PD-L1 expression in tumor biopsies. This study sought to evaluate the risk of PD-L1 misclassification. Methods: We conducted a high-resolution analysis on ten surgical specimens of TNBC. First, we determined PD-L1 expression pattern distribution via manual segmentation and measurement of 6666 microscopic clusters of positive PD-L1 immunohistochemical staining. Then, based on these results, we generated a computer model to calculate the effect of the positive PD-L1 fraction, aggregate size, and distribution of PD-L1 positive cells on the diagnostic accuracy. Results: Our computer-based model showed that larger aggregates of PD-L1 positive cells and smaller biopsy size were associated with higher fraction of false results (P < 0.001, P < 0.001, respectively). Additionally, our model showed a significant increase in error rate when the fraction of PD-L1 expression was close to the cut-off (error rate of 12.1%, 0.84%, and 0.65% for PD-L1 positivity of 0.5-1.5%, ≤ 0.5% ,and ≥ 1.5%, respectively, P < 0.0001). Interestingly, false positive results were significantly higher than false negative results (0.51-22.62%, with an average of 6.31% versus 0.11-11.36% with an average of 1.58% for false positive and false negative results, respectively, P < 0.05). Furthermore, heterogeneous tumors with different aggregate sizes in the same tumor, were associated with increased rate of false results in comparison to homogenous tumors (P < 0.001). Conclusion: Our model can be used to estimate the risk of PD-L1 misclassification in biopsies, with potential implications for treatment decisions.
MeSH term(s)	B7-H1 Antigen/genetics ; B7-H1 Antigen/metabolism ; Humans ; Prognosis ; Triple Negative Breast Neoplasms/diagnosis ; Triple Negative Breast Neoplasms/genetics ; Triple Negative Breast Neoplasms/metabolism
Chemical Substances	B7-H1 Antigen
Language	English
Publishing date	2022-05-27
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	604563-7
ISSN	1573-7217 ; 0167-6806
ISSN (online)	1573-7217
ISSN	0167-6806
DOI	10.1007/s10549-022-06630-3
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Article: Molecular and Morphometric Tools for Next-Generation Pathology Diagnosis of Colon Carcinoma.

Fisher, Yael / Hershkovitz, Dov

The Israel Medical Association journal : IMAJ

2016 Volume 18, Issue 7, Page(s) 426–432

Language	English
Publishing date	2016-07
Publishing country	Israel
Document type	Journal Article ; Review
ZDB-ID	2008291-5
ISSN	1565-1088 ; 0021-2180
ISSN	1565-1088 ; 0021-2180
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Article ; Online: Tumor-to-Tumor Metastasis of Colorectal Adenocarcinoma to Ovarian Cystadenofibroma: A Case Report and Review of the Literature.

Fahoum, Ibrahim / Brazowski, Eli / Hershkovitz, Dov / Aizic, Asaf

International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists

2019 Volume 39, Issue 3, Page(s) 270–272

Abstract: Tumor-to-tumor metastasis is being described in different types of tumors and in increasing amount of cases. Being aware of this phenomenon is important, as it affects disease stage and treatment approach. In this report, we descried an incidental ... ...

Abstract	Tumor-to-tumor metastasis is being described in different types of tumors and in increasing amount of cases. Being aware of this phenomenon is important, as it affects disease stage and treatment approach. In this report, we descried an incidental histopathologic finding of metastatic adenocarcinoma to an ovarian cystadenofibroma and review cases published previously in the literature.
MeSH term(s)	Adenocarcinoma/pathology ; Aged, 80 and over ; Colorectal Neoplasms/pathology ; Cystadenofibroma/pathology ; Female ; Humans ; Neoplasms, Second Primary/pathology ; Ovarian Neoplasms/pathology
Language	English
Publishing date	2019-03-18
Publishing country	United States
Document type	Case Reports ; Journal Article ; Review
ZDB-ID	604859-6
ISSN	1538-7151 ; 0277-1691
ISSN (online)	1538-7151
ISSN	0277-1691
DOI	10.1097/PGP.0000000000000592
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