Journal of Pathology and Translational Medicine

Original Articles

Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning: Truong Phan-Xuan Nguyen, Minh-Khang Le, Sittiruk Roytrakul, Shanop Shuangshoti, Nakarin Kitkumthorn, Somboon Keelawat; Received July 23, 2024 Accepted September 14, 2024 Published online October 24, 2024; DOI: https://doi.org/10.4132/jptm.2024.09.14 [Epub ahead of print]

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Abstract PDF Supplementary Material: Background
Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples.
Methods
We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples.
Results
We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC > 0.5.
Conclusions
We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Revisiting the utility of identifying nuclear grooves as unique nuclear changes by an object detector model: Pedro R. F. Rende, Joel Machado Pires, Kátia Sakimi Nakadaira, Sara Lopes, João Vale, Fabio Hecht, Fabyan E. L. Beltrão, Gabriel J. R. Machado, Edna T. Kimura, Catarina Eloy, Helton E. Ramos; J Pathol Transl Med. 2024;58(3):117-126. Published online April 30, 2024; DOI: https://doi.org/10.4132/jptm.2024.03.07

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Abstract PDF: Background
Among other structures, nuclear grooves are vastly found in papillary thyroid carcinoma (PTC). Considering that the application of artificial intelligence in thyroid cytology has potential for diagnostic routine, our goal was to develop a new supervised convolutional neural network capable of identifying nuclear grooves in Diff-Quik stained whole-slide images (WSI) obtained from thyroid fineneedle aspiration.
Methods
We selected 22 Diff-Quik stained cytological slides with cytological diagnosis of PTC and concordant histological diagnosis. Each of the slides was scanned, forming a WSI. Images that contained the region of interest were obtained, followed by pre-formatting, annotation of the nuclear grooves and data augmentation techniques. The final dataset was divided into training and validation groups in a 7:3 ratio.
Results
This is the first artificial intelligence model based on object detection applied to nuclear structures in thyroid cytopathology. A total of 7,255 images were obtained from 22 WSI, totaling 7,242 annotated nuclear grooves. The best model was obtained after it was submitted 15 times with the train dataset (14th epoch), with 67% true positives, 49.8% for sensitivity and 43.1% for predictive positive value.
Conclusions
The model was able to develop a structure predictor rule, indicating that the application of an artificial intelligence model based on object detection in the identification of nuclear grooves is feasible. Associated with a reduction in interobserver variability and in time per slide, this demonstrates that nuclear evaluation constitutes one of the possibilities for refining the diagnosis through computational models.

Case Study

EWSR1 rearranged primary renal myoepithelial carcinoma: a diagnostic conundrum: Nilay Nishith, Zachariah Chowdhury; J Pathol Transl Med. 2023;57(5):284-288. Published online September 15, 2023; DOI: https://doi.org/10.4132/jptm.2023.08.08

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Abstract PDF: Primary renal myoepithelial carcinoma is an exceedingly rare neoplasm with an aggressive phenotype and Ewing sarcoma breakpoint region 1 (EWSR1) rearrangement in a small fraction of cases. In addition to its rarity, the diagnosis can be challenging for the pathologist due to morphologic heterogeneity, particularly on the biopsy specimen. At times, immunohistochemistry may be indecisive; therefore, molecular studies should be undertaken for clinching the diagnosis. We aim to illustrate a case of primary myoepithelial carcinoma of the kidney with EWSR1-rearrangement in a 67-year-old male patient who presented with right supraclavicular mass, which was clinically diagnosed as carcinoma of an unknown primary. An elaborate immunohistochemical work-up aided by fluorescent in-situ hybridization allowed us to reach a conclusive diagnosis. This unusual case report advocates that one should be aware of the histological mimickers and begin with broad differential diagnoses alongside sporadic ones and then narrow them down with appropriate ancillary studies.

Original Article

Loss of aquaporin-1 expression is associated with worse clinical outcomes in clear cell renal cell carcinoma: an immunohistochemical study: Seokhyeon Lee, Bohyun Kim, Minsun Jung, Kyung Chul Moon; J Pathol Transl Med. 2023;57(4):232-237. Published online July 11, 2023; DOI: https://doi.org/10.4132/jptm.2023.06.17

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Abstract PDF

Background
Aquaporin (AQP) expression has been investigated in various malignant neoplasms, and the overexpression of AQP is related to poor prognosis in some malignancies. However, the expression of AQP protein in clear cell renal cell carcinoma (ccRCC) has not been extensively investigated by immunohistochemistry with large sample size.
Methods
We evaluated the AQP expression in 827 ccRCC with immunohistochemical staining in tissue microarray blocks and classified the cases into two categories, high and low expression.
Results
High expression of aquaporin-1 (AQP1) was found in 320 cases (38.7%), but aquaporin-3 was not expressed in ccRCC. High AQP1 expression was significantly related to younger age, low TNM stage, low World Health Organization/International Society of Urologic Pathology nuclear grade, and absence of distant metastasis. Furthermore, high AQP1 expression was also significantly associated with longer overall survival (OS; p<.001) and progression-specific survival (PFS; p<.001) and was an independent predictor of OS and PFS in ccRCC.
Conclusions
Our study revealed the prognostic significance of AQP1 protein expression in ccRCC. These findings could be applied to predict the prognosis of ccRCC.

Citations

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Serum Exosomal MiR-874 as a Potential Biomarker for Nonsmall Cell Lung Cancer Diagnosis and Prognosis
Amal F. Gharib, Saad S. Al-Shehri, Abdulraheem Almalki, Ayman Alhazmi, Mamdouh Allahyani, Ahmed Alghamdi, Amani A. Alrehaili, Maha M. Bakhuraysah, Althobaiti Naif Saad M., Weal H. Elsawy
Indian Journal of Medical and Paediatric Oncology.2024;[Epub] CrossRef

Review

Noninvasive follicular thyroid neoplasm with papillary-like nuclear features: its updated diagnostic criteria, preoperative cytologic diagnoses and impact on the risk of malignancy: Hee Young Na, So Yeon Park; J Pathol Transl Med. 2022;56(6):319-325. Published online November 9, 2022; DOI: https://doi.org/10.4132/jptm.2022.09.29

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Abstract PDF

Due to the extremely indolent behavior, a subset of noninvasive encapsulated follicular variant papillary thyroid carcinomas has been classified as “noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP)” since 2016 and is no longer considered carcinoma. Since the introduction of this new terminology, changes and refinements have been made in diagnostic criteria. Initially, the incidence of NIFTP was estimated substantial. However, the reported incidence of NIFTP varies greatly among studies and regions, with higher incidence in North American and European countries than in Asian countries. Thus, the changes in the risk of malignancy (ROM) in the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) differ inevitably among regions. Because more conservative surgery is recommended for NIFTPs, distinguishing NIFTPs from papillary thyroid carcinomas in preoperative fine-needle aspiration cytology became one of the major concerns. This review will provide comprehensive overview of updates on diagnostic criteria, actual incidence and preoperative cytologic diagnoses of NIFTP, and its impact on the ROM in TBSRTC.

Citations

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Papillae, psammoma bodies, and/or many nuclear pseudoinclusions are helpful criteria but should not be required for a definitive cytologic diagnosis of papillary thyroid carcinoma: An institutional experience of 207 cases with surgical follow up
Tarik M. Elsheikh, Matthew Thomas, Jennifer Brainard, Jessica Di Marco, Erica Manosky, Bridgette Springer, Dawn Underwood, Deborah J. Chute
Cancer Cytopathology.2024; 132(6): 348. CrossRef
ThyroSeq overview on indeterminate thyroid nodules: An institutional experience
Sam Sirotnikov, Christopher C. Griffith, Daniel Lubin, Chao Zhang, Nabil F. Saba, Dehong Li, Amanda Kornfield, Amy Chen, Qiuying Shi
Diagnostic Cytopathology.2024; 52(7): 353. CrossRef
Oncocytic Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features: A Case Report
Kaveripakam Ajay Joseph, Sana Ahuja, Sufian Zaheer
Indian Journal of Surgical Oncology.2024;[Epub] CrossRef
Cytologic hallmarks and differential diagnosis of papillary thyroid carcinoma subtypes
Agnes Stephanie Harahap, Chan Kwon Jung
Journal of Pathology and Translational Medicine.2024; 58(6): 265. CrossRef
Preoperative evaluation of thyroid nodules – Diagnosis and management strategies
Tapoi Dana Antonia, Lambrescu Ioana Maria, Gheorghisan-Galateanu Ancuta-Augustina
Pathology - Research and Practice.2023; 246: 154516. CrossRef
Reevaluating diagnostic categories and associated malignancy risks in thyroid core needle biopsy
Chan Kwon Jung
Journal of Pathology and Translational Medicine.2023; 57(4): 208. CrossRef
Strategies for Treatment of Thyroid Cancer
Deepika Yadav, Pramod Kumar Sharma, Rishabha Malviya, Prem Shankar Mishra
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Identification of NIFTP-Specific mRNA Markers for Reliable Molecular Diagnosis of Thyroid Tumors
So-Yeon Lee, Jong-Lyul Park, Kwangsoon Kim, Ja Seong Bae, Jae-Yoon Kim, Seon-Young Kim, Chan Kwon Jung
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Original Articles

Diagnostic distribution and pitfalls of glandular abnormalities in cervical cytology: a 25-year single-center study: Jung-A Sung, Ilias P. Nikas, Haeryoung Kim, Han Suk Ryu, Cheol Lee; J Pathol Transl Med. 2022;56(6):354-360. Published online November 9, 2022; DOI: https://doi.org/10.4132/jptm.2022.09.05

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Abstract PDF

Background
Detection of glandular abnormalities in Papanicolaou (Pap) tests is challenging. This study aimed to review our institute’s experience interpreting such abnormalities, assess cytohistologic concordance, and identify cytomorphologic features associated with malignancy in follow-up histology.
Methods
Patients with cytologically-detected glandular lesions identified in our pathology records from 1995 to 2020 were included in this study.
Results
Of the 683,197 Pap tests performed, 985 (0.144%) exhibited glandular abnormalities, 657 of which had tissue follow-up available. One hundred eighty-eight cases were cytologically interpreted as adenocarcinoma and histologically diagnosed as malignant tumors of various origins. There were 213 cases reported as atypical glandular cells (AGC) and nine cases as adenocarcinoma in cytology, yet they were found to be benign in follow-up histology. In addition, 48 cases diagnosed with AGC and six with adenocarcinoma cytology were found to have cervical squamous lesions in follow-up histology, including four squamous cell carcinomas. Among the cytomorphological features examined, nuclear membrane irregularity, three-dimensional clusters, single-cell pattern, and presence of mitoses were associated with malignant histology in follow-up.
Conclusions
This study showed our institute’s experience detecting glandular abnormalities in cervical cytology over a 25-year period, revealing the difficulty of this task. Nonetheless, the present study indicates that several cytological findings such as membrane irregularity, three-dimensional clusters, single-cell pattern, and evidence of proliferation could help distinguishing malignancy from a benign lesion.

Citations

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Analysis of atypical glandular cells in ThinPrep Pap smear and follow-up histopathology
Tengfei Wang, Yinan Hua, Lina Liu, Bing Leng
Baylor University Medical Center Proceedings.2024; 37(3): 403. CrossRef

Cytopathologic features of human papillomavirus–independent, gastric-type endocervical adenocarcinoma: Min-Kyung Yeo, Go Eun Bae, Dong-Hyun Kim, In-Ock Seong, Kwang-Sun Suh; J Pathol Transl Med. 2022;56(5):260-269. Published online September 13, 2022; DOI: https://doi.org/10.4132/jptm.2022.07.05

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Abstract PDF

Background
Gastric-type endocervical adenocarcinoma (GEA) is unrelated to human papillomavirus (HPV) infection and is clinically aggressive compared with HPV-associated usual-type endocervical adenocarcinoma (UEA). The cytological diagnosis falls short of a definitive diagnosis of GEA and is often categorized as atypical glandular cells (AGCs). To improve cytologic recognition, cytological findings of HPV-independent GEA were analyzed and the results compared with HPV-associated UEA.
Methods
Cervical Papanicolaou (Pap) smears from eight patients with a histopathologic diagnosis of GEA and 12 control cases of UEA were reviewed. All slides were conventionally prepared and/or liquid-based prepared (ThinPrep) and stained following the Pap method. A mucinous background, architectural, nuclear, and cytoplasmic features were analyzed and compared with UEA.
Results
Preoperative cytologic diagnoses of the eight GEA cases were AGCs, favor neoplastic in three cases, adenocarcinoma in situ in one case, and adenocarcinoma in four cases. Cytologically, monolayered honeycomb-like sheets (p = .002) of atypical endocervical cells with vacuolar granular cytoplasm (p = .001) were extensive in GEA, and three-dimensional clusters (p = .010) were extensive in UEA. Although the differences were not statistically significant, background mucin (p = .058), vesicular nuclei (p = .057), and golden-brown intracytoplasmic mucin (p = .089) were also discriminatory findings for GEA versus UEA.
Conclusions
Although GEA is difficult to diagnose on cytologic screening, GEA can be recognized based on cytologic features of monolayered honeycomb sheets of atypical endocervical cells with abundant vacuolar cytoplasm and some golden-brown intracytoplasmic mucin. UEA cases are characterized by three-dimensional clusters.

Citations

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Risk Factors Affecting Clinical Outcomes of Low-risk Early-stage Human Papillomavirus–Associated Endocervical Adenocarcinoma Treated by Surgery Alone: Application of Silva Pattern
Bong Kyung Bae, Hyunsik Bae, Won Kyung Cho, Byoung-Gie Kim, Chel Hun Choi, Tae-Joong Kim, Yoo-Young Lee, Jeong-Won Lee, Hyun-Soo Kim, Won Park
International Journal of Gynecological Pathology.2024; 43(5): 447. CrossRef
Tall‐columnar glandular cells in SurePath™ liquid‐based cytology Pap sample: Learning from mimics/pitfalls
Nalini Gupta, Vanita Jain, Radhika Srinivasan, Tulika Singh
Cytopathology.2024; 35(4): 510. CrossRef

Deep learning for computer-assisted diagnosis of hereditary diffuse gastric cancer: Sean A. Rasmussen, Thomas Arnason, Weei-Yuarn Huang; J Pathol Transl Med. 2021;55(2):118-124. Published online January 22, 2021; DOI: https://doi.org/10.4132/jptm.2020.12.22

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Abstract PDF

Background
Patients with hereditary diffuse gastric cancer often undergo prophylactic gastrectomy to minimize cancer risk. Because intramucosal poorly cohesive carcinomas in this setting are typically not grossly visible, many pathologists assess the entire gastrectomy specimen microscopically. With 150 or more slides per case, this is a major time burden for pathologists. This study utilizes deep learning methods to analyze digitized slides and detect regions of carcinoma.
Methods
Prophylactic gastrectomy specimens from seven patients with germline CDH1 mutations were analyzed (five for training/validation and two for testing, with a total of 133 tumor foci). All hematoxylin and eosin slides containing cancer foci were digitally scanned, and patches of size 256×256 pixels were randomly extracted from regions of cancer as well as from regions of normal background tissue, resulting in 15,851 images for training/validation and 970 images for testing. A model with DenseNet-169 architecture was trained for 150 epochs, then evaluated on images from the test set. External validation was conducted on 814 images scanned at an outside institution.
Results
On individual patches, the trained model achieved a receiver operating characteristic (ROC) area under the curve (AUC) of 0.9986. This enabled it to maintain a sensitivity of 90% with a false-positive rate of less than 0.1%. On the external validation dataset, the model achieved a similar ROC AUC of 0.9984. On whole slide images, the network detected 100% of tumor foci and correctly eliminated an average of 99.9% of the non-cancer slide area from consideration.
Conclusions
Overall, our model shows encouraging progress towards computer-assisted diagnosis of hereditary diffuse gastric cancer.

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Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review
Marianne Linley L. Sy-Janairo, Jose Isagani B. Janairo
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Guoyang Zhang, Jingjing Song, Zongfeng Feng, Wentao Zhao, Pan Huang, Li Liu, Yang Zhang, Xufeng Su, Yukang Wu, Yi Cao, Zhengrong Li, Zhigang Jie
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Anqi Wang, Jieli Zhou, Gang Wang, Beibei Zhang, Hongyi Xin, Haiyang Zhou
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Using Deep Learning to Predict Final HER2 Status in Invasive Breast Cancers That are Equivocal (2+) by Immunohistochemistry
Sean A. Rasmussen, Valerie J. Taylor, Alexi P. Surette, Penny J. Barnes, Gillian C. Bethune
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A machine-learning expert-supporting system for diagnosis prediction of lymphoid neoplasms using a probabilistic decision-tree algorithm and immunohistochemistry profile database: Yosep Chong, Ji Young Lee, Yejin Kim, Jingyun Choi, Hwanjo Yu, Gyeongsin Park, Mee Yon Cho, Nishant Thakur; J Pathol Transl Med. 2020;54(6):462-470. Published online August 31, 2020; DOI: https://doi.org/10.4132/jptm.2020.07.11

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Abstract PDF Supplementary Material

Background
Immunohistochemistry (IHC) has played an essential role in the diagnosis of hematolymphoid neoplasms. However, IHC interpretations can be challenging in daily practice, and exponentially expanding volumes of IHC data are making the task increasingly difficult. We therefore developed a machine-learning expert-supporting system for diagnosing lymphoid neoplasms.
Methods
A probabilistic decision-tree algorithm based on the Bayesian theorem was used to develop mobile application software for iOS and Android platforms. We tested the software with real data from 602 training and 392 validation cases of lymphoid neoplasms and compared the precision hit rates between the training and validation datasets.
Results
IHC expression data for 150 lymphoid neoplasms and 584 antibodies was gathered. The precision hit rates of 94.7% in the training data and 95.7% in the validation data for lymphomas were not statistically significant. Results in most B-cell lymphomas were excellent, and generally equivalent performance was seen in T-cell lymphomas. The primary reasons for lack of precision were atypical IHC profiles for certain cases (e.g., CD15-negative Hodgkin lymphoma), a lack of disease-specific markers, and overlapping IHC profiles of similar diseases.
Conclusions
Application of the machine-learning algorithm to diagnosis precision produced acceptable hit rates in training and validation datasets. Because of the lack of origin- or disease- specific markers in differential diagnosis, contextual information such as clinical and histological features should be taken into account to make proper use of this system in the pathologic decision-making process.

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Enhanced Immunohistochemistry Interpretation with a Machine Learning-Based Expert System
Anca Iulia Neagu, Diana Gina Poalelungi, Ana Fulga, Marius Neagu, Iuliu Fulga, Aurel Nechita
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Shi-Xuan Wang, Zou-Fang Huang, Jing Li, Yin Wu, Jun Du, Ting Li
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Jamshid Abdul-Ghafar, Kyung Jin Seo, Hye-Ra Jung, Gyeongsin Park, Seung-Sook Lee, Yosep Chong
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Dai Chihara, Loretta J. Nastoupil, Christopher R. Flowers
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Recent Application of Artificial Intelligence in Non-Gynecological Cancer Cytopathology: A Systematic Review
Nishant Thakur, Mohammad Rizwan Alam, Jamshid Abdul-Ghafar, Yosep Chong
Cancers.2022; 14(14): 3529. CrossRef
Diagnosis prediction of tumours of unknown origin using ImmunoGenius, a machine learning-based expert system for immunohistochemistry profile interpretation
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Review

Introduction to digital pathology and computer-aided pathology: Soojeong Nam, Yosep Chong, Chan Kwon Jung, Tae-Yeong Kwak, Ji Youl Lee, Jihwan Park, Mi Jung Rho, Heounjeong Go; J Pathol Transl Med. 2020;54(2):125-134. Published online February 13, 2020; DOI: https://doi.org/10.4132/jptm.2019.12.31

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Abstract PDF

Digital pathology (DP) is no longer an unfamiliar term for pathologists, but it is still difficult for many pathologists to understand the engineering and mathematics concepts involved in DP. Computer-aided pathology (CAP) aids pathologists in diagnosis. However, some consider CAP a threat to the existence of pathologists and are skeptical of its clinical utility. Implementation of DP is very burdensome for pathologists because technical factors, impact on workflow, and information technology infrastructure must be considered. In this paper, various terms related to DP and computer-aided pathologic diagnosis are defined, current applications of DP are discussed, and various issues related to implementation of DP are outlined. The development of computer-aided pathologic diagnostic tools and their limitations are also discussed.

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Original Articles

Comparison of papanicolaou smear and human papillomavirus (HPV) test as cervical screening tools: can we rely on HPV test alone as a screening method? An 11-year retrospective experience at a single institution: Myunghee Kang, Seung Yeon Ha, Hyun Yee Cho, Dong Hae Chung, Na Rae Kim, Jungsuk An, Sangho Lee, Jae Yeon Seok, Juhyeon Jeong; J Pathol Transl Med. 2020;54(1):112-118. Published online January 15, 2020; DOI: https://doi.org/10.4132/jptm.2019.11.29

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Abstract PDF

Background
The decrease in incidence of cervical dysplasia and carcinoma has not been as dramatic as expected with the development of improved research tools and test methods. The human papillomavirus (HPV) test alone has been suggested for screening in some countries. The National Cancer Screening Project in Korea has applied Papanicolaou smears (Pap smears) as the screening method for cervical dysplasia and carcinoma. We evaluated the value of Pap smear and HPV testing as diagnostic screening tools in a single institution.
Methods
Patients co-tested with HPV test and Pap smear simultaneously or within one month of each other were included in this study. Patients with only punch biopsy results were excluded because of sampling errors. A total of 999 cases were included, and the collected reports encompassed results of smear cytology, HPV subtypes, and histologic examinations.
Results
Sensitivity and specificity of detecting high-grade squamous intraepithelial lesion (HSIL) and squamous cell carcinoma (SCC) were higher for Pap smears than for HPV tests (sensitivity, 97.14%; specificity, 85.58% for Pap smears; sensitivity, 88.32%; specificity, 54.92% for HPV tests). HPV tests and Pap smears did not differ greatly in detection of low-grade squamous intraepithelial lesion (85.35% for HPV test, 80.31% for Pap smears). When atypical glandular cells were noted on Pap smears, the likelihood for histologic diagnosis of adenocarcinoma following Pap smear was higher than that of high-risk HPV test results (18.8 and 1.53, respectively).
Conclusions
Pap smears were more useful than HPV tests in the diagnosis of HSIL, SCC, and glandular lesions.

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Challenges in the diagmosis of cervical pathologies
D. Y. Chernov, O. A. Tikhonovskaya, S. V. Logvinov, I. A. Petrov, Y. S. Yuriev, A. A. Zhdankina, A. V. Gerasimov, I. V. Zingalyuk, G. A. Mikheenko
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Role of Self-Sampling for Cervical Cancer Screening: Diagnostic Test Properties of Three Tests for the Diagnosis of HPV in Rural Communities of Cuenca, Ecuador
Bernardo Vega Crespo, Vivian Alejandra Neira, José Ortíz Segarra, Ruth Maldonado Rengel, Diana López, María Paz Orellana, Andrea Gómez, María José Vicuña, Jorge Mejía, Ina Benoy, Tesifón Parrón Carreño, Veronique Verhoeven
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A Multi-institutional Study of Prevalence and Clinicopathologic Features of Non-invasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP) in Korea: Ja Yeong Seo, Ji Hyun Park, Ju Yeon Pyo, Yoon Jin Cha, Chan Kwon Jung, Dong Eun Song, Jeong Ja Kwak, So Yeon Park, Hee Young Na, Jang-Hee Kim, Jae Yeon Seok, Hee Sung Kim, Soon Won Hong; J Pathol Transl Med. 2019;53(6):378-385. Published online October 21, 2019; DOI: https://doi.org/10.4132/jptm.2019.09.18

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Abstract PDF

Background
In the present multi-institutional study, the prevalence and clinicopathologic characteristics of non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) were evaluated among Korean patients who underwent thyroidectomy for papillary thyroid carcinoma (PTC).
Methods
Data from 18,819 patients with PTC from eight university hospitals between January 2012 and February 2018 were retrospectively evaluated. Pathology reports of all PTCs and slides of potential NIFTP cases were reviewed. The strict criterion of no papillae was applied for the diagnosis of NIFTP. Due to assumptions regarding misclassification of NIFTP as non-PTC tumors, the lower boundary of NIFTP prevalence among PTCs was estimated. Mutational analysis for BRAF and three RAS isoforms was performed in 27 randomly selected NIFTP cases.
Results
The prevalence of NIFTP was 1.3% (238/18,819) of all PTCs when the same histologic criteria were applied for NIFTP regardless of the tumor size but decreased to 0.8% (152/18,819) when tumors ≥1 cm in size were included. The mean follow-up was 37.7 months and no patient with NIFTP had evidence of lymph node metastasis, distant metastasis, or disease recurrence during the follow-up period. A difference in prevalence of NIFTP before and after NIFTP introduction was not observed. BRAF^V600E mutation was not found in NIFTP. The mutation rate for the three RAS genes was 55.6% (15/27).
Conclusions
The low prevalence and indolent clinical outcome of NIFTP in Korea was confirmed using the largest number of cases to date. The introduction of NIFTP may have a small overall impact in Korean practice.

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Review

Artificial Intelligence in Pathology: Hye Yoon Chang, Chan Kwon Jung, Junwoo Isaac Woo, Sanghun Lee, Joonyoung Cho, Sun Woo Kim, Tae-Yeong Kwak; J Pathol Transl Med. 2019;53(1):1-12. Published online December 28, 2018; DOI: https://doi.org/10.4132/jptm.2018.12.16

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1,220 Download
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Abstract PDF

As in other domains, artificial intelligence is becoming increasingly important in medicine. In particular,deep learning-based pattern recognition methods can advance the field of pathology byincorporating clinical, radiologic, and genomic data to accurately diagnose diseases and predictpatient prognoses. In this review, we present an overview of artificial intelligence, the brief historyof artificial intelligence in the medical domain, recent advances in artificial intelligence applied topathology, and future prospects of pathology driven by artificial intelligence.

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Original Articles

Quilty Lesions in the Endomyocardial Biopsies after Heart Transplantation: Haeyon Cho, Jin-Oh Choi, Eun-Seok Jeon, Jung-Sun Kim; J Pathol Transl Med. 2019;53(1):50-56. Published online December 26, 2018; DOI: https://doi.org/10.4132/jptm.2018.11.30

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125 Download
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Abstract PDF Supplementary Material

Background
The aim of this study was to investigate the clinical significance of Quilty lesions in endomyocardial biopsies (EMBs) of cardiac transplantation patients.
Methods
A total of 1190EMBs from 117 cardiac transplantation patients were evaluated histologically for Quilty lesions,acute cellular rejection, and antibody-mediated rejection. Cardiac allograft vasculopathy wasdiagnosed by computed tomography coronary angiography. Clinical information, including thepatients’ survival was retrieved by a review of medical records.
Results
Eighty-eight patients(75.2%) were diagnosed with Quilty lesions, which were significantly associated with acute cellularrejection, but not with acute cellular rejection ≥ 2R or antibody-mediated rejection. In patientsdiagnosed with both Quilty lesions and acute cellular rejection, the time-to-onset of Quilty lesionsfrom transplantation was longer than that of acute cellular rejections. We found a significant associationbetween Quilty lesions and cardiac allograft vasculopathy. No significant relationship wasfound between Quilty lesions and the patients’ survival.
Conclusions
Quilty lesion may be an indicator of previous acute cellular rejection rather than a predictor for future acute cellular rejection.

Citations

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The human myocardium harbors a population of naive B-cells with a distinctive gene expression signature conserved across species
Kevin C. Bermea, Nicolas Kostelecky, Sylvie T. Rousseau, Chieh-Yu Lin, Luigi Adamo
Frontiers in Immunology.2022;[Epub] CrossRef
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Tao Lu, Yiwei Huang, Yulei Qiao, Yongxing Zhang, Yu Liu
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Essentials in the diagnosis of postoperative myocardial lesions similar to or unrelated to rejection in heart transplant
Costel Dumitru, Ancuta Zazgyva, Adriana Habor, Ovidiu Cotoi, Horațiu Suciu, Carmen Cotrutz, Bogdan Grecu, Ileana Anca Sin
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Fazal Shafiq, Yixuan Wang, Geng Li, Zongtao Liu, Fei Li, Ying Zhou, Li Xu, Xingjian Hu, Nianguo Dong
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The XVth Banff Conference on Allograft Pathology the Banff Workshop Heart Report: Improving the diagnostic yield from endomyocardial biopsies and Quilty effect revisited
Jean-Paul Duong Van Huyen, Marny Fedrigo, Gregory A. Fishbein, Ornella Leone, Desley Neil, Charles Marboe, Eliot Peyster, Jan von der Thüsen, Alexandre Loupy, Michael Mengel, Monica P. Revelo, Benjamin Adam, Patrick Bruneval, Annalisa Angelini, Dylan V. M
American Journal of Transplantation.2020; 20(12): 3308. CrossRef

Loss of Nuclear BAP1 Expression Is Associated with High WHO/ISUP Grade in Clear Cell Renal Cell Carcinoma: Young Chan Wi, Ahrim Moon, Min Jung Jung, Yeseul Kim, Seong Sik Bang, Kiseok Jang, Seung Sam Paik, Su-Jin Shin; J Pathol Transl Med. 2018;52(6):378-385. Published online October 1, 2018; DOI: https://doi.org/10.4132/jptm.2018.09.21

7,693 View
213 Download
12 Web of Science
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Abstract PDF

Background
BRCA1-associated protein 1 (BAP1) mutations are frequently reported in clear cell renal cell carcinoma (ccRCC); however, very few studies have evaluated the role of these mutations in other renal cell carcinoma (RCC) subtypes. Therefore, we analyzed BAP1 protein expression using immunohistochemistry in several RCC subtypes and assessed its relationship with clinicopathological characteristics of patients.
Methods
BAP1 expression was immunohistochemically evaluated in tissue microarray blocks constructed from 371 samples of RCC collected from two medical institutions. BAP1 expression was evaluated based on the extent of nuclear staining in tumor cells, and no expression or expression in < 10% of tumor cells was defined as negative.
Results
Loss of BAP1 expression was observed in ccRCC (56/300, 18.7%), chromophobe RCC (6/26, 23.1%), and clear cell papillary RCC (1/4, 25%), while we failed to detect BAP1 expression loss in papillary RCC, acquired cystic disease-associated RCC, or collecting duct carcinoma. In ccRCC, loss of BAP1 expression was significantly associated with high World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grade (p = .002); however, no significant correlation was observed between loss of BAP1 expression and survival in ccRCC. Loss of BAP1 expression showed no association with prognostic factors in chromophobe RCC.
Conclusions
Loss of BAP1 nuclear expression was observed in both ccRCC and chromophobe RCC. In addition, BAP1 expression loss was associated with poor prognostic factors such as high WHO/ISUP grade in ccRCC.

Citations

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