{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:36:38Z","timestamp":1787027798556,"version":"build-2736575974"},"reference-count":34,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,21]],"date-time":"2024-12-21T00:00:00Z","timestamp":1734739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"KAWASAKI Foundation for Medical Science and Medical Welfare","award":["JP 23K14489"],"award-info":[{"award-number":["JP 23K14489"]}]},{"name":"JSPS KAKENHI","award":["JP 23K14489"],"award-info":[{"award-number":["JP 23K14489"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: The diagnostic challenges presented by hyperchromatic crowded cell groups (HCGs) in cervical cytology often result in either overdiagnosis or underdiagnosis due to their densely packed, three-dimensional structures. The objective of this study is to characterize the structural differences among HSIL-HCGs, AGC-HCGs, and NILM-HCGs using quantitative texture analysis metrics, with the aim of facilitating the differentiation of benign from malignant cases. Methods: A total of 585 HCGs images were analyzed, with assessments conducted on 8-bit gray-scale value, thickness, skewness, and kurtosis across various groups. Results: HSIL-HCGs are distinctly classified based on 8-bit gray-scale value. Significant statistical differences were observed in all groups, with HSIL-HCGs exhibiting higher cellular density and cluster thickness compared to NILM and AGC groups. In the AGC group, HCGs shows statistically significant differences in 8-bit gray-scale value compared to NILM-HCGs, but the classification performance by 8-bit gray-scale value is not high because the cell density and thickness are almost similar. These variations reflect the characteristic cellular structures unique to each group and substantiate the potential of 8-bit gray-scale value as an objective diagnostic indicator, especially for HSIL-HCGs. Conclusion: Our findings indicate that the integration of gray-scale-based texture analysis has the potential to improve diagnostic accuracy in cervical cytology and break through current diagnostic limitations in the identification of high-risk lesions.<\/jats:p>","DOI":"10.3390\/cancers16244258","type":"journal-article","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:13:38Z","timestamp":1734945218000},"page":"4258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Quantitative Structural Analysis of Hyperchromatic Crowded Cell Groups in Cervical Cytology: Overcoming Diagnostic Pitfalls"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1723-9459","authenticated-orcid":false,"given":"Shinichi","family":"Tanaka","sequence":"first","affiliation":[{"name":"Department of Medical Technology, Kawasaki University of Medical Welfare, Kurashiki 701-0193, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tamami","family":"Yamamoto","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shikoku Cancer Center, Matsuyama 791-0245, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norihiro","family":"Teramoto","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shikoku Cancer Center, Matsuyama 791-0245, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ritu Nayar, D.C.W. (2015). The Bethesda System for Reporting Cervical Cytology. Definitions, Criteria and Explanatory Notes, Springer.","DOI":"10.1007\/978-3-319-11074-5"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.1111\/j.1471-0528.2005.00699.x","article-title":"The comparative diagnostic accuracy of conventional and liquid-based cytology in a colposcopic setting","volume":"112","author":"Hussein","year":"2005","journal-title":"BJOG Int. J. Obstet. Gynaecol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/j.ygyno.2008.12.012","article-title":"Superior performance of liquid-based versus conventional cytology in a population-based cervical cancer screening program","volume":"112","author":"Beerman","year":"2009","journal-title":"Gynecol. Oncol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/S0090-8258(03)00176-8","article-title":"Performance of ThinPrep liquid-based cervical cytology in comparison with conventionally prepared Papanicolaou smears: A quantitative survey","volume":"90","author":"Abulafia","year":"2003","journal-title":"Gynecol. Oncol."},{"key":"ref_5","first-page":"S36","article-title":"Hyperchromatic crowded groups: Pitfalls in pap smear diagnosis","volume":"114","author":"Demay","year":"2000","journal-title":"Am. J. Clin. Pathol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/1742-6413-4-2","article-title":"Evaluation and significance of hyperchromatic crowded groups (HCG) in liquid-based paps","volume":"4","author":"Chivukula","year":"2007","journal-title":"Cytojournal"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"393","DOI":"10.4132\/jptm.2019.08.14","article-title":"Cytomorphological Features of Hyperchromatic Crowded Groups in Liquid-Based Cervicovaginal Cytology: A Single Institutional Experience","volume":"53","author":"Lee","year":"2019","journal-title":"J. Pathol. Transl. Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1008","DOI":"10.1002\/dc.24805","article-title":"The association of atypical squamous cells cannot exclude a high grade squamous intraepithelial lesion, hyperchromatic crowded groups and high grade squamous intraepithelial lesions involving endocervical glands","volume":"49","author":"Selvaggi","year":"2021","journal-title":"Diagn. Cytopathol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1159\/000539637","article-title":"Pitfalls in Gynecological Cytology: Review of the Common and Less Frequent Entities in Pap Test","volume":"68","year":"2024","journal-title":"Acta Cytol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1136\/jcp.46.8.700","article-title":"Negative cytology preceding cervical cancer: Causes and prevention","volume":"46","author":"Robertson","year":"1993","journal-title":"J. Clin. Pathol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1111\/cyt.12040","article-title":"Image analysis of hyperchromatic crowded cell groups in SurePath cervical cytology","volume":"24","author":"Evered","year":"2013","journal-title":"Cytopathology"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kanavati, F., Hirose, N., Ishii, T., Fukuda, A., Ichihara, S., and Tsuneki, M. (2022). A Deep Learning Model for Cervical Cancer Screening on Liquid-Based Cytology Specimens in Whole Slide Images. Cancers, 14.","DOI":"10.3390\/cancers14051159"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kurita, Y., Meguro, S., Tsuyama, N., Kosugi, I., Enomoto, Y., Kawasaki, H., Uemura, T., Kimura, M., and Iwashita, T. (2023). Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images. PLoS ONE, 18.","DOI":"10.1371\/journal.pone.0285996"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1002\/cncy.22669","article-title":"Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology","volume":"131","author":"Hirokawa","year":"2023","journal-title":"Cancer Cytopathol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1038\/s41591-024-02915-w","article-title":"Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning","volume":"30","author":"Tian","year":"2024","journal-title":"Nat. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1111\/cyt.13189","article-title":"The inclusion of nuclear area improves the Paris system for reporting urinary cytology","volume":"34","author":"Tanaka","year":"2023","journal-title":"Cytopathology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1111\/cyt.12998","article-title":"Quantitative cytomorphological comparison of SurePath and ThinPrep liquid-based cytology using high-grade urothelial carcinoma cells","volume":"32","author":"Okuda","year":"2021","journal-title":"Cytopathology"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kim, H., Choi, S., Do, S.-I., Lee, S.H., Yoon, N., and Kim, H.-S. (2020). Clinicopathological Characteristics of Pleomorphic High-Grade Squamous Intraepithelial Lesion of the Uterine Cervix: A Single-Institutional Series of 31 Cases. Diagnostics, 10.","DOI":"10.3390\/diagnostics10080595"},{"key":"ref_19","unstructured":"Khieu, M., and Butler, S.L. (2024). High-Grade Squamous Intraepithelial Lesion of the Cervix. StatPearls, StatPearls Publishing LLC."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"dev197657","DOI":"10.1242\/dev.197657","article-title":"Exocrine gland structure-function relationships","volume":"149","author":"Khan","year":"2022","journal-title":"Development"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.5858\/arpa.2016-0356-RA","article-title":"Cervical Adenocarcinoma: Diagnosis of Human Papillomavirus-Positive and Human Papillomavirus-Negative Tumors","volume":"141","author":"Pirog","year":"2017","journal-title":"Arch. Pathol. Lab. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1038\/modpathol.2014.55","article-title":"HPV prevalence and genotypes in different histological subtypes of cervical adenocarcinoma, a worldwide analysis of 760 cases","volume":"27","author":"Pirog","year":"2014","journal-title":"Mod. Pathol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1002\/dc.24293","article-title":"Cervical high-grade squamous intraepithelial lesion on conventional cytology: Cytological patterns, pitfalls, and diagnostic clues","volume":"47","author":"Gupta","year":"2019","journal-title":"Diagn. Cytopathol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1678","DOI":"10.1136\/ijgc-2020-001457","article-title":"HrHPV testing vs liquid-based cytology in cervical cancer screening among women aged 50 and older: A prospective study","volume":"30","author":"Andersen","year":"2020","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1111\/j.1365-2303.2012.00992.x","article-title":"Factors contributing to false-negative and potential false-negative cytology reports in SurePath\u2122 liquid-based cervical cytology","volume":"24","author":"Gupta","year":"2013","journal-title":"Cytopathology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1007\/s00404-013-3015-5","article-title":"Cervical cytology with a diagnosis of atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesion (ASC-H): A follow-up study with corresponding histology and significance of predicting dysplasia by human papillomavirus (HPV) DNA testing","volume":"289","author":"Gilani","year":"2014","journal-title":"Arch. Gynecol. Obstet."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"8476","DOI":"10.3390\/cimb45100534","article-title":"The Role of p16\/Ki67 Dual Staining in Cervical Cancer Screening","volume":"45","author":"Dovnik","year":"2023","journal-title":"Curr. Issues Mol. Biol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"245","DOI":"10.5144\/0256-4947.2016.245","article-title":"Predictive value of p16\/Ki-67 immunocytochemistry for triage of women with abnormal Papanicolaou test in cervical cancer screening: A systematic review and meta-analysis","volume":"36","author":"Chen","year":"2016","journal-title":"Ann. Saudi Med."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1002\/cncy.22103","article-title":"Meta-analysis of the accuracy of p16 or p16\/Ki-67 immunocytochemistry versus HPV testing for the detection of CIN2+\/CIN3+ in triage of women with minor abnormal cytology","volume":"127","author":"Peeters","year":"2019","journal-title":"Cancer Cytopathol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"116","DOI":"10.4103\/joc.joc_156_23","article-title":"Can Mitotic Figures in Hyperchromatic Crowded Groups be Cytodiagnostic Criteria for High-Grade Squamous Intra-epithelial Lesions?","volume":"41","author":"Suzuki","year":"2024","journal-title":"J. Cytol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hamdi, M., Senan, E.M., Awaji, B., Olayah, F., Jadhav, M.E., and Alalayah, K.M. (2023). Analysis of WSI Images by Hybrid Systems with Fusion Features for Early Diagnosis of Cervical Cancer. Diagnostics, 13.","DOI":"10.3390\/diagnostics13152538"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Karasu Benyes, Y., Welch, E.C., Singhal, A., Ou, J., and Tripathi, A. (2022). A Comparative Analysis of Deep Learning Models for Automated Cross-Preparation Diagnosis of Multi-Cell Liquid Pap Smear Images. Diagnostics, 12.","DOI":"10.3390\/diagnostics12081838"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3541","DOI":"10.1038\/s41467-021-23913-3","article-title":"Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears","volume":"12","author":"Zhu","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"}],"container-title":["Cancers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6694\/16\/24\/4258\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:57:31Z","timestamp":1760115451000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6694\/16\/24\/4258"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,21]]},"references-count":34,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["cancers16244258"],"URL":"https:\/\/doi.org\/10.3390\/cancers16244258","relation":{},"ISSN":["2072-6694"],"issn-type":[{"value":"2072-6694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,21]]}}}