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Diagnostics
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New Insights into the Diagnosis of Gynecological Diseases
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New Insights into the Diagnosis of Gynecological Diseases

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 5255

Special Issue Editor

Prof. Dr. Dah Ching Ding

E-Mail Website
Guest Editor
Department of Obstetrics and Gynecology, Hualien Tzu Chi Hospital, Hualien 970, Taiwan
Interests: obstetrics; gynecology

Special Issue Information

Dear Colleagues,

Advancements in the diagnosis of gynecological diseases have ushered in a new era of precision medicine, enabling earlier detection, improved prognostic accuracy, and tailored treatment strategies. With the integration of novel biomarkers, cutting-edge imaging technologies, and artificial-intelligence-driven tools, the landscape of gynecological diagnostics is rapidly evolving. These innovations address longstanding challenges associated with conditions such as ovarian cancer, endometriosis, uterine fibroids, and gynecological infections, where early and accurate diagnosis remains pivotal for optimal patient outcomes. This Special Issue focuses on exploring these advancements, as well as highlighting breakthroughs in molecular diagnostics, next-generation sequencing, and the role of big data in enhancing clinical decision-making. By bringing together interdisciplinary research and clinical expertise, we aim to provide a comprehensive overview of the emerging trends and transformative technologies that are shaping the future of gynecological healthcare.

Prof. Dr. Dah Ching Ding
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • gynecological diseases
  • precision medicine
  • molecular diagnostics
  • artificial intelligence
  • biomarkers
  • next-generation sequencing
  • imaging technologies
  • big data

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Published Papers (4 papers)

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Research

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13 pages, 2759 KiB  
Article
A Novel Serum-Based Bioassay for Quantification of Cancer-Associated Transformation Activity: A Case–Control and Animal Study
by Aye Aye Khine, Hsuan-Shun Huang, Pao-Chu Chen, Chun-Shuo Hsu, Ying-Hsi Chen, Sung-Chao Chu and Tang-Yuan Chu
Diagnostics 2025, 15(15), 1975; https://doi.org/10.3390/diagnostics15151975 - 6 Aug 2025
Viewed by 270
Abstract
Background/Objectives: The detection of ovarian cancer remains challenging due to the lack of reliable serum biomarkers that reflect malignant transformation rather than mere tumor presence. We developed a novel biotest using an immortalized human fallopian tube epithelial cell line (TY), which exhibits [...] Read more.
Background/Objectives: The detection of ovarian cancer remains challenging due to the lack of reliable serum biomarkers that reflect malignant transformation rather than mere tumor presence. We developed a novel biotest using an immortalized human fallopian tube epithelial cell line (TY), which exhibits anchorage-independent growth (AIG) in response to cancer-associated serum factors. Methods: Sera from ovarian and breast cancer patients, non-cancer controls, and ID8 ovarian cancer-bearing mice were tested for AIG-promoting activity in TY cells. Results: TY cells (passage 96) effectively distinguished cancer sera from controls (68.50 ± 2.12 vs. 17.50 ± 3.54 colonies, p < 0.01) and correlated with serum CA125 levels (r = 0.73, p = 0.03) in ovarian cancer patients. Receiver operating characteristic (ROC) analysis showed high diagnostic accuracy (AUC = 0.85, cutoff: 23.75 colonies). The AIG-promoting activity was mediated by HGF/c-MET and IGF/IGF-1R signaling, as inhibition of these pathways reduced phosphorylation and AIG. In an ID8 mouse ovarian cancer model, TY-AIG colonies strongly correlated with tumor burden (r = 0.95, p < 0.01). Conclusions: Our findings demonstrate that the TY cell-based AIG assay is a sensitive and specific biotest for detecting ovarian cancer and potentially other malignancies, leveraging the fundamental hallmark of malignant transformation. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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16 pages, 1322 KiB  
Article
Perioperative Risk Prediction in Major Gynaecological Oncology Surgery: A National Diagnostic Survey of UK Clinical Practice
by Lusine Sevinyan, Anil Tailor, Pradeep Prabhu, Peter Williams, Melanie Flint and Thumuluru Kavitha Madhuri
Diagnostics 2025, 15(13), 1723; https://doi.org/10.3390/diagnostics15131723 - 6 Jul 2025
Viewed by 451
Abstract
Background: Gynaecological oncology (GO) surgery involves a wide range of procedures, from minor diagnostic interventions to highly complex cytoreductive operations. Accurate perioperative diagnostics—particularly in major surgery—are critical to optimise patient care, predict morbidity, and facilitate shared decision-making. This study aimed to evaluate [...] Read more.
Background: Gynaecological oncology (GO) surgery involves a wide range of procedures, from minor diagnostic interventions to highly complex cytoreductive operations. Accurate perioperative diagnostics—particularly in major surgery—are critical to optimise patient care, predict morbidity, and facilitate shared decision-making. This study aimed to evaluate current practices in perioperative risk assessment amongst UK GO specialists, focusing on the use, perception, and applicability of diagnostic risk prediction tools. Methods: A national multicentre survey was distributed via the British Gynaecological Cancer Society (BGCS) to consultants, trainees, and nurse specialists. The questionnaire examined clinician familiarity with and use of existing tools such as POSSUM, P-POSSUM, and ACS NSQIP, as well as perceived reliability and areas for improvement. Results: Fifty-four clinicians responded, two-thirds of whom were consultant gynaecological oncologists. While 51.9% used morbidity prediction tools selectively, only 7.4% used them routinely for all major surgeries. The most common models were P-POSSUM (39.6%) and ACS NSQIP (25%), though over 20% did not use any formal tool. Despite this, 80% of respondents expressed a desire for more accurate, GO-specific models. Conclusions: This study reveals a gap between available perioperative diagnostics and real-world clinical use in GO surgical planning. There is an urgent need for validated, user-friendly, and GO-specific risk prediction tools—particularly for high-risk, complex surgical cases. Further research should focus on prospective validation of tools such as ACS NSQIP and their integration into routine practice to improve outcomes in gynaecological oncology. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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Review

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17 pages, 13655 KiB  
Review
Molar Pregnancy: Early Diagnosis, Clinical Management, and the Role of Referral Centers
by Antônio Braga, Lohayne Coutinho, Marcela Chagas, Juliana Pereira Soares, Gustavo Yano Callado, Raphael Alevato, Consuelo Lozoya, Sue Yazaki Sun, Edward Araujo Júnior and Jorge Rezende-Filho
Diagnostics 2025, 15(15), 1953; https://doi.org/10.3390/diagnostics15151953 - 4 Aug 2025
Viewed by 298
Abstract
Molar pregnancy (MP) is a gestational disorder resulting from abnormal fertilization, leading to atypical trophoblastic proliferation and the formation of a complete or partial hydatidiform mole. This condition represents the most common form of gestational trophoblastic disease (GTD) and carries a significant risk [...] Read more.
Molar pregnancy (MP) is a gestational disorder resulting from abnormal fertilization, leading to atypical trophoblastic proliferation and the formation of a complete or partial hydatidiform mole. This condition represents the most common form of gestational trophoblastic disease (GTD) and carries a significant risk of progression to gestational trophoblastic neoplasia (GTN). Although rare in high-income countries, MP remains up to ten times more prevalent in low-income and developing countries, contributing to preventable maternal morbidity and mortality. This narrative review provides an updated, practical overview of the clinical presentation, diagnosis, treatment, and follow-up of MP. A key focus is the challenge of early diagnosis, particularly given the increasing frequency of first-trimester detection, where classical histopathological criteria may be subtle, leading to diagnostic errors. The review innovates by integrating advanced diagnostic methods—combining histopathology, immunohistochemistry using p57Kip2, Ki-67, and p53 markers, along with cytogenetic analysis—to improve diagnostic accuracy in early gestation. The central role of referral centers is also emphasized, not only in facilitating timely treatment and access to chemotherapy, but also in implementing standardized post-molar follow-up protocols that reduce progression to GTN and maternal mortality. By focusing on both advanced diagnostic strategies and the organization of care through referral centers, this review offers a comprehensive, practice-oriented perspective to optimize patient outcomes in GTD and address persistent care gaps in high-burden regions. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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20 pages, 371 KiB  
Review
Early Diagnosis of Ovarian Cancer: A Comprehensive Review of the Advances, Challenges, and Future Directions
by Mun-Kun Hong and Dah-Ching Ding
Diagnostics 2025, 15(4), 406; https://doi.org/10.3390/diagnostics15040406 - 7 Feb 2025
Cited by 11 | Viewed by 3772
Abstract
Ovarian cancer (OC), the seventh most common cancer in women and the most lethal gynecological malignancy, is a significant global health challenge, with >324,000 new cases and >200,000 deaths being reported annually. OC is characterized by late-stage diagnosis, a poor prognosis, and 5-year [...] Read more.
Ovarian cancer (OC), the seventh most common cancer in women and the most lethal gynecological malignancy, is a significant global health challenge, with >324,000 new cases and >200,000 deaths being reported annually. OC is characterized by late-stage diagnosis, a poor prognosis, and 5-year survival rates ranging from 93% (early stage) to 20% (advanced stage). Despite advances in genomics and proteomics, effective early-stage diagnostic tools and population-wide screening strategies remain elusive, contributing to high mortality rates. The complex pathogenesis of OC involves diverse histological subtypes and genetic predispositions, including BRCA1/2 mutations; notably, a considerable proportion of OC cases have a hereditary component. Current diagnostic modalities, including imaging techniques (transvaginal ultrasound, computed/positron emission tomography, and magnetic resonance imaging) and biomarkers (CA-125 and human epididymis protein 4), with varying degrees of sensitivity and specificity, have limited efficacy in detecting early-stage OC. Emerging technologies, such as liquid biopsy, multiomics, and artificial intelligence (AI)-assisted diagnostics, may enhance early detection. Liquid biopsies using circulating tumor DNA and microRNAs are popular minimally invasive diagnostic tools. Integrated multiomics has advanced biomarker discovery. AI algorithms have improved imaging interpretation and risk prediction. Novel screening methods including organoids and multiplex panels are being explored to overcome current diagnostic limitations. This review highlights the critical need for continued research and innovation to enhance early diagnosis, reduce mortality, and improve patient outcomes in OC and posits personalized medicine, integrated emerging technologies, and targeted global initiatives and collaborative efforts, which address care access disparities and promote cost-effective, scalable screening strategies, as potential tools to combat OC. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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