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Life
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Advances in Imaging for Female Patients: Breast and Gynecological Diagnostics
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Advances in Imaging for Female Patients: Breast and Gynecological Diagnostics

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Medical Research".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1827

Special Issue Editors

Dr. Silvia Gigli

E-Mail Website
Guest Editor
Department of Diagnostic Imaging, Sandro Pertini Hospital, Via dei Monti Tiburtini, 385, 00157 Rome, Italy
Interests: mammography; breast cancer screening; ultrasound; MRI; CEM; gynecology; oncological imaging; senology
Dr. Emanuele David

E-Mail Website
Guest Editor
Radiology Unit 1, Department of Medical Surgical Sciences and Advanced Technologies “GF Ingrassia”, University Hospital “Policlinico G. Rodolico”, University of Catania, 95123 Catania, Italy
Interests: ultrasound; MRI; gynecology; head and neck; vascular; neuroradiology; musculoskeletal; senology
Special Issues, Collections and Topics in MDPI journals
Dr. Giacomo Bonito

E-Mail Website
Guest Editor
Unit of Emergency Radiology, Policlinico Umberto I Hospital, Sapienza University of Rome, Viale Regina Elena, Rome, Italy
Interests: radiology; MRI; cancer; imaging in pregnancy and puerperium

Special Issue Information

Dear Colleagues,

We are pleased to announce a forthcoming Life Special Issue dedicated to “Advances in Imaging for Female Patients: Breast and Gynecological Diagnostics”. This issue aims to highlight recent developments, challenges, and breakthroughs in imaging technologies and methodologies used in the diagnosis, staging, and management of breast and gynecological conditions. The role of imaging in women’s health continues to evolve, with innovations in modalities such as mammography, ultrasound, MRI, PET/CT, and AI-driven diagnostics significantly enhancing clinical decision-making. This Special Issue invites contributions that explore novel imaging techniques, comparative studies, AI applications, radiomics, early detection strategies, and interdisciplinary approaches to breast and pelvic imaging.

Topics of interest include, but are not limited to, the following:

  • Imaging biomarkers in breast and gynecological cancers;
  • Advances in MRI and ultrasound for pelvic pathology;
  • AI and machine learning applications in imaging for female patients;
  • Screening and diagnostic protocols for breast cancer;
  • Imaging in fertility assessment and reproductive health;
  • Radiomics and quantitative imaging in gynecology;
  • Multimodal imaging approaches and comparative effectiveness;
  • Challenges in imaging of benign vs. malignant lesions;
  • Role of imaging in treatment planning and monitoring.

We welcome original research articles, reviews, clinical studies, and case reports that provide significant insights into this important area of diagnostic medicine.

We look forward to receiving your valuable contributions to this Special Issue.

Dr. Silvia Gigli
Dr. Emanuele David
Dr. Giacomo Bonito
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Life is an international peer-reviewed open access monthly 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

  • breast cancer
  • breast screening
  • gynecological cancer
  • mammography
  • CEM
  • ultrasound
  • MRI
  • PET/TC
  • radiomics
  • artificial intelligence

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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30 pages, 3316 KB  
Article
A Novel Hybrid CNN-ViT-Based Bi-Directional Cross-Guidance Fusion-Driven Breast Cancer Detection Model
by Abdul Rahaman Wahab Sait and Yazeed Alkhurayyif
Life 2026, 16(3), 474; https://doi.org/10.3390/life16030474 - 14 Mar 2026
Viewed by 776
Abstract
Accurate and early identification of breast cancer from mammography is key to reducing breast cancer mortality, and automated analysis is challenging due to subtle lesion appearances, heterogeneous breast density, and the variance caused by modality. Standard Convolutional Neural Networks (CNNs) are excellent at [...] Read more.
Accurate and early identification of breast cancer from mammography is key to reducing breast cancer mortality, and automated analysis is challenging due to subtle lesion appearances, heterogeneous breast density, and the variance caused by modality. Standard Convolutional Neural Networks (CNNs) are excellent at capturing localized textures, whereas Vision Transformers (ViTs) capture long-range dependencies; however, both often struggle to produce a unified representation that consistently supports diagnostic decision-making. To address these limitations, this study presents a dual-stream framework integrating ConvNeXt for high-fidelity local feature extraction with Swin Transformer V2 for hierarchical global context modeling. A Bi-Directional Cross-Guidance (BDCG) mechanism is added to harmonize interactions between the two feature domains and ensure mutual information learning in the representations. Furthermore, a Prototype-Anchored Similarity Head (PASH) is used to stabilize classification using distance-based reasoning instead of using linear separation. Comprehensive experiments show the effectiveness of the proposed method using two benchmark datasets. On Dataset 1, the model achieves accuracy: 98.8%, precision: 98.7%, recall: 98.6%, and F1 score: 97.2%, outperforming existing models based on CNN, ViTs, and hybrid architectures, and provides a lower inference time (8.3 ms/image). On the more heterogeneous Dataset 2, the model maintains strong performance, with an accuracy of 97.0%, precision of 95.4%, recall of 94.8%, and F1-score of 95.1%, demonstrating its resilience to domain shift and imaging variability. These results underscore the value of structural multi-scale feature interaction and prototype-driven classification for robust mammographic analysis. The consistent performance across internal and external evaluations indicates the potential for the proposed framework to be reliably applied in computer-aided screening systems. Full article
(This article belongs to the Special Issue Advances in Imaging for Female Patients: Breast and Gynecological Diagnostics)
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Review

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20 pages, 3983 KB  
Review
Beyond the Beam: Multimodal Imaging and Surveillance of Post-Radiotherapy Changes in the Breast
by Silvia Gigli, Giacomo Bonito, Emanuele David, Corrado Spatola, Brandon M. Ascenzi, Roberta Valerieva Ninkova, Sandrine Riccardi, Lucia Malzone, Paolo Ricci and Lucia Manganaro
Life 2026, 16(4), 701; https://doi.org/10.3390/life16040701 - 21 Apr 2026
Viewed by 535
Abstract
Breast-conserving therapy, consisting of lumpectomy followed by adjuvant radiotherapy, is the standard of care for early-stage breast cancer, providing oncologic outcomes equivalent to mastectomy while preserving breast anatomy and quality of life. Radiotherapy remains a cornerstone of treatment across disease stages, significantly reducing [...] Read more.
Breast-conserving therapy, consisting of lumpectomy followed by adjuvant radiotherapy, is the standard of care for early-stage breast cancer, providing oncologic outcomes equivalent to mastectomy while preserving breast anatomy and quality of life. Radiotherapy remains a cornerstone of treatment across disease stages, significantly reducing local recurrence rates and improving long-term survival. Advances in radiotherapy techniques—including conventional fractionation, hypofractionation, tumor-bed boost delivery, and regional nodal irradiation—have optimized oncologic efficacy while inducing a broad spectrum of time-dependent morphological changes in breast tissue. Accurate imaging surveillance is therefore essential to distinguish expected post-radiotherapy changes from tumor recurrence and to avoid unnecessary diagnostic or therapeutic interventions. This review provides a comprehensive overview of contemporary breast radiotherapy protocols, their impact on post-treatment imaging appearances, and current recommendations for imaging surveillance. Characteristic findings across mammography, ultrasound, magnetic resonance imaging, and nuclear medicine modalities are discussed, with emphasis on their temporal evolution from acute inflammatory changes to chronic fibrosis, fat necrosis, and architectural distortion. Recognition of these imaging patterns, together with integration of radiotherapy-related parameters into image interpretation, is crucial for accurate diagnosis, early detection of recurrence, and informed clinical management of breast cancer survivors. Full article
(This article belongs to the Special Issue Advances in Imaging for Female Patients: Breast and Gynecological Diagnostics)
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