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Tomography
Special Issues
New Advances in Breast Imaging
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New Advances in Breast Imaging

A special issue of Tomography (ISSN 2379-139X).

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 7404

Special Issue Editor

Dr. Daniele Tari

E-Mail Website
Guest Editor
Department of Diagnostic Senology, District 12, Caserta Local Health Authority, Caserta LHA, 81100 Caserta, Italy
Interests: breast imaging; breast cancer prevention; screening; breast interventional radiology; radiomics; breast cancer epidemiology; epidemiology and health statistics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Breast imaging is one of the most exciting subspecialties in radiology. The need for personalized medicine has changed our vision of the field, giving even more importance to multimodality and to the integration of both Artificial Intelligence and human resources. Consequently, evaluating the application of radiomics could be of particular interest. In addition, examining the real impact of the most recent advancements of standard imaging techniques, such as digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS), on breast cancer prevention could be incredibly challenging.

Contrast-enhanced spectral mammography (CESM) could be considered a true alternative to the most expensive magnetic resonance imaging (MRI). On the other side, the evaluation of fast MRI could have a great impact on breast cancer prevention, especially in young women with dense breast.

This Special Issue aims to present and discuss the most recent advancements in breast imaging. Original research articles and reviews are welcome. Research areas may include (but are not limited to) all the aforementioned topics. Articles on breast cancer screening programs are welcome, especially those dealing with DBT and ABUS. Finally, articles on breast interventional radiology, with particular regard to vacuum-assisted biopsy or excision system, are also welcome.

I look forward to receiving your contributions.

Dr. Daniele Tari
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. Tomography 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 2400 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 imaging
  • breast cancer screening
  • digital breast tomosynthesis (DBT)
  • 3D automated breast ultrasound (ABUS)
  • contrast-enhanced spectral mammography (CESM)
  • fast-MRI
  • vacuum-assisted breast biopsy (VABB)
  • breast lesion excision system (BLES)
  • radiomics
  • computer-aided detection (CAD)

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

Published Papers (3 papers)

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Editorial

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2 pages, 169 KiB  
Editorial
Special Issue “New Advances in Breast Imaging”
by Daniele Ugo Tari
Tomography 2022, 8(4), 1702-1703; https://doi.org/10.3390/tomography8040142 - 28 Jun 2022
Viewed by 1720
Abstract
Breast cancer (BC) is the most common cancer in women of all ages, with more than 2 million diagnoses every year and a high economic and psychological impact on both the health care system and the population [...] Full article
(This article belongs to the Special Issue New Advances in Breast Imaging)

Research

Jump to: Editorial

14 pages, 2268 KiB  
Article
Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network
by Timothy J. Allen, Leah C. Henze Bancroft, Kang Wang, Ping Ni Wang, Orhan Unal, Lloyd D. Estkowski, Ty A. Cashen, Ersin Bayram, Roberta M. Strigel and James H. Holmes
Tomography 2023, 9(3), 967-980; https://doi.org/10.3390/tomography9030079 - 10 May 2023
Cited by 1 | Viewed by 2258
Abstract
Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical [...] Read more.
Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical with the rise in abbreviated breast MRI exams for screening purposes. This work proposes an automated approach for the placement of scan and pre-scan volumes for breast MRI. Anatomic 3-plane scout image series and associated scan volumes were retrospectively collected from 333 clinical breast exams acquired on 10 individual MRI scanners. Bilateral pre-scan volumes were also generated and reviewed in consensus by three MR physicists. A deep convolutional neural network was trained to predict both the scan and pre-scan volumes from the 3-plane scout images. The agreement between the network-predicted volumes and the clinical scan volumes or physicist-placed pre-scan volumes was evaluated using the intersection over union, the absolute distance between volume centers, and the difference in volume sizes. The scan volume model achieved a median 3D intersection over union of 0.69. The median error in scan volume location was 2.7 cm and the median size error was 2%. The median 3D intersection over union for the pre-scan placement was 0.68 with no significant difference in mean value between the left and right pre-scan volumes. The median error in the pre-scan volume location was 1.3 cm and the median size error was −2%. The average estimated uncertainty in positioning or volume size for both models ranged from 0.2 to 3.4 cm. Overall, this work demonstrates the feasibility of an automated approach for the placement of scan and pre-scan volumes based on a neural network model. Full article
(This article belongs to the Special Issue New Advances in Breast Imaging)
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13 pages, 3315 KiB  
Article
Supine versus Prone 3D Abus Accuracy in Breast Tumor Size Evaluation
by Anna D’Angelo, Gianluca Gatta, Graziella Di Grezia, Sara Mercogliano, Francesca Ferrara, Charlotte Marguerite Lucille Trombadori, Antonio Franco, Alessandro Cina, Paolo Belli and Riccardo Manfredi
Tomography 2022, 8(4), 1997-2009; https://doi.org/10.3390/tomography8040167 - 12 Aug 2022
Cited by 1 | Viewed by 2191
Abstract
Breast-conserving surgery (BCS) with negative resection margins decreases the locoregional recurrence rate. Breast cancer size is one of the main determinants of Tumor-Node-Metastasis (TNM) staging. Our study aimed to investigate the accuracy of supine 3D automated breast ultrasound (3D ABUS) compared to prone [...] Read more.
Breast-conserving surgery (BCS) with negative resection margins decreases the locoregional recurrence rate. Breast cancer size is one of the main determinants of Tumor-Node-Metastasis (TNM) staging. Our study aimed to investigate the accuracy of supine 3D automated breast ultrasound (3D ABUS) compared to prone 3D ABUS in the evaluation of tumor size in breast cancer patient candidates for BCS. In this prospective two-center study (Groups 1 and 2), we enrolled patients with percutaneous biopsy-proven early-stage breast cancer, in the period between June 2019 and May 2020. Patients underwent hand-held ultrasound (HHUS), contrast-enhanced magnetic resonance imaging (CE-MRI) and 3D ABUS—supine 3D ABUS in Group 1 and prone 3D ABUS in Group 2. Histopathological examination (HE) was considered the reference standard. Bland–Altman analysis and plots were used. Eighty-eight patients were enrolled. Compared to prone, supine 3D ABUS showed better agreement with HE, with a slight tendency toward underestimation (mean difference of −2 mm). Supine 3D ABUS appears to be a useful tool and more accurate than HHUS in the staging of breast cancer. Full article
(This article belongs to the Special Issue New Advances in Breast Imaging)
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