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Abstract
Breast-specific positron imaging systems provide higher sensitivity than whole-body PET for breast cancer detection. The clinical applications for breast-specific positron imaging are similar to breast MRI including preoperative local staging and neoadjuvant therapy response assessment. Breast-specific positron imaging may be an alternative for patients who cannot undergo breast MRI. Further research is needed in expanding the field-of-view for posterior breast lesions, increasing biopsy capability, and reducing radiation dose. Efforts are also necessary for developing appropriate use criteria, increasing availability, and advancing insurance coverage.
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Affiliation(s)
- Amy M Fowler
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252, USA; Department of Medical Physics, University of Wisconsin-Madison; University of Wisconsin Carbone Cancer Center, Madison, WI, USA.
| | - Kanae K Miyake
- Department of Advanced Medical Imaging Research, Graduate School of Medicine Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
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2
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Kataoka M, Iima M, Miyake KK, Honda M. Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment. Invest Radiol 2024; 59:26-37. [PMID: 37994113 DOI: 10.1097/rli.0000000000001044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
ABSTRACT A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.
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Affiliation(s)
- Masako Kataoka
- From the Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan (M.K., M.I., M.H.); Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan (M.I.); Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine Kyoto University, Kyoto, Japan (K.K.M); and Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan (M.H.)
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3
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Castorina L, Comis AD, Prestifilippo A, Quartuccio N, Panareo S, Filippi L, Castorina S, Giuffrida D. Innovations in Positron Emission Tomography and State of the Art in the Evaluation of Breast Cancer Treatment Response. J Clin Med 2023; 13:154. [PMID: 38202160 PMCID: PMC10779934 DOI: 10.3390/jcm13010154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/14/2023] [Accepted: 12/23/2023] [Indexed: 01/12/2024] Open
Abstract
The advent of hybrid Positron Emission Tomography/Computed Tomography (PET/CT) and PET/Magnetic Resonance Imaging (MRI) scanners resulted in an increased clinical relevance of nuclear medicine in oncology. The use of [18F]-Fluorodeoxyglucose ([18F]FDG) has also made it possible to study tumors (including breast cancer) from not only a dimensional perspective but also from a metabolic point of view. In particular, the use of [18F]FDG PET allowed early confirmation of the efficacy or failure of therapy. The purpose of this review was to assess the literature concerning the response to various therapies for different subtypes of breast cancer through PET. We start by summarizing studies that investigate the validation of PET/CT for the assessment of the response to therapy in breast cancer; then, we present studies that compare PET imaging (including PET devices dedicated to the breast) with CT and MRI, focusing on the identification of the most useful parameters obtainable from PET/CT. We also focus on novel non-FDG radiotracers, as they allow for the acquisition of information on specific aspects of the new therapies.
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Affiliation(s)
- Luigi Castorina
- Nuclear Medicine Outpatient Unit, REM Radiotherapy Srl, Via Penninanzzo 11, 95029 Viagrande, Italy;
| | - Alessio Danilo Comis
- Nuclear Medicine Outpatient Unit, REM Radiotherapy Srl, Via Penninanzzo 11, 95029 Viagrande, Italy;
| | - Angela Prestifilippo
- Department of Oncology, IOM Mediterranean Oncology Institute, Via Penninanzzo 7, 95029 Viagrande, Italy; (A.P.); (D.G.)
| | - Natale Quartuccio
- Nuclear Medicine Unit, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy;
| | - Stefano Panareo
- Nuclear Medicine Unit, Oncology and Haematology Department, University Hospital of Modena, 41124 Modena, Italy;
| | - Luca Filippi
- Nuclear Medicine Unit, Department of Oncohaematology, Fondazione PTV Policlinico Tor Vergata University Hospital, Viale Oxford 81, 00133 Rome, Italy;
| | - Serena Castorina
- Nuclear Medicine Unit, Azienda Ospedaliero Universitaria Policlinico “G. Rodolico-San Marco”, 95123 Catania, Italy
| | - Dario Giuffrida
- Department of Oncology, IOM Mediterranean Oncology Institute, Via Penninanzzo 7, 95029 Viagrande, Italy; (A.P.); (D.G.)
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Kuzmova M, Cullinane C, Rutherford C, McCartan D, Rothwell J, Evoy D, Geraghty J, Prichard RS. The accuracy of MRI in detecting pathological complete response following neoadjuvant chemotherapy in different breast cancer subtypes. Surg Oncol 2023; 51:102011. [PMID: 37931546 DOI: 10.1016/j.suronc.2023.102011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 08/03/2023] [Accepted: 10/22/2023] [Indexed: 11/08/2023]
Abstract
BACKGROUND Pathological complete response (pCR) following neo-adjuvant chemotherapy (NACT) for breast cancer is associated with improved disease-free and overall survival in certain breast cancer subtypes. Magnetic Resonance Imaging (MRI) is increasingly used as standard to assess treatment response in patients receiving NACT. The aim of this study was to determine the clinical utility of MRI in accurately predicting pCR post-NACT. METHODS A single-centre, retrospective study was conducted in breast cancer patients, who received NACT between 2013 and 2020. Patients who had an MRI before and after NACT were included. Pathological and MRI radiological response rates to NACT were analyzed and MRI accuracy assessed in detecting pCR according to breast cancer subtype. RESULTS One hundred and sixty-seven patients were included in the study. Forty-one of the 167 patients achieved pCR (24.6 %), with the highest proportion in HR- HER2+ subgroup (58.3 %), followed by triple negative breast cancer (TNBC) (35 %). Only 22.2 % and 10.5 % of patients with HR + HER2+ and HR + HER2-respectively achieved pCR. The overall accuracy of MRI in predicting pCR after NACT was 77.3 %. The greatest accuracy was in TNBC (87.5 %) with a specificity and positive predictive value (PPV) of 100 % and the highest number of correctly diagnosed complete responses (14 of 40). MRI was less accurate in predicting response rates in HR + HER2- (PPV 91.2 %) and HR + HER2+ groups (PPV 90.5 %). MRI performed significantly better in predicting complete response in TNBC compared to HR + HER2-subtype (p = 0.0057). CONCLUSION MRI is a clinically useful adjunct in assessing pCR following NACT and appears to predict pathological response more accurately in TNBC compared to HR + HER2-breast cancer subtypes. This has significant clinical implications in terms of surgical planning, adjuvant treatment options and prognosis.
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Affiliation(s)
- Miroslava Kuzmova
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland.
| | - Carolyn Cullinane
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Claire Rutherford
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Damian McCartan
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Jane Rothwell
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Denis Evoy
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - James Geraghty
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
| | - Ruth S Prichard
- Department of Breast and Endocrine Surgery, St. Vincent's University Hospital, Dublin 4, Ireland
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Caracciolo M, Castello A, Urso L, Borgia F, Marzola MC, Uccelli L, Cittanti C, Bartolomei M, Castellani M, Lopci E. Comparison of MRI vs. [ 18F]FDG PET/CT for Treatment Response Evaluation of Primary Breast Cancer after Neoadjuvant Chemotherapy: Literature Review and Future Perspectives. J Clin Med 2023; 12:5355. [PMID: 37629397 PMCID: PMC10455346 DOI: 10.3390/jcm12165355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/27/2023] Open
Abstract
The purpose of this systematic review was to investigate the diagnostic accuracy of [18F]FDG PET/CT and breast MRI for primary breast cancer (BC) response assessment after neoadjuvant chemotherapy (NAC) and to evaluate future perspectives in this setting. We performed a critical review using three bibliographic databases (i.e., PubMed, Scopus, and Web of Science) for articles published up to the 6 June 2023, starting from 2012. The Quality Assessment of Diagnosis Accuracy Study (QUADAS-2) tool was adopted to evaluate the risk of bias. A total of 76 studies were identified and screened, while 14 articles were included in our systematic review after a full-text assessment. The total number of patients included was 842. Eight out of fourteen studies (57.1%) were prospective, while all except one study were conducted in a single center. In the majority of the included studies (71.4%), 3.0 Tesla (T) MRI scans were adopted. Three out of fourteen studies (21.4%) used both 1.5 and 3.0 T MRI and only two used 1.5 T. [18F]FDG was the radiotracer used in every study included. All patients accepted surgical treatment after NAC and each study used pathological complete response (pCR) as the reference standard. Some of the studies have demonstrated the superiority of [18F]FDG PET/CT, while others proved that MRI was superior to PET/CT. Recent studies indicate that PET/CT has a better specificity, while MRI has a superior sensitivity for assessing pCR in BC patients after NAC. The complementary value of the combined use of these modalities represents probably the most important tool to improve diagnostic performance in this setting. Overall, larger prospective studies, possibly randomized, are needed, hopefully evaluating PET/MR and allowing for new tools, such as radiomic parameters, to find a proper place in the setting of BC patients undergoing NAC.
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Affiliation(s)
- Matteo Caracciolo
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
| | - Angelo Castello
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Luca Urso
- Department of Nuclear Medicine PET/CT Centre, S. Maria della Misericordia Hospital, 45100 Rovigo, Italy
| | - Francesca Borgia
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Maria Cristina Marzola
- Department of Nuclear Medicine PET/CT Centre, S. Maria della Misericordia Hospital, 45100 Rovigo, Italy
| | - Licia Uccelli
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Corrado Cittanti
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Mirco Bartolomei
- Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, 44124 Ferrara, Italy
| | - Massimo Castellani
- Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Egesta Lopci
- Nuclear Medicine Unit, IRCCS—Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Italy
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Satoh Y, Hanaoka K, Ikegawa C, Imai M, Watanabe S, Morimoto-Ishikawa D, Onishi H, Ito T, Komoike Y, Ishii K. Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models. Diagnostics (Basel) 2023; 13:diagnostics13061079. [PMID: 36980385 PMCID: PMC10047304 DOI: 10.3390/diagnostics13061079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/02/2023] [Accepted: 03/11/2023] [Indexed: 03/14/2023] Open
Abstract
The performances of photomultiplier tube (PMT)-based dedicated breast positron emission tomography (PET) and silicon photomultiplier tube (SiPM)-based time-of-flight (TOF) PET, which is applicable not only to breast imaging but also to head imaging, were compared using a phantom study. A cylindrical phantom containing four spheres (3–10 mm in diameter) filled with 18F-FDG at two signal-to-background ratios (SBRs), 4:1 and 8:1, was scanned. The phantom images, which were reconstructed using three-dimensional list-mode dynamic row-action maximum likelihood algorithm with various β-values and post-smoothing filters, were visually and quantitatively compared. Visual evaluation showed that the 3 mm sphere was more clearly visualized with higher β and smaller post-filters, while the background was noisier; SiPM-based TOF-PET was superior to PMT-based dbPET in sharpness, smoothness, and detectability, although the background was noisier at the SBR of 8:1. Quantitative evaluation revealed that the detection index (DI) and recovery coefficient (CRC) of SiPM-based TOF-PET images were higher than those of PMT-based PET images, despite a higher background coefficient of variation (CVBG). The two organ-specific PET systems showed that a 3 mm lesion in the breast could be visualized at the center of the detector, and there was less noise in the SiPM-based TOF-PET image.
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Affiliation(s)
- Yoko Satoh
- Yamanashi PET Imaging Clinic, Chuo 409-3821, Japan
- Department of Radiology, University of Yamanashi, Chuo 409-3898, Japan
- Correspondence:
| | - Kohei Hanaoka
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | | | | | - Shota Watanabe
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | - Daisuke Morimoto-Ishikawa
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | - Hiroshi Onishi
- Department of Radiology, University of Yamanashi, Chuo 409-3898, Japan
| | - Toshikazu Ito
- Division of Breast and Endocrine Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osakasayama 589-8511, Japan
| | - Yoshifumi Komoike
- Division of Breast and Endocrine Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osakasayama 589-8511, Japan
| | - Kazunari Ishii
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
- Department of Radiology, Kindai University Faculty of Medicine, Osakasayama 577-8502, Japan
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Mizuta T. [9. Development of Dedicated Breast PET]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2023; 79:196-199. [PMID: 36804811 DOI: 10.6009/jjrt.2023-2155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Affiliation(s)
- Tetsuro Mizuta
- Research & Department Development, Medical Systems Division, Shimadzu Corporation
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8
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Sabatino V, Pignata A, Valentini M, Fantò C, Leonardi I, Campora M. Assessment and Response to Neoadjuvant Treatments in Breast Cancer: Current Practice, Response Monitoring, Future Approaches and Perspectives. Cancer Treat Res 2023; 188:105-147. [PMID: 38175344 DOI: 10.1007/978-3-031-33602-7_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Neoadjuvant treatments (NAT) for breast cancer (BC) consist in the administration of chemotherapy-more rarely endocrine therapy-before surgery. Firstly, it was introduced 50 years ago to downsize locally advanced (inoperable) BCs. NAT are now widespread and so effective to be used also at the early stage of the disease. NAT are heterogeneous in terms of therapeutic patterns, class of used drugs, dosage, and duration. The poly-chemotherapy regimen and administration schedule are established by a multi-disciplinary team, according to the stage of disease, the tumor subtype and the age, the physical status, and the drug sensitivity of BC patients. Consequently, an accurate monitoring of treatment response can provide significant clinical advantages, such as the treatment de-escalation in case of early recognition of complete response or, on the contrary, the switch to an alternative treatment path in case of early detection of resistance to the ongoing therapy. Future is going toward increasingly personalized therapies and the prediction of individual response to treatment is the key to practice customized care pathways, preserving oncological safety and effectiveness. To gain such goal, the development of an accurate monitoring system, reproducible and reliable alone or as part of more complex diagnostic algorithms, will be promising.
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Affiliation(s)
- Vincenzo Sabatino
- Breast Imaging Department, Santa Chiara Hospital, APSS, Trento, Italy.
| | - Alma Pignata
- Breast Center, Spedali Civili Hospital, ASST, Brescia, Italy
| | - Marvi Valentini
- Breast Imaging Department, Santa Chiara Hospital, APSS, Trento, Italy
| | - Carmen Fantò
- Breast Imaging Department, Santa Chiara Hospital, APSS, Trento, Italy
| | - Irene Leonardi
- Breast Imaging Department, Santa Chiara Hospital, APSS, Trento, Italy
| | - Michela Campora
- Pathology Department, Santa Chiara Hospital, APSS, Trento, Italy
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9
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Fujioka T, Satoh Y, Imokawa T, Mori M, Yamaga E, Takahashi K, Kubota K, Onishi H, Tateishi U. Proposal to Improve the Image Quality of Short-Acquisition Time-Dedicated Breast Positron Emission Tomography Using the Pix2pix Generative Adversarial Network. Diagnostics (Basel) 2022; 12:diagnostics12123114. [PMID: 36553120 PMCID: PMC9777139 DOI: 10.3390/diagnostics12123114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/26/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
This study aimed to evaluate the ability of the pix2pix generative adversarial network (GAN) to improve the image quality of low-count dedicated breast positron emission tomography (dbPET). Pairs of full- and low-count dbPET images were collected from 49 breasts. An image synthesis model was constructed using pix2pix GAN for each acquisition time with training (3776 pairs from 16 breasts) and validation data (1652 pairs from 7 breasts). Test data included dbPET images synthesized by our model from 26 breasts with short acquisition times. Two breast radiologists visually compared the overall image quality of the original and synthesized images derived from the short-acquisition time data (scores of 1−5). Further quantitative evaluation was performed using a peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the visual evaluation, both readers revealed an average score of >3 for all images. The quantitative evaluation revealed significantly higher SSIM (p < 0.01) and PSNR (p < 0.01) for 26 s synthetic images and higher PSNR for 52 s images (p < 0.01) than for the original images. Our model improved the quality of low-count time dbPET synthetic images, with a more significant effect on images with lower counts.
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Affiliation(s)
- Tomoyuki Fujioka
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Yoko Satoh
- Yamanashi PET Imaging Clinic, Chuo City 409-3821, Japan
- Department of Radiology, University of Yamanashi, Chuo City 409-3898, Japan
- Correspondence:
| | - Tomoki Imokawa
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Mio Mori
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Emi Yamaga
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Kanae Takahashi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Kazunori Kubota
- Department of Radiology, Dokkyo Medical University Saitama Medical Center, Koshigaya 343-8555, Japan
| | - Hiroshi Onishi
- Department of Radiology, University of Yamanashi, Chuo City 409-3898, Japan
| | - Ukihide Tateishi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
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10
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Browne R, McAnena P, O'Halloran N, Moloney BM, Crilly E, Kerin MJ, Lowery AJ. Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy. Breast Cancer (Auckl) 2022; 16:11782234221103504. [PMID: 35769423 PMCID: PMC9234834 DOI: 10.1177/11782234221103504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 04/28/2022] [Indexed: 11/30/2022] Open
Abstract
Introduction: The ability to accurately predict pathologic complete response (pCR) after
neoadjuvant chemotherapy (NAC) in breast cancer would improve patient
selection for specific treatment strategies, would provide important
information for patients to aid in the treatment selection process, and
could potentially avoid the need for more extensive surgery. The diagnostic
performance of magnetic resonance imaging (MRI) in predicting pCR has
previously been studied, with mixed results. Magnetic resonance imaging
performance may also be influenced by tumour and patient factors. Methods: Eighty-seven breast cancer patients who underwent NAC were studied. Pre-NAC
and post-NAC MRI findings were compared with pathologic findings
postsurgical excision. The impact of patient and tumour characteristics on
MRI accuracy was evaluated. Results: The mean (SD) age of participants was 48.7 (10.3) years. The rate of pCR
based on post-NAC MRI was 19.5% overall (19/87). The sensitivity,
specificity, positive predictive value (PPV), negative predictive value, and
accuracy in predicting pCR were 52.9%, 77.1%, 36.0%, 87.1%, and 72.4%,
respectively. Positive predictive value was the highest in nonluminal versus
Luminal A disease (45.0% vs 25.0%, P < .001), with
higher rates of false positivity in nonluminal subtypes
(P = .002). Tumour grade, T category, and histological
subtype were all independent predictors of MRI accuracy regarding post-NAC
tumour size. Conclusion: Magnetic resonance imaging alone is insufficient to accurately predict pCR in
breast cancer patients post-NAC. Magnetic resonance imaging predictions of
pCR are more accurate in nonluminal subtypes. Tumour grade, T category, and
histological subtype should be considered when evaluating post-NAC tumour
sizes.
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Affiliation(s)
- Robert Browne
- Department of Surgery, University Hospital Galway, Galway, Ireland
| | - Peter McAnena
- Department of Surgery, University Hospital Galway, Galway, Ireland
| | - Niamh O'Halloran
- Department of Radiology, University Hospital Galway, Galway, Ireland
| | - Brian M Moloney
- Department of Radiology, University Hospital Galway, Galway, Ireland
| | - Emily Crilly
- Department of Surgery, University Hospital Galway, Galway, Ireland
| | - Michael J Kerin
- Department of Surgery, University Hospital Galway, Galway, Ireland.,Discipline of Surgery, Lambe Institute for Translational Research, National University of Ireland Galway, Galway, Ireland
| | - Aoife J Lowery
- Department of Surgery, University Hospital Galway, Galway, Ireland.,Discipline of Surgery, Lambe Institute for Translational Research, National University of Ireland Galway, Galway, Ireland
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11
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Kong X, Zhang Q, Wu X, Zou T, Duan J, Song S, Nie J, Tao C, Tang M, Wang M, Zou J, Xie Y, Li Z, Li Z. Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer. Front Oncol 2022; 12:816297. [PMID: 35669440 PMCID: PMC9163342 DOI: 10.3389/fonc.2022.816297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 03/29/2022] [Indexed: 11/13/2022] Open
Abstract
Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.
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Affiliation(s)
- Xianshu Kong
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Qian Zhang
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Xuemei Wu
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Tianning Zou
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Jiajun Duan
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Shujie Song
- Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Jianyun Nie
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Chu Tao
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Mi Tang
- Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Maohua Wang
- First Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Jieya Zou
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Yu Xie
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Zhenhui Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
- *Correspondence: Zhen Li, ; Zhenhui Li,
| | - Zhen Li
- Third Department of the Breast Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
- *Correspondence: Zhen Li, ; Zhenhui Li,
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Ota R, Kataoka M, Iima M, Honda M, Ohashi A, Ohno Kishimoto A, Kawai Miyake K, Yamada Y, Takeuchi Y, Toi M, Nakamoto Y. Evaluation of pathological complete response after neoadjuvant systemic treatment of invasive breast cancer using diffusion-weighted imaging compared with dynamic contrast-enhanced based kinetic analysis. Eur J Radiol 2022; 154:110372. [DOI: 10.1016/j.ejrad.2022.110372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 04/21/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022]
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Satoh Y, Imokawa T, Fujioka T, Mori M, Yamaga E, Takahashi K, Takahashi K, Kawase T, Kubota K, Tateishi U, Onishi H. Deep learning for image classification in dedicated breast positron emission tomography (dbPET). Ann Nucl Med 2022; 36:401-410. [PMID: 35084712 DOI: 10.1007/s12149-022-01719-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 01/13/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE This study aimed to investigate and determine the best deep learning (DL) model to predict breast cancer (BC) with dedicated breast positron emission tomography (dbPET) images. METHODS Of the 1598 women who underwent dbPET examination between April 2015 and August 2020, a total of 618 breasts on 309 examinations for 284 women who were diagnosed with BC or non-BC were analyzed in this retrospective study. The Xception-based DL model was trained to predict BC or non-BC using dbPET images from 458 breasts of 109 BCs and 349 non-BCs, which consisted of mediallateral and craniocaudal maximum intensity projection images, respectively. It was tested using dbPET images from 160 breasts of 43 BC and 117 non-BC. Two expert radiologists and two radiology residents also interpreted them. Sensitivity, specificity, and area under the receiver operating characteristic curves (AUCs) were calculated. RESULTS Our DL model had a sensitivity and specificity of 93% and 93%, respectively, while radiologists had a sensitivity and specificity of 77-89% and 79-100%, respectively. Diagnostic performance of our model (AUC = 0.937) tended to be superior to that of residents (AUC = 0.876 and 0.868, p = 0.073 and 0.073), although not significantly different. Moreover, no significant differences were found between the model and experts (AUC = 0.983 and 0.941, p = 0.095 and 0.907). CONCLUSIONS Our DL model could be applied to dbPET and achieve the same diagnostic ability as that of experts.
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Affiliation(s)
- Yoko Satoh
- Yamanashi PET Imaging Clinic, Chuo City, Yamanashi Prefecture, Japan
- Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
| | - Tomoki Imokawa
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Tomoyuki Fujioka
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan.
| | - Mio Mori
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Emi Yamaga
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Kanae Takahashi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Keiko Takahashi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Takahiro Kawase
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Kazunori Kubota
- Department of Radiology, Dokkyo Medical University Saitama Medical Center, Koshigaya City, Saitama Prefecture, Japan
| | - Ukihide Tateishi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo Ku, Tokyo, Japan
| | - Hiroshi Onishi
- Department of Radiology, University of Yamanashi, Chuo City, Yamanashi Prefecture, Japan
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