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Zhang J, Sun H, Gao S, Kang Y, Shang C. Prediction of disease-free survival using strain elastography and diffuse optical tomography in patients with T1 breast cancer: a 10-year follow-up study. BMC Cancer 2024; 24:1057. [PMID: 39192199 DOI: 10.1186/s12885-024-12844-z] [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: 01/25/2024] [Accepted: 08/22/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS. METHODS A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated. RESULTS During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P < 0.001 for trend) and the total hemoglobin concentration (TTHC) (P = 0.001 for trend) and DFS. In the subgroup analysis, an intensified association between SR and DFS was observed among women who were progesterone receptor (PR)-positive, lower Ki-67 expression, HER2 negative, and without adjuvant chemotherapy and without Herceptin treatment (all P < 0.05 for interaction). Significant interactions between TTHC status and the lymphovascular invasion, estrogen receptor (ER) status, PR status, HER2 status, and Herceptin treatment were found for DFS(P < 0.05).The imaging-clinical combined model (TTHC + SR + clinicopathological variables) proved to be the best prediction model (AUC = 0.829, 95% CI = 0.786-0.872) and was identified as a potential risk stratification tool to discriminate the risk probability of recurrence. CONCLUSION The combined imaging-clinical model we developed outperformed traditional clinical prognostic indicators, providing a non-invasive, reliable tool for preoperative DFS risk stratification and personalized therapeutic strategies in T1 BC. These findings underscore the importance of integrating advanced imaging techniques into clinical practice and offer support for future research to validate and expand on these predictive methodologies.
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Affiliation(s)
- Jing Zhang
- Department of Ultrasound, Shengjing Hospital of China Medical University, No.36, Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China
| | - Hao Sun
- Department of Clinical Epidemiology and Evidence-Based Medicine, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, China
| | - Song Gao
- Department of Clinical Oncology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110004, China
| | - Ye Kang
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110004, China
| | - Cong Shang
- Department of Ultrasound, Shengjing Hospital of China Medical University, No.36, Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China.
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Deng B, Muldoon A, Cormier J, Mercaldo ND, Niehoff E, Moffett N, Saksena MA, Isakoff SJ, Carp SA. Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:066001. [PMID: 38737790 PMCID: PMC11088438 DOI: 10.1117/1.jbo.29.6.066001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/12/2024] [Accepted: 04/12/2024] [Indexed: 05/14/2024]
Abstract
Significance Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. Aim We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Approach Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Results Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p = 0.042 ). In addition, the change in normalized tumor StO 2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p = 0.038 ). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. Conclusions These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.
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Affiliation(s)
- Bin Deng
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
| | - Ailis Muldoon
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Jayne Cormier
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - Nathaniel D. Mercaldo
- Harvard Medical School, Boston, Massachusetts, United States
- Massachusetts General Hospital, Institute for Technology Assessment, Boston, Massachusetts, United States
| | - Elizabeth Niehoff
- Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, United States
| | - Natalie Moffett
- Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, United States
| | - Mansi A. Saksena
- Harvard Medical School, Boston, Massachusetts, United States
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - Steven J. Isakoff
- Harvard Medical School, Boston, Massachusetts, United States
- Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
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Cheung SM, Wu WS, Senn N, Sharma R, McGoldrick T, Gagliardi T, Husain E, Masannat Y, He J. Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion. Front Oncol 2023; 13:1277556. [PMID: 38125950 PMCID: PMC10731248 DOI: 10.3389/fonc.2023.1277556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/21/2023] [Indexed: 12/23/2023] Open
Abstract
Introduction The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response. Materials and methods Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy. Results The perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [-7.98% (-19.47-1.73), n = 7] and an increase in poor responders [10.04% (5.09-28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy. Conclusion The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT. Clinical trial registration https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.
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Affiliation(s)
- Sai Man Cheung
- Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - Wing-Shan Wu
- Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - Nicholas Senn
- Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - Ravi Sharma
- Department of Oncology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Trevor McGoldrick
- Department of Oncology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Tanja Gagliardi
- Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
- Department of Radiology, Royal Marsden Hospital, London, United Kingdom
| | - Ehab Husain
- Department of Pathology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Yazan Masannat
- Breast Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Jiabao He
- Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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Ahmadpour ST, Orre C, Bertevello PS, Mirebeau-Prunier D, Dumas JF, Desquiret-Dumas V. Breast Cancer Chemoresistance: Insights into the Regulatory Role of lncRNA. Int J Mol Sci 2023; 24:15897. [PMID: 37958880 PMCID: PMC10650504 DOI: 10.3390/ijms242115897] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023] Open
Abstract
Long noncoding RNAs (lncRNAs) are a subclass of noncoding RNAs composed of more than 200 nucleotides without the ability to encode functional proteins. Given their involvement in critical cellular processes such as gene expression regulation, transcription, and translation, lncRNAs play a significant role in organism homeostasis. Breast cancer (BC) is the second most common cancer worldwide and evidence has shown a relationship between aberrant lncRNA expression and BC development. One of the main obstacles in BC control is multidrug chemoresistance, which is associated with the deregulation of multiple mechanisms such as efflux transporter activity, mitochondrial metabolism reprogramming, and epigenetic regulation as well as apoptosis and autophagy. Studies have shown the involvement of a large number of lncRNAs in the regulation of such pathways. However, the underlying mechanism is not clearly elucidated. In this review, we present the principal mechanisms associated with BC chemoresistance that can be directly or indirectly regulated by lncRNA, highlighting the importance of lncRNA in controlling BC chemoresistance. Understanding these mechanisms in deep detail may interest the clinical outcome of BC patients and could be used as therapeutic targets to overcome BC therapy resistance.
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Affiliation(s)
- Seyedeh Tayebeh Ahmadpour
- Nutrition, Croissance et Cancer, Inserm, UMR1069, Université de Tours, 37032 Tours, France; (P.S.B.); (J.-F.D.)
| | - Charlotte Orre
- Inserm U1083, UMR CNRS 6214, Angers University, 49933 Angers, France; (C.O.); (D.M.-P.)
| | - Priscila Silvana Bertevello
- Nutrition, Croissance et Cancer, Inserm, UMR1069, Université de Tours, 37032 Tours, France; (P.S.B.); (J.-F.D.)
| | | | - Jean-François Dumas
- Nutrition, Croissance et Cancer, Inserm, UMR1069, Université de Tours, 37032 Tours, France; (P.S.B.); (J.-F.D.)
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Pavlov MV, Bavrina AP, Plekhanov VI, Golubyatnikov GY, Orlova AG, Subochev PV, Davydova DA, Turchin IV, Maslennikova AV. Correction: Changes in the tumor oxygenation but not in the tumor volume and tumor vascularization reflect early response of breast cancer to neoadjuvant chemotherapy. Breast Cancer Res 2023; 25:16. [PMID: 36750941 PMCID: PMC9903525 DOI: 10.1186/s13058-023-01614-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023] Open
Affiliation(s)
- Mikhail V. Pavlov
- Nizhny Novgorod Regional Clinical Oncology Dispensary, Delovaya St., 11/1, Nizhny Novgorod, Russia 603126
| | - Anna P. Bavrina
- grid.416347.30000 0004 0386 1631Privolzhsky Research Medical University, Minina Square, 10/1, Nizhny Novgorod, Russia 603950
| | - Vladimir I. Plekhanov
- grid.410472.40000 0004 0638 0147Institute of Applied Physics RAS, Ul’yanov Street, 46, Nizhny Novgorod, Russia 603950
| | - German Yu. Golubyatnikov
- grid.410472.40000 0004 0638 0147Institute of Applied Physics RAS, Ul’yanov Street, 46, Nizhny Novgorod, Russia 603950
| | - Anna G. Orlova
- grid.410472.40000 0004 0638 0147Institute of Applied Physics RAS, Ul’yanov Street, 46, Nizhny Novgorod, Russia 603950
| | - Pavel V. Subochev
- grid.410472.40000 0004 0638 0147Institute of Applied Physics RAS, Ul’yanov Street, 46, Nizhny Novgorod, Russia 603950
| | - Diana A. Davydova
- Nizhny Novgorod Regional Clinical Oncology Dispensary, Delovaya St., 11/1, Nizhny Novgorod, Russia 603126
| | - Ilya V. Turchin
- grid.410472.40000 0004 0638 0147Institute of Applied Physics RAS, Ul’yanov Street, 46, Nizhny Novgorod, Russia 603950
| | - Anna V. Maslennikova
- grid.416347.30000 0004 0386 1631Privolzhsky Research Medical University, Minina Square, 10/1, Nizhny Novgorod, Russia 603950 ,grid.28171.3d0000 0001 0344 908XNational Research Lobachevsky State University of Nizhny Novgorod, Gagarin Ave., 23, Nizhny Novgorod, Russia 603022
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