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Yang XL, Ni DH, Yu Y, Zhao JC, Lin R, Xiu C, Chang ZX. Value of magnetic resonance imaging radiomics features in predicting histologic grade of invasive ductal carcinoma of the breast. Technol Health Care 2024; 32:1609-1618. [PMID: 38393931 DOI: 10.3233/thc-230671] [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: 02/25/2024]
Abstract
BACKGROUND Breast cancer has the second highest mortality rate of all cancers and occurs mainly in women. OBJECTIVE To investigate the relationship between magnetic resonance imaging (MRI) radiomics features and histological grade of invasive ductal carcinoma (IDC) of the breast and to evaluate its diagnostic efficacy. METHODS The two conventional MRI quantitative indicators, i.e. the apparent diffusion coefficient (ADC) and the initial enhancement rate, were collected from 112 patients with breast cancer. The breast cancer lesions were manually segmented in dynamic contrast-enhanced MRI (DCE-MRI) and ADC images, the differences in radiomics features between Grades I, II and III IDCs were compared and the diagnostic efficacy was evaluated. RESULTS The ADC values (0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20, F= 4.204, p< 0.01), as well as the B_sum_variance (188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58, F= 6.040, p< 0.01), L_energy (0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14, F= 7.118, p< 0.01) and L_sum_average (0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74, F= 21.860, p< 0.001) values of patients with Grade III IDC were significantly lower than those of patients with Grades I and II IDC. The B_uniform (0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03, F= 3.797, p< 0.01) and L_SRE (0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32, F= 3.024, p< 0.01) values of patients with Grade III IDC were significantly higher than those of patients with Grades I and II IDC. All differences were statistically significant (p< 0.05). The ADC radiomics signature model had a higher area-under-the-curve value in identifying different grades of IDC than the ADC value model and the DCE radiomics signature model (0.869 vs 0.711 vs 0.682). The accuracy (0.812 vs 0.647 vs 0.710), specificity (0.731 vs 0.435 vs 0.342), positive predictive value (0.815 vs 0.663 vs 0.669) and negative predictive value (0.753 vs 0.570 vs 0.718) of the ADC radiomics signature model were all significantly better than the ADC value model and the DCE radiomics signature model. CONCLUSION ADC values and breast MRI radiomics signatures are significant in identifying the histological grades of IDC, with the ADC radiomics signatures having greater value.
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Affiliation(s)
- Xin-Lei Yang
- Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China
- Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China
| | - Dong-He Ni
- Department of Radiology, Jilin Province Integrated Traditional Chinese and Western Medicine Hospital, Jilin, China
- Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China
| | - Yang Yu
- Department of Radiology, Beihua University Affiliated Hospital, Jilin, China
| | - Jin-Cui Zhao
- Department of Radiology, Beihua University Affiliated Hospital, Jilin, China
| | - Rui Lin
- Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China
| | - Chao Xiu
- Department of Radiology, Beihua University Affiliated Hospital, Jilin, China
| | - Zhe-Xing Chang
- Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China
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2
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Fokkinga E, Hernandez-Tamames JA, Ianus A, Nilsson M, Tax CMW, Perez-Lopez R, Grussu F. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging 2023. [PMID: 38032021 DOI: 10.1002/jmri.29144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ella Fokkinga
- Biomedical Engineering, Track Medical Physics, Delft University of Technology, Delft, The Netherlands
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Andrada Ianus
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Markus Nilsson
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund, Sweden
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Raquel Perez-Lopez
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Francesco Grussu
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
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Pikūnienė I, Saladžinskas Ž, Basevičius A, Strakšytė V, Žilinskas J, Ambrazienė R. MRI Evaluation of Rectal Cancer Lymph Node Staging Using Apparent Diffusion Coefficient. Cureus 2023; 15:e45002. [PMID: 37701166 PMCID: PMC10493462 DOI: 10.7759/cureus.45002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/10/2023] [Indexed: 09/14/2023] Open
Abstract
Introduction Colorectal cancer is the third most diagnosed cancer globally. Lymph node metastases significantly affect prognosis, emphasizing the importance of early detection and management. Despite significant advances in conventional MRI's role in staging, improvements in advanced functional imaging such as diffusion-weighted imaging (DWI) in identifying lymph node metastases persist. Objectives The aim is to evaluate the effectiveness of apparent diffusion coefficient (ADC) MRI in evaluating lymph node staging in rectal cancer. Patients and methods In a prospective study, 89 patients with stage II-III rectal cancer were grouped into two treatments: pre-operative FOLFOX4 chemotherapy and standard pre-operative chemoradiotherapy. All underwent 1.5T MRI, with T2-weighted and DWI sequences. A radiologist defined regions of interest on the tumor, lymph nodes, and intact rectal wall to calculate ADC values. Results Rectal cancer ADC's receiver operating characteristic curve had an area under the curve (AUC) of 0.688 (P < 0.001), with optimal ADC cutoff at 0.99 x 10-3 mm2/s (sensitivity: 75%, specificity: 83%). For lymph nodes, AUC was 0.508 (P < 0.001), with a cutoff of 0.9 x 10-3 mm2/s (sensitivity: 78%, specificity: 67%). No correlation between tumor and lymph node ADC values was observed. In chemotherapy patients, "healthy" inguinal lymph nodes had higher ADC values than affected ones pre-treatment (P = 0.001), a disparity fading post-treatment (P = 0.313). For chemoradiotherapy patients, the ADC difference persisted pre and post-treatment (P = 0.001). Conclusion The study of ADC-MRI showed different ADC values between tumors and lymph nodes and highlighted ADC differences between treatment groups. Notably, no correlation was observed between tumor and lymph node ADC values. However, differences were apparent when comparing "healthy" inguinal nodes with lymph nodes affected by cancer.
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Affiliation(s)
- Ingrida Pikūnienė
- Department of Radiology, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
| | - Žilvinas Saladžinskas
- Department of Surgery, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
| | - Algidas Basevičius
- Department of Radiology, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
| | - Vestina Strakšytė
- Department of Radiology, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
| | - Justas Žilinskas
- Department of Surgery, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
| | - Rita Ambrazienė
- Department of Oncology, Hospital of Lithuanian University of Health Sciences Kauno Klinikos, Kaunas, LTU
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Ma C, Tian S, Song Q, Chen L, Meng X, Wang N, Lin L, Wang J, Liu A, Song Q. Amide Proton Transfer-Weighted Imaging Combined With Intravoxel Incoherent Motion for Evaluating Microsatellite Instability in Endometrial Cancer. J Magn Reson Imaging 2023; 57:493-505. [PMID: 35735273 DOI: 10.1002/jmri.28287] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/24/2022] [Accepted: 05/26/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Microsatellite instability (MSI), caused by mismatch repair (MMR) protein defects that lead to uncorrectable mismatch bases, results in the accumulation of gene mutations and ultimately to tumors. Preoperative prediction of MSI can provide a basis for personalized and precise treatment of endometrial cancer (EC) patients. PURPOSE To investigate amide proton transfer weighting (APTw) imaging combined with intravoxel incoherent motion (IVIM) in the assessment of MSI in EC. STUDY TYPE Retrospective. POPULATION A total of 71 patients with EC (12 classified as the MSI group and 22 as the microsatellite stabilization [MSS] group after entering and leaving the group standard). FIELD STRENGTH/SEQUENCE A 3.0 T/IVIM, diffusion-weighted imaging (DWI) and APTw. ASSESSMENT Amide proton transfer (APT) value, apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were calculated and compared between MSI and MSS groups. STATISTICAL TESTS The Kendall's W test; Mann-Whitney U-test; Chi-square test or Fisher's exact test; logistic regression analysis; Area under the receiver operating characteristic (ROC) curve (AUC); The Delong test; Pearson or Spearman correlation coefficients. The significance threshold was set at P < 0.05. RESULTS APT and D* values of the MSI group were significantly higher than those of the MSS group. While ADC, D, and f values in the MSI group were significantly lower than those in the MSS group. The multivariate analysis revealed that only APT and D* values were independent predictors to evaluate the MSI status. And the ROC curves indicated that the combination of APT and D* values could distinguish the MSI status of EC with the highest diagnostic efficacy (AUC = 0.973), even without significant difference to those by APT (AUC = 0.894) or D* (AUC = 0.920) value separately (P = 0.149 and 0.078, respectively). CONCLUSION Combination of APTw and IVIM imaging may serve as an effective noninvasive method for clinical assessment of MSI in EC. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Changjun Ma
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Shifeng Tian
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Qingling Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Lihua Chen
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Xing Meng
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Women and Children's Medical Group, Dalian, Liaoning, China
| | - Nan Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Liangjie Lin
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Ailian Liu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
| | - Qingwei Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.,Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, Liaoning, China
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Cho P, Park CS, Park GE, Kim SH, Kim HS, Oh SJ. Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer. Diagnostics (Basel) 2023; 13:diagnostics13030513. [PMID: 36766617 PMCID: PMC9914452 DOI: 10.3390/diagnostics13030513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/20/2023] [Accepted: 01/21/2023] [Indexed: 02/01/2023] Open
Abstract
This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10-3 mm2/s, and that of benign ALNs was 0.991 × 10-3 mm2/s (p = 0.243). All morphologic features showed significant difference between the two groups. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the final categorization on DW-MRI were 77.1%, 93.3%, 79.4%, 92.5%, and 86.2%, respectively. Our results suggest that morphologic evaluation of ALNs on DWI can discriminate metastatic ALNs from benign. The ADC value of metastatic ALNs was lower than that of benign nodes, but the difference was not statistically significant.
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Affiliation(s)
- Pyeonghwa Cho
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
| | - Chang Suk Park
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
- Correspondence: ; Tel.: +82-32-280-7305; Fax: +82-32-280-5192
| | - Ga Eun Park
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea
| | - Sung Hun Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea
| | - Hyeon Sook Kim
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
| | - Se-Jeong Oh
- Department of General Surgery, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
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Iima M, Le Bihan D. The road to breast cancer screening with diffusion MRI. Front Oncol 2023; 13:993540. [PMID: 36895474 PMCID: PMC9989267 DOI: 10.3389/fonc.2023.993540] [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: 07/13/2022] [Accepted: 01/10/2023] [Indexed: 02/23/2023] Open
Abstract
Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat á l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:1770531. [PMID: 36238476 PMCID: PMC9553330 DOI: 10.1155/2022/1770531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/11/2022] [Accepted: 09/08/2022] [Indexed: 11/17/2022]
Abstract
Background and Objective. Breast cancer is a common malignant tumor that seriously threatens the health of women in my country and even around the world. The proliferation marker Ki-67 has been utilized to distinguish luminal B from luminal A tumors and is a reliable indicator of more aggressive breast cancer growth. If a reliable prediction method for breast cancer patients to avoid invasive damage can be found to predict Ki-67 before pathological examination, it will be very beneficial for doctors to formulate later treatment plans and provide more useful treatment options. Methodology. This paper proposes a tumor segmentation and prediction framework based on the combination of improved attention U-Net and SVM. The framework first improves on attention U-Net by introducing coefficients for learning multidimensional attention. Make the attention mechanism more aware of the main situation in the segmentation process. At the same time, the segmented breast MRI results and corresponding labels were input into the SVM classifier to accurately predict the expression of Ki-67. Results. The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion. Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.
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Correlation Analysis of Pathological Features and Axillary Lymph Node Metastasis in Patients with Invasive Breast Cancer. J Immunol Res 2022; 2022:7150304. [PMID: 36249424 PMCID: PMC9553448 DOI: 10.1155/2022/7150304] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 06/21/2022] [Accepted: 08/05/2022] [Indexed: 11/17/2022] Open
Abstract
Objective To investigate the risk factors of axillary lymph node metastasis in patients with invasive breast cancer. Methods This study retrospectively included 122 cases of invasive breast cancer patients admitted to the First Medical Center of PLA General Hospital from January 2019 to September 2020. According to postoperative pathological results, axillary lymph node metastasis was divided into axillary lymph node metastasis (ALNM) group (n =40) and non-axillary lymph node metastasis (NALNM) group (n =82). General demographic information was collected and compared between the two groups. Collected pathological results included lymphovascular invasion (LVI) and the expression of estrogen receptor (ER), progestogen receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 detected by immunohistochemistry. Imaging parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) including apparent diffusion coefficient (ADC), early enhanced rate, and time-intensity curve (TIC) were also included into univariate analysis. The variables with differences between the two groups were compared by univariate analysis, and the related factors of axillary lymph node metastasis were analyzed by logistic regression model. Results There was no significant difference in general demographic information between the two groups. No significant differences were found in the positive rates of HER-2, ER, PR, Ki-67, pathological types, and clavicular lymph node metastasis and skin chest wall invasion between the two groups (P > 0.05). The proportion of LVI in ALNM group was significantly higher than that in NALNM group (37.50% vs. 6.10%, P < 0.001). The proportion of breast cancer on the left side in the ALNM group was higher than that in the NALNM group, and the difference was statistically significant (70.00% vs. 47.56%, P = 0.019). There were no significant differences in the imaging parameters obtained by DCE-MRI between the two groups. Binary logistics regression analysis showed that LVI (OR =12.258, 95% CI =3.681-40.812, P < 0.001) and left breast cancer (OR =3.598, 95% CI =1.404-9.219, P = 0.008) were risk factors for axillary lymph node metastasis in patients with invasive breast cancer. Conclusion The formation of vascular tumor thrombi in breast cancer tissue and left breast cancer are risk factors for axillary lymph node metastasis in invasive breast cancer and might be helpful for preoperative detailed assessment of the patient's condition.
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Di Paola V, Mazzotta G, Pignatelli V, Bufi E, D’Angelo A, Conti M, Panico C, Fiorentino V, Pierconti F, Kilburn-Toppin F, Belli P, Manfredi R. Beyond N Staging in Breast Cancer: Importance of MRI and Ultrasound-based Imaging. Cancers (Basel) 2022; 14:cancers14174270. [PMID: 36077805 PMCID: PMC9454572 DOI: 10.3390/cancers14174270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 08/27/2022] [Accepted: 08/30/2022] [Indexed: 12/29/2022] Open
Abstract
The correct N-staging in breast cancer is crucial to tailor treatment and stratify the prognosis. N-staging is based on the number and the localization of suspicious regional nodes on physical examination and/or imaging. Since clinical examination of the axillary cavity is associated with a high false negative rate, imaging modalities play a central role. In the presence of a T1 or T2 tumor and 0–2 suspicious nodes, on imaging at the axillary level I or II, a patient should undergo sentinel lymph node biopsy (SLNB), whereas in the presence of three or more suspicious nodes at the axillary level I or II confirmed by biopsy, they should undergo axillary lymph node dissection (ALND) or neoadjuvant chemotherapy according to a multidisciplinary approach, as well as in the case of internal mammary, supraclavicular, or level III axillary involved lymph nodes. In this scenario, radiological assessment of lymph nodes at the time of diagnosis must be accurate. False positives may preclude a sentinel lymph node in an otherwise eligible woman; in contrast, false negatives may lead to an unnecessary SLNB and the need for a second surgical procedure. In this review, we aim to describe the anatomy of the axilla and breast regional lymph node, and their diagnostic features to discriminate between normal and pathological nodes at Ultrasound (US) and Magnetic Resonance Imaging (MRI). Moreover, the technical aspects, the advantage and limitations of MRI versus US, and the possible future perspectives are also analyzed, through the analysis of the recent literature.
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Affiliation(s)
- Valerio Di Paola
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
- Correspondence: or
| | - Giorgio Mazzotta
- Institute of Radiology, Catholic University of the Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Vincenza Pignatelli
- Institute of Radiology, Catholic University of the Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Enida Bufi
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Anna D’Angelo
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Marco Conti
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Camilla Panico
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Vincenzo Fiorentino
- Institute of Pathology, Università Cattolica del S. Cuore, Fondazione Policlinico “A. Gemelli”, 00168 Rome, Italy
| | - Francesco Pierconti
- Institute of Pathology, Università Cattolica del S. Cuore, Fondazione Policlinico “A. Gemelli”, 00168 Rome, Italy
| | - Fleur Kilburn-Toppin
- Cambridge Breast Unit, Cambridge University Hospital NHS Foundation Trust, Addenbrookes’ Hospital, Hills Road, Cambridge CB2 0QQ, UK
| | - Paolo Belli
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
- Institute of Radiology, Catholic University of the Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
| | - Riccardo Manfredi
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiologia, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, 00168 Rome, Italy
- Institute of Radiology, Catholic University of the Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
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Nardone V, Barbarino M, Angrisani A, Correale P, Pastina P, Cappabianca S, Reginelli A, Mutti L, Miracco C, Giannicola R, Giordano A, Pirtoli L. CDK4, CDK6/cyclin-D1 Complex Inhibition and Radiotherapy for Cancer Control: A Role for Autophagy. Int J Mol Sci 2021; 22:8391. [PMID: 34445095 PMCID: PMC8395054 DOI: 10.3390/ijms22168391] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/01/2021] [Accepted: 08/02/2021] [Indexed: 12/13/2022] Open
Abstract
The expanding clinical application of CDK4- and CDK6-inhibiting drugs in the managements of breast cancer has raised a great interest in testing these drugs in other neoplasms. The potential of combining these drugs with other therapeutic approaches seems to be an interesting work-ground to explore. Even though a potential integration of CDK4 and CDK6 inhibitors with radiotherapy (RT) has been hypothesized, this kind of approach has not been sufficiently pursued, neither in preclinical nor in clinical studies. Similarly, the most recent discoveries focusing on autophagy, as a possible target pathway able to enhance the antitumor efficacy of CDK4 and CDK6 inhibitors is promising but needs more investigations. The aim of this review is to discuss the recent literature on the field in order to infer a rational combination strategy including cyclin-D1/CDK4-CDK6 inhibitors, RT, and/or other anticancer agents targeting G1-S phase cell cycle transition.
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Affiliation(s)
- Valerio Nardone
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (A.A.); (S.C.); (A.R.)
| | - Marcella Barbarino
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (M.B.); (A.G.)
| | - Antonio Angrisani
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (A.A.); (S.C.); (A.R.)
| | - Pierpaolo Correale
- Medical Oncology Unit, Grand Metropolitan Hospital “Bianchi-Melacrino-Morelli”, 89124 Reggio Calabria, Italy; (P.C.); (R.G.)
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA 19104, USA; (L.M.); (L.P.)
| | - Pierpaolo Pastina
- Section of Radiation Oncology, Medical School, University of Siena, 53100 Siena, Italy;
| | - Salvatore Cappabianca
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (A.A.); (S.C.); (A.R.)
| | - Alfonso Reginelli
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (A.A.); (S.C.); (A.R.)
| | - Luciano Mutti
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA 19104, USA; (L.M.); (L.P.)
| | - Clelia Miracco
- Pathological Anatomy Unit, Department of Medical, Surgical and Neurological Science, University of Siena, 53100 Siena, Italy;
| | - Rocco Giannicola
- Medical Oncology Unit, Grand Metropolitan Hospital “Bianchi-Melacrino-Morelli”, 89124 Reggio Calabria, Italy; (P.C.); (R.G.)
| | - Antonio Giordano
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (M.B.); (A.G.)
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA 19104, USA; (L.M.); (L.P.)
| | - Luigi Pirtoli
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA 19104, USA; (L.M.); (L.P.)
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