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Makita K, Hamamoto Y, Kanzaki H, Nagasaki K, Aogi K. Internal mammary node abnormality in imaging studies and treatment outcomes in patients with breast cancer. Oncol Lett 2024; 27:218. [PMID: 38586202 PMCID: PMC10995659 DOI: 10.3892/ol.2024.14352] [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: 11/17/2023] [Accepted: 02/22/2024] [Indexed: 04/09/2024] Open
Abstract
The clinical significance of mild internal mammary node (IMN) enlargement (Mild-IMN) is uncertain. This study aimed to evaluate the relationship between treatment outcomes and IMN status in patients with breast cancer who underwent postmastectomy radiation therapy between January 2010 and December 2018. Overall, 250 patients were categorized based on IMN status: Clinically normal IMN (Normal-IMN; n=172), Mild-IMN (n=39) and clinically metastatic IMN (cMet-IMN; n=39). None of the patients in the Normal- or Mild-IMN groups received IMN irradiation. In the cMet-IMN group, 25 patients underwent IMN irradiation with an IMN boost (10 Gy in 5 fractions), while 14 patients did not. The median follow-up time was 80.0 months (range, 7.2-147.6 months). The 7-year overall survival (OS), disease-free survival (DFS) and IMN recurrence-free survival (IRF) rates were 80.2, 73.0 and 93.4%, respectively. Multivariate analyses indicated that only cMet-IMN had a significant impact on OS [hazard ratio (HR), 1.66; 95% CI, 1.01-3.68; P=0.05] and DFS (HR, 1.91; 95% CI, 1.08-3.39; P=0.03), while cMet-IMN did not have a significant impact on IRF (HR, 1.66; 95% CI, 0.41-6.78; P=0.48). Additionally, receiving an IMN boost had no influence on OS (HR, 1.11; 95% CI, 0.37-2.34; P=0.84), DFS (HR, 1.28; 95% CI, 0.51-3.22; P=0.60) or IRF (HR, 1.94; 95% CI, 0.22-17.47; P=0.55). In conclusion, the impact of Mild-IMN on clinical outcomes was small. Although irradiation for cMet-IMN is important, the impact of the cMet-IMN boost with 10 Gy in 5 fractions on clinical outcomes may also be limited.
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Affiliation(s)
- Kenji Makita
- Department of Radiation Oncology, National Hospital Organization Shikoku Cancer Center, Matsuyama, Ehime 791-0280, Japan
- Department of Radiology, Ehime Prefectural Central Hospital, Matsuyama, Ehime 790-0024, Japan
| | - Yasushi Hamamoto
- Department of Radiation Oncology, National Hospital Organization Shikoku Cancer Center, Matsuyama, Ehime 791-0280, Japan
| | - Hiromitsu Kanzaki
- Department of Radiation Oncology, National Hospital Organization Shikoku Cancer Center, Matsuyama, Ehime 791-0280, Japan
| | - Kei Nagasaki
- Department of Radiation Oncology, National Hospital Organization Shikoku Cancer Center, Matsuyama, Ehime 791-0280, Japan
| | - Kenjiro Aogi
- Department of Breast Oncology, National Hospital Organization Shikoku Cancer Center, Matsuyama, Ehime 791-0280, Japan
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Pedersen MA, Dias AH, Hjorthaug K, Gormsen LC, Fledelius J, Johnsson AL, Borgquist S, Tramm T, Munk OL, Vendelbo MH. Increased lesion detectability in patients with locally advanced breast cancer-A pilot study using dynamic whole-body [ 18F]FDG PET/CT. EJNMMI Res 2024; 14:31. [PMID: 38528239 DOI: 10.1186/s13550-024-01096-4] [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: 12/13/2023] [Accepted: 03/14/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Accurate diagnosis of axillary lymph node (ALN) metastases is essential for prognosis and treatment planning in breast cancer. Evaluation of ALN is done by ultrasound, which is limited by inter-operator variability, and by sentinel lymph node biopsy and/or ALN dissection, none of which are without risks and/or long-term complications. It is known that conventional 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) has limited sensitivity for ALN metastases. However, a recently developed dynamic whole-body (D-WB) [18F]FDG PET/CT scanning protocol, allowing for imaging of tissue [18F]FDG metabolic rate (MRFDG), has been shown to have the potential to increase lesion detectability. The study purpose was to examine detectability of malignant lesions in D-WB [18F]FDG PET/CT compared to conventional [18F]FDG PET/CT. RESULTS This study prospectively included ten women with locally advanced breast cancer who were referred for an [18F]FDG PET/CT as part of their diagnostic work-up. They all underwent D-WB [18F]FDG PET/CT, consisting of a 6 min single bed dynamic scan over the chest region started at the time of tracer injection, a 64 min dynamic WB PET scan consisting of 16 continuous bed motion passes, and finally a contrast-enhanced CT scan, with generation of MRFDG parametric images. Lesion visibility was assessed by tumor-to-background and contrast-to-noise ratios using volumes of interest isocontouring tumors with a set limit of 50% of SUVmax and background volumes placed in the vicinity of tumors. Lesion visibility was best in the MRFDG images, with target-to-background values 2.28 (95% CI: 2.04-2.54) times higher than target-to-background values in SUV images, and contrast-to-noise values 1.23 (95% CI: 1.12-1.35) times higher than contrast-to-noise values in SUV images. Furthermore, five imaging experts visually assessed the images and three additional suspicious lesions were found in the MRFDG images compared to SUV images; one suspicious ALN, one suspicious parasternal lymph node, and one suspicious lesion located in the pelvic bone. CONCLUSIONS D-WB [18F]FDG PET/CT with MRFDG images show potential for improved lesion detectability compared to conventional SUV images in locally advanced breast cancer. Further validation in larger cohorts is needed. CLINICAL TRIAL REGISTRATION The trial is registered in clinicaltrials.gov, NCT05110443, https://www. CLINICALTRIALS gov/study/NCT05110443?term=NCT05110443&rank=1 .
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Affiliation(s)
- Mette Abildgaard Pedersen
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark.
| | - André H Dias
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
| | - Karin Hjorthaug
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
| | - Lars C Gormsen
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joan Fledelius
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
| | | | - Signe Borgquist
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Oncology, Aarhus University Hospital, Aarhus, Denmark
| | - Trine Tramm
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Pathology, Aarhus University Hospital, Aarhus, Denmark
| | - Ole Lajord Munk
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Mikkel Holm Vendelbo
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
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Robson N, Thekkinkattil DK. Current Role and Future Prospects of Positron Emission Tomography (PET)/Computed Tomography (CT) in the Management of Breast Cancer. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:321. [PMID: 38399608 PMCID: PMC10889944 DOI: 10.3390/medicina60020321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024]
Abstract
Breast cancer has become the most diagnosed cancer in women globally, with 2.3 million new diagnoses each year. Accurate early staging is essential for improving survival rates with metastatic spread from loco regional to distant metastasis, decreasing mortality rates by 50%. Current guidelines do not advice the routine use of positron emission tomography (PET)-computed tomography (CT) in the staging of early breast cancer in the absence of symptoms. However, there is a growing body of evidence to suggest that the use of PET-CT in this early stage can benefit the patient by improving staging and as a result treatment and outcomes, as well as psychological burden, without increasing costs to the health service. Ongoing research in PET radiomics and artificial intelligence is showing promising future prospects in its use in diagnosis, staging, prognostication, and assessment of responses to the treatment of breast cancer. Furthermore, ongoing research to address current limitations of PET-CT by improving techniques and tracers is encouraging. In this narrative review, we aim to evaluate the current evidence of the usefulness of PET-CT in the management of breast cancer in different settings along with its future prospects, including the use of artificial intelligence (AI), radiomics, and novel tracers.
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Affiliation(s)
- Nicole Robson
- Lincoln Medical School, Ross Lucas Medical Sciences Building, University of Lincoln, Lincoln LN6 7FS, UK;
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Sae-Lim C, Wu WP, Chang MC, Lai HW, Chen ST, Chou CT, Liao CY, Huang HI, Chen ST, Chen DR, Hung CL. Reliability of predicting low-burden (≤ 2) positive axillary lymph nodes indicating sentinel lymph node biopsy in primary operable breast cancer - a retrospective comparative study with PET/CT and breast MRI. World J Surg Oncol 2024; 22:12. [PMID: 38183069 PMCID: PMC10770957 DOI: 10.1186/s12957-023-03297-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 12/26/2023] [Indexed: 01/07/2024] Open
Abstract
BACKGROUND Sentinel lymph node biopsy (SLNB) is the standard of care for axillary staging in early breast cancer patients with low-burden axillary metastasis (≤ 2 positive nodes). This study aimed to determine the diagnostic performances of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and breast magnetic resonance imaging in detecting axillary lymph node (ALN) metastases and the reliability to predict ALN burden. METHODS A total of 275 patients with primary operable breast cancer receiving preoperative PET/CT and upfront surgery from January 2001 to December 2022 in a single institution were enrolled. A total of 244 (88.7%) of them also received breast MRI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PET/CT and breast MRI were assessed. The predictive values to determine ALN burden were evaluated using radio-histopathological concordance. RESULTS PET/CT demonstrated a sensitivity of 53.4%, specificity of 82.1%, PPV of 65.5%, NPV of 73.5%, and accuracy of 70.9% for detecting ALN metastasis, and the corresponding values for MRI were 71.8%, 67.8%, 56%, 80.8%, and 69.2%, respectively. Combining PET/CT and MRI showed a significantly higher PPV than MRI (72.7% vs 56% for MRI alone, p = 0.037) and a significantly higher NPV than PET/CT (84% vs 73.5% for PET/CT alone, p = 0.041). For predicting low-burden axillary metastasis (1-2 positive nodes), the PPVs were 35.9% for PET/CT, 36.7% for MRI, and 55% for combined PET/CT and MRI. Regarding patients with 0-2 positive ALNs in imaging, who were indicated for SLNB, the predictive correctness was 96.1% for combined PET/CT and MRI, 95.7% for MRI alone, and 88.6% for PET/CT alone. CONCLUSIONS PET/CT and breast MRI exhibit high predictive values for identifying low-burden axillary metastasis in patients with operable breast cancer with ≦ 2 positive ALNs on imaging.
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Affiliation(s)
- Chayanee Sae-Lim
- Department of Surgery, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Wen-Pei Wu
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Radiology, Changhua Christian Hospital, Changhua, Taiwan
- Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Che Chang
- Department of Nuclear Medicine, Changhua Christian Hospital, Changhua, Taiwan
| | - Hung-Wen Lai
- Division of General Surgery, Changhua Christian Hospital, Changhua, Taiwan.
- Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
- Endoscopic and Oncoplastic Breast Surgery Center, Changhua Christian Hospital, 135 Nanxiao Street, Changhua, 500, Taiwan.
- Minimally Invasive Surgery Research Center, Changhua Christian Hospital, Changhua, Taiwan.
- Division of Breast Surgery, Yuanlin Christian Hospital, Yuanlin, Taiwan.
- Kaohsiung Medical University, Kaohsiung, Taiwan.
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan.
- Department of Surgery, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Shu-Tian Chen
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi Branch, Chiayi, Taiwan
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
| | - Chen-Te Chou
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Radiology, Changhua Christian Hospital, Changhua, Taiwan
- Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chiung-Ying Liao
- Department of Radiology, Changhua Christian Hospital, Changhua, Taiwan
| | - Hsin-I Huang
- Department of Information Management, National Sun Yat-Sen University, Kaohsiung, Taiwan
| | - Shou-Tung Chen
- Division of General Surgery, Changhua Christian Hospital, Changhua, Taiwan
- Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan
| | - Dar-Ren Chen
- Division of General Surgery, Changhua Christian Hospital, Changhua, Taiwan
- Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan
| | - Che-Lun Hung
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
- Department of Computer Science and Communication Engineering, Providence University, Taichung, Taiwan
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Wang X, Li L, Wang L, Chen M. The expression of Ki-67 and Glypican -3 in hepatocellular carcinoma was evaluated by comparing DWI and 18F-FDG PET/CT. Front Oncol 2023; 13:1026245. [PMID: 37920165 PMCID: PMC10619679 DOI: 10.3389/fonc.2023.1026245] [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: 08/23/2022] [Accepted: 10/02/2023] [Indexed: 11/04/2023] Open
Abstract
Objective The value of DWI and 18F-FDG PET/CT in evaluating the expression of Ki-67 and GPC-3 in HCC was compared. Materials and methods Ninety-four patients with primary HCC confirmed by pathology were retrospectively divided into high- and low-Ki-67-expression groups and positive- and negative- GPC-3 groups. The ADC and SUVmax values of the lesions in both groups were measured. ROC curves were used to evaluate the identification efficiency of parameters with significant differences for each group of lesions, and AUCwas calculated. The combined ADC and SUVmax values were analyzed by binary logistic regression. The Delong test was used to compare the AUC values of the combined and single parameters. Pearson (in line with normal distribution) or Spearman (in line with abnormal distribution) correlation analysis was used to analyze the correlation. Results The ADC value of the high-Ki-67-expression group was lower than that of the low-Ki-67-expression group (P<0.05), and the SUVmax value of the high-expression group was higher than that of the low-expression group (P<0.05). The ADC value of the positive-GPC-3 group was lower than that of the negative group (P<0.0.tive group (P<0.05). The combined ADC and SUVmax values in the GPC-3 group were better than those of a single parameter (P<0.05). There was a strong negative correlation between the SUVmax value and ADC value in the Ki-67 group (R=-0.578, P<0.001) and a weak negative correlation between the SUVmax value and ADC value in the GPC-3 group (R=-0.279, P=0.006). The SUVmax value was strongly positively correlated with the Ki-67 expression index (R=0.733, P<0.001), while the ADC value was strongly negatively correlated with the Ki-67 expression index (R=-0.687, P<0.001). Conclusion DWI and 18F-FDG PET/CT can be used to evaluate the expression of Ki-67 and GPC-3 in HCC, and there is a certain correlation between the ADC value and SUVmax. Combined DWI and 18F-FDG PET/CT is superior to a single technique in evaluating the expression of GPC-3 in HCC patients. However, the combined model did not benefit the Ki-67 group.
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Affiliation(s)
- Xuedong Wang
- Department of Radiology, Zhuhai People’s Hospital (Zhuhai Hospital Affiliated Jinan University), Zhuhai, China
| | - Lei Li
- Department of Nuclear Medicine, Zhuhai People’s Hospital (Zhuhai Hospital Affiliated Jinan University), Zhuhai, China
| | - Linjie Wang
- Department of Pathology, Zhuhai People’s Hospital (Zhuhai Hospital Affiliated Jinan University), Zhuhai, China
| | - Min Chen
- Department of Radiology, Zhuhai People’s Hospital (Zhuhai Hospital Affiliated Jinan University), Zhuhai, China
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Ruan D, Sun L. Diagnostic Performance of PET/MRI in Breast Cancer: A Systematic Review and Bayesian Bivariate Meta-analysis. Clin Breast Cancer 2023; 23:108-124. [PMID: 36549970 DOI: 10.1016/j.clbc.2022.11.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 11/07/2022] [Accepted: 11/26/2022] [Indexed: 12/04/2022]
Abstract
INTRODUCTION By performing a systematic review and meta-analysis, the diagnostic value of 18F-FDG PET/MRI in breast lesions, lymph nodes, and distant metastases was assessed, and the merits and demerits of PET/MRI in the application of breast cancer were comprehensively reviewed. METHODS Breast cancer-related studies using 18F-FDG PET/MRI as a diagnostic tool published before September 12, 2022 were included. The pooled sensitivity, specificity, log diagnostic odds ratio (LDOR), and area under the curve (AUC) were calculated using Bayesian bivariate meta-analysis in a lesion-based and patient-based manner. RESULTS We ultimately included 24 studies (including 1723 patients). Whether on a lesion-based or patient-based analysis, PET/MRI showed superior overall pooled sensitivity (0.95 [95% CI: 0.92-0.98] & 0.93 [95% CI: 0.88-0.98]), specificity (0.94 [95% CI: 0.90-0.97] & 0.94 [95% CI: 0.92-0.97]), LDOR (5.79 [95% CI: 4.95-6.86] & 5.64 [95% CI: 4.58-7.03]) and AUC (0.98 [95% CI: 0.94-0.99] & 0.98[95% CI: 0.92-0.99]) for diagnostic applications in breast cancer. In the specific subgroup analysis, PET/MRI had high pooled sensitivity and specificity for the diagnosis of breast lesions and distant metastatic lesions and was especially excellent for bone lesions. PET/MRI performed poorly for diagnosing axillary lymph nodes but was better than for lymph nodes at other sites (pooled sensitivity, specificity, LDOR, AUC: 0.86 vs. 0.58, 0.90 vs. 0.82, 4.09 vs. 1.98, 0.89 vs. 0.84). CONCLUSION 18F-FDG PET/MRI performed excellently in diagnosing breast lesions and distant metastases. It can be applied to the initial diagnosis of suspicious breast lesions, accurate staging of breast cancer patients, and accurate restaging of patients with suspected recurrence.
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Affiliation(s)
- Dan Ruan
- Department of Nuclear Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Long Sun
- Department of Nuclear Medicine and Minnan PET Center, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Xiamen, China.
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Yur M, Aygen E, İlhan YS, Lale A, Ebiloğlu MF. The effect of the tumor-to-skin distance on axillary lymph node metastasis in breast cancer. REVISTA DA ASSOCIACAO MEDICA BRASILEIRA (1992) 2023; 69:e20221277. [PMID: 37098931 PMCID: PMC10176633 DOI: 10.1590/1806-9282.20221277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 01/20/2023] [Indexed: 04/27/2023]
Abstract
OBJECTIVE Tumor-to-skin distance is known to have an effect on axillary lymph node metastasis but has no clinical use with nomograms. This study aimed to investigate the effect of tumor-to-skin distance on axillary lymph node metastasis alone and in combination with nomogram for clinical use. METHODS A total of 145 patients who underwent surgery for breast cancer (T1-T2 stage) and whose axillary lymph nodes were evaluated (axillary dissection or sentinel lymph node biopsy) between January 2010 and December 2020 were included in the study. Tumor-to-skin distance and other pathological data of the patients were evaluated. RESULTS Of the 145 patients, 83 (57.2%) had metastatic lymph nodes in the axilla. Tumor-to-skin distance was different in terms of lymph node metastasis (p=0.045). In the receiver operating characteristic curve for tumor-to-skin distance, area under curve was 0.597 (95%CI 0.513-0.678, p=0.046), area under curve of the nomogram was 0.740 (95%CI 0.660-0.809), p<0.001) and nomogram+tumor-to-skin distance was 0.753 (95%CI 0.674-0.820), p<0.001). No statistical difference was found for axillary lymph node metastasis between the nomogram+tumor-to-skin distance and the nomogram alone (p=0.433). CONCLUSION Although tumor-to-skin distance demonstrated a significant difference in axillary lymph node metastasis, it had a poor association with an area under curve value of 0.597 and did not produce a significant improvement in predicting lymph node metastasis when combined with the nomogram. The tumor-to-skin distance may be unlikely to enter clinical practice.
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Affiliation(s)
- Mesut Yur
- Firat Üniversitesi, Department of Surgical Oncology - Elâzığ, Turkey
| | - Erhan Aygen
- Firat Üniversitesi, Department of Surgical Oncology - Elâzığ, Turkey
| | - Yavuz Selim İlhan
- Firat Üniversitesi, Department of Surgical Oncology - Elâzığ, Turkey
| | - Azmi Lale
- Fethi Sekin State Hospital, Department of Surgical Oncology - Elâzığ, Turkey
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Zhang X, Liu M, Ren W, Sun J, Wang K, Xi X, Zhang G. Predicting of axillary lymph node metastasis in invasive breast cancer using multiparametric MRI dataset based on CNN model. Front Oncol 2022; 12:1069733. [PMID: 36561533 PMCID: PMC9763602 DOI: 10.3389/fonc.2022.1069733] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022] Open
Abstract
Purpose To develop a multiparametric MRI model for predicting axillary lymph node metastasis in invasive breast cancer. Methods Clinical data and T2WI, DWI, and DCE-MRI images of 252 patients with invasive breast cancer were retrospectively analyzed and divided into the axillary lymph node metastasis (ALNM) group and non-ALNM group using biopsy results as a reference standard. The regions of interest (ROI) in T2WI, DWI, and DCE-MRI images were segmented using MATLAB software, and the ROI was unified into 224 × 224 sizes, followed by image normalization as input to T2WI, DWI, and DCE-MRI models, all of which were based on ResNet 50 networks. The idea of a weighted voting method in ensemble learning was employed, and then T2WI, DWI, and DCE-MRI models were used as the base models to construct a multiparametric MRI model. The entire dataset was randomly divided into training sets and testing sets (the training set 202 cases, including 78 ALNM, 124 non-ALNM; the testing set 50 cases, including 20 ALNM, 30 non-ALNM). Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of models were calculated. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic performance of each model for axillary lymph node metastasis, and the DeLong test was performed, P< 0.05 statistically significant. Results For the assessment of axillary lymph node status in invasive breast cancer on the test set, multiparametric MRI models yielded an AUC of 0.913 (95% CI, 0.799-0.974); T2WI-based model yielded an AUC of 0.908 (95% CI, 0.792-0.971); DWI-based model achieved an AUC of 0.702 (95% CI, 0.556-0.823); and the AUC of the DCE-MRI-based model was 0.572 (95% CI, 0.424-0.711). The improvement in the diagnostic performance of the multiparametric MRI model compared with the DWI and DCE-MRI-based models were significant (P< 0.01 for both). However, the increase was not meaningful compared with the T2WI-based model (P = 0.917). Conclusion Multiparametric MRI image analysis based on an ensemble CNN model with deep learning is of practical application and extension for preoperative prediction of axillary lymph node metastasis in invasive breast cancer.
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Affiliation(s)
- Xiaodong Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University, Jinan, China,Postgraduate Department, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, China
| | - Menghan Liu
- Department of Health Management, The First Affiliated Hospital of Shandong First Medical University, Jinan, China
| | - Wanqing Ren
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University, Jinan, China,Postgraduate Department, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, China
| | - Jingxiang Sun
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University, Jinan, China,Postgraduate Department, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, China
| | - Kesong Wang
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China
| | - Xiaoming Xi
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China
| | - Guang Zhang
- Department of Health Management, The First Affiliated Hospital of Shandong First Medical University, Jinan, China,*Correspondence: Guang Zhang,
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Li Z, Gao Y, Gong H, Feng W, Ma Q, Li J, Lu X, Wang X, Lei J. Different Imaging Modalities for the Diagnosis of Axillary Lymph Node Metastases in Breast Cancer: A Systematic Review and Network Meta-Analysis of Diagnostic Test Accuracy. J Magn Reson Imaging 2022; 57:1392-1403. [PMID: 36054564 DOI: 10.1002/jmri.28399] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Accurate diagnosis of axillary lymph node metastasis (ALNM) of breast cancer patients is important to guide local and systemic treatment. PURPOSE To evaluate the diagnostic performance of different imaging modalities for ALNM in patients with breast cancer. STUDY TYPE Systematic review and network meta-analysis (NMA). SUBJECTS Sixty-one original articles with 8011 participants. FIELD STRENGTH 1.5 T and 3.0 T. ASSESSMENT We used the QUADAS-2 and QUADAS-C tools to assess the risk of bias in eligible studies. The identified articles assessed ultrasonography (US), MRI, mammography, ultrasound elastography (UE), PET, CT, PET/CT, scintimammography, and PET/MRI. STATISTICAL ANALYSIS We used random-effects conventional meta-analyses and Bayesian network meta-analyses for data analyses. We used sensitivity and specificity, relative sensitivity and specificity, superiority index, and summary receiver operating characteristic curve (SROC) analysis to compare the diagnostic value of different imaging modalities. RESULTS Sixty-one studies evaluated nine imaging modalities. At patient level, sensitivities of the nine imaging modalities ranged from 0.27 to 0.84 and specificities ranged from 0.84 to 0.95. Patient-based NMA showed that UE had the highest superiority index (5.95) with the highest relative sensitivity of 1.13 (95% confidence interval [CI]: 0.93-1.29) among all imaging methods when compared to US. At lymph node level, MRI had the highest superiority index (6.91) with highest relative sensitivity of 1.13 (95% CI: 1.01-1.23) and highest relative specificity of 1.11 (95% CI: 0.95-1.23) among all imaging methods when compared to US. SROCs also showed that UE and MRI had the largest area under the curve (AUC) at patient level and lymph node level of 0.92 and 0.94, respectively. DATA CONCLUSION UE and MRI may be superior to other imaging modalities in the diagnosis of ALNM in breast cancer patients at the patient level and the lymph node level, respectively. Further studies are needed to provide high-quality evidence to validate our findings. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhifan Li
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Ya Gao
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Hengxin Gong
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Wen Feng
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Qinqin Ma
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Jinkui Li
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Xingru Lu
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Xiaohui Wang
- Department of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, China
| | - Junqiang Lei
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, China
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10
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Stanzione A, Romeo V. Editorial for "Different Imaging Modalities for the Diagnosis of Axillary Lymph Node Metastases in Breast Cancer: A Systematic Review and Network Meta-Analysis". J Magn Reson Imaging 2022; 57:1404-1405. [PMID: 36017549 DOI: 10.1002/jmri.28409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 08/09/2022] [Indexed: 11/07/2022] Open
Affiliation(s)
- Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
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11
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de Mooij CM, Samiei S, Mitea C, Lobbes MBI, Kooreman LFS, Heuts EM, Beets-Tan RGH, van Nijnatten TJA, Smidt ML. Axillary lymph node response to neoadjuvant systemic therapy with dedicated axillary hybrid 18F-FDG PET/MRI in clinically node-positive breast cancer patients: a pilot study. Clin Radiol 2022; 77:e732-e740. [PMID: 35850866 DOI: 10.1016/j.crad.2022.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 06/07/2022] [Accepted: 06/20/2022] [Indexed: 11/26/2022]
Abstract
AIM To investigate the diagnostic performance of dedicated axillary hybrid 18F-2-[18F]-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) in detecting axillary pathological complete response (pCR) following neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer patients. MATERIALS AND METHODS Ten prospectively included clinically node-positive breast cancer patients underwent dedicated axillary hybrid 18F-FDG PET/MRI after completing NST followed by axillary surgery. PET images were reviewed by a nuclear medicine physician and coronal T1-weighted and T2-weighted MRI images by a radiologist. All axillary lymph nodes visible on PET/MRI were matched with those removed during axillary surgery. Diagnostic performance parameters were calculated based on patient-by-patient and node-by-node validation with histopathology of the axillary surgical specimen as the reference standard. RESULTS Six patients achieved axillary pCR at final histopathology. A total of 84 surgically harvested axillary lymph nodes were matched with axillary lymph nodes depicted on PET/MRI. Histopathological examination of the matched axillary lymph nodes resulted in 10 lymph nodes with residual axillary disease of which eight contained macrometastases and two micrometastases. The patient-by-patient analysis yielded a sensitivity, specificity, positive predictive value, and negative predictive value of 25%, 100%, 100%, and 67%, respectively. The diagnostic performance parameters of the node-by-node analysis were 0%, 96%, 0%, and 88%, respectively. Excluding micrometastases from the node-by-node analysis increased the negative predictive value to 90%. CONCLUSION This pilot study suggests that the negative predictive value and sensitivity of dedicated axillary 18F-FDG PET/MRI are insufficiently accurate to detect axillary pCR or exclude residual axillary disease following NST in clinically node-positive breast cancer patients.
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Affiliation(s)
- C M de Mooij
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; Department of Surgery, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands.
| | - S Samiei
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; Department of Surgery, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands
| | - C Mitea
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands
| | - M B I Lobbes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands; Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands
| | - L F S Kooreman
- GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands; Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands
| | - E M Heuts
- Department of Surgery, Maastricht University Medical Center+, Maastricht, the Netherlands
| | - R G H Beets-Tan
- GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands; Department of Radiology, Antoni van Leeuwenhoek/Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - T J A van Nijnatten
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands
| | - M L Smidt
- Department of Surgery, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands
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12
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Qiu Y, Zhang X, Wu Z, Wu S, Yang Z, Wang D, Le H, Mao J, Dai G, Tian X, Zhou R, Huang J, Hu L, Shen J. MRI-Based Radiomics Nomogram: Prediction of Axillary Non-Sentinel Lymph Node Metastasis in Patients With Sentinel Lymph Node-Positive Breast Cancer. Front Oncol 2022; 12:811347. [PMID: 35296027 PMCID: PMC8920306 DOI: 10.3389/fonc.2022.811347] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 02/01/2022] [Indexed: 11/23/2022] Open
Abstract
Background Overtreatment of axillary lymph node dissection (ALND) may occur in patients with axillary positive sentinel lymph node (SLN) but negative non-SLN (NSLN). Developing a magnetic resonance imaging (MRI)-based radiomics nomogram to predict axillary NSLN metastasis in patients with SLN-positive breast cancer could effectively decrease the probability of overtreatment and optimize a personalized axillary surgical strategy. Methods This retrospective study included 285 patients with positive SLN breast cancer. Fifty five of them had metastatic NSLNs and 230 had non-metastatic NSLNs. MRI-based radiomic features of primary tumors were extracted and MRI morphologic findings of the primary tumor and axillary lymph nodes were assessed. Four models, namely, a radiomics signature, an MRI-clinical nomogram, and two MRI-clinical-radiomics nomograms were established based on MRI morphologic findings, clinicopathologic characteristics, and MRI-based radiomic features to predict the NSLN status. The optimal predictors in each model were selected using the 5-fold cross-validation (CV) method. Their predictive performances were determined by the receiver operating characteristic (ROC) curves analysis. The area under the curves (AUCs) of different models was compared by the Delong test. Their discrimination capability, calibration curve, and clinical usefulness were also assessed. Results The 5-fold CV analysis showed that the AUCs ranged from 0.770 to 0.847 for the radiomics signature, from 0.720 to 0.824 for the MRI-clinical nomogram, from 0.843 to 0.932 for the MRI-clinical-radiomics nomogram. The optimal predictive factors in the radiomics signature, MRI-clinical nomogram, and MRI-clinical-radiomics nomogram were one texture feature of diffusion-weighted imaging (DWI), two clinicopathologic features together with one MRI morphologic finding, and the DWI-based texture feature together with the two clinicopathologic features plus the one MRI morphologic finding, respectively. The MRI-clinical-radiomics nomogram with CA 15-3 included achieved the highest AUC compared with the radiomics signature (0.868 vs. 0.806, P <0.001) and MRI-clinical nomogram (0.868 vs. 0.761; P <0.001). In addition, the MRI-clinical-radiomics nomogram without CA 15-3 showed a higher performance than that of the radiomics signature (AUC, 0.852 vs. 0.806, P = 0.016) and the MRI-clinical nomogram (AUC, 0.852 vs. 0.761, P = 0.007). The MRI-clinical-radiomics nomograms showed good discrimination and good calibration. Decision curve analysis demonstrated that the MRI-clinical-radiomics nomograms were clinically useful. Conclusion The MRI-clinical-radiomics nomograms developed in our study showed high predictive performance, which can be used to predict the axillary NSLN status in SLN-positive breast cancer patients before surgery.
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Affiliation(s)
- Ya Qiu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
- Department of Radiology, the First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Xiang Zhang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Zhiyuan Wu
- School of Public Health, Capital Medical University, Beijing, China
| | - Shiji Wu
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
- Department of Ultrasound, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Ultrasound, the First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Zehong Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Dongye Wang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Hongbo Le
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Jiaji Mao
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Guochao Dai
- Department of Radiology, the First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Xuwei Tian
- Department of Radiology, the First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Renbing Zhou
- Department of Radiology, the First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Jiayi Huang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Lanxin Hu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Jun Shen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Epigenetics and Gene Regulation of Malignant Tumors, Sun Yat-sen Memorial Hospital, Guangzhou, China
- *Correspondence: Jun Shen,
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18F-Alfatide II for the evaluation of axillary lymph nodes in breast cancer patients: comparison with 18F-FDG. Eur J Nucl Med Mol Imaging 2022; 49:2869-2876. [PMID: 35138445 DOI: 10.1007/s00259-021-05333-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 03/23/2021] [Indexed: 11/04/2022]
Abstract
PURPOSE 18F-Alfatide II has been translated into clinical use and been proven to have good performance in identifying breast cancer. In this study, we investigated 18F-Alfatide II for evaluation of axillary lymph nodes (ALN) in breast cancer patients and compared the performance with 18F-FDG. METHODS A total of 44 female patients with clinically suspected breast cancer were enrolled and underwent 18F-Alfatide II and 18F-FDG PET/CT within a week. Tracer uptakes in ALN were evaluated by visual analysis, semi-quantitative analysis with maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and SUVmax ratio of target/non-target (T/NT). RESULTS Among 44 patients, 37 patients were pathologically diagnosed with breast cancer with metastatic (17 cases) or non-metastatic (20 cases) ALN. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of visual analysis were 70.6%, 90%, 81.1%, 85.7%, and 78.3% for 18F-Alfatide II, 64.7%, 90%, 78.4%, 84.6%, and 75% for 18F-FDG, respectively. By combining 18F-Alfatide II and 18F-FDG, the sensitivity significantly increased to 82.4%, the specificity was 85%, the accuracy increased to 83.8%, the PPV was 82.4%, and the NPV significantly increased to 85.0%. Three cases of luminal B subtype were false negative for both 18F-Alfatide II and 18F-FDG. The other 2 false negative cases of 18F-Alfatide II were triple-negative subtype and 3 false negative cases of 18F-FDG were luminal B subtype too. The AUCs of three semi-quantitative parameters (SUVmax, SUVmean, T/NT) for 18F-Alfatide II were between 0.8 and 0.9, whereas those for 18F-FDG were more than 0.9. 18F-Alfatide II T/NT had the highest Youden index (76.5%), specificity (100%), accuracy (89.2%), and PPV (100%) among these semi-quantitative parameters. 18F-Alfatide II uptake as well as 18F-FDG uptake in metastatic axillary lymph nodes (MALN) was significantly higher than that in benign axillary lymph nodes (BALN). Both 18F-Alfatide II and 18F-FDG did not show difference in primary tumor uptake irrespective of ALN status. CONCLUSION 18F-Alfatide II can be used in breast cancer patients to detect metastatic ALN, however, like 18F-FDG, with high specificity but relatively low sensitivity. The combination of 18F-Alfatide II and 18F-FDG can significantly improve sensitivity and NPV. 18F-Alfatide II T/NT may serve as the most important semi-quantitative parameter to evaluate ALN.
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Kang J, Yoo TK, Lee A, Kang J, Yoon CI, Kang BJ, Kim SH, Park WC. Avoiding unnecessary intraoperative sentinel lymph node frozen section biopsy of patients with early breast cancer. Ann Surg Treat Res 2022; 102:241-247. [PMID: 35611090 PMCID: PMC9111965 DOI: 10.4174/astr.2022.102.5.241] [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: 12/22/2021] [Revised: 03/26/2022] [Accepted: 04/12/2022] [Indexed: 11/30/2022] Open
Abstract
Purpose After the publication of the ACOSOG (American College of Surgeons Oncology Group) Z0011 trial, the rate of axillary lymph node dissection has reduced. Thus, the need for intraoperative frozen section biopsy of sentinel lymph nodes (SLNs) has become controversial. We identified patients for whom intraoperative SLN frozen section biopsy could be omitted and found that frozen section biopsy rate can be reduced. Methods We reviewed the records of patients with tumors ≤5 cm in diameter who underwent breast-conserving surgery between January 2013 and December 2019 at Seoul St. Mary’s Hospital. Clinicopathological and imaging characteristics were compared according to number of positive SLNs (0–2 SLNs positive vs. ≥3 SLNs positive). Results A total of 1,983 patients were included in this study. Thirty-two patients (1.6%) had at least 3 positive SLNs. Patients with ≥3 positive SLNs had significantly larger tumors and were more frequently high-grade tumors (P < 0.001 and P = 0.002, respectively). Identification of suspicious lymph nodes on imaging studies was also associated with the presence of ≥3 positive SLNs (hazard ratio, 11.54; 95% confidence interval, 4.42–30.10). All patients with none or only 1 suspicious lymph node on any imaging modality (n = 647, 32.6%) had 0–2 positive SLNs. Also, among patients with clinical T1-stage tumors and at least 2 suspicious lymph nodes on only 1 imaging modality (n = 514, 25.9%), only 2 cases had ≥3 positive SLNs. Conclusion We found that intraoperative SLN frozen biopsy could be omitted in patients using tumor size and axillary lymph node status on imaging modality.
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Affiliation(s)
- Jongwon Kang
- Department of Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Tae-Kyung Yoo
- Division of Breast Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Ahwon Lee
- Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jun Kang
- Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Chang Ik Yoon
- Department of Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Bong Joo Kang
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sung Hun Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Woo Chan Park
- Department of Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Karami K, Anbari K. Breast Cancer: A Review of Risk Factors and New Insights into Treatment. CURRENT CANCER THERAPY REVIEWS 2021. [DOI: 10.2174/1573394717999210120195208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Today, despite significant advances in cancer treatment have been made, breast cancer
remains one of the main health problems and considered a top biomedical investigation urgency.
The present study reviewed the common conventional chemotherapy agents and also some alternative
and complementary approaches such as oncolytic virotherapy, bacteriotherapy, nanotherapy,
immunotherapy, and natural products, which are recommended for breast cancer treatment. In addition
to current surgery approaches such as mastectomy, in recent years, a number of novel techniques
such as robotic mastectomies, nipple-sparing mastectomy, skin-sparing mastectomy, daycase
mastectomy were used in breast cancer surgery. In this review, we summarize new insights
into risk factors, surgical and non-surgical treatments for breast cancer.
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Affiliation(s)
- Kimia Karami
- Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Khatereh Anbari
- Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
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Kasem J, Wazir U, Mokbel K. Sensitivity, Specificity and the Diagnostic Accuracy of PET/CT for Axillary Staging in Patients With Stage I-III Cancer: A Systematic Review of The Literature. In Vivo 2021; 35:23-30. [PMID: 33402446 DOI: 10.21873/invivo.12228] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND/AIM Axillary lymph node (ALN) status plays a key role in the staging of breast cancer. Positron Emission Tomography/Computed Tomography (PET/CT) using 18-Fluorodeoxyglucose (18FDG) can visualise ALN metastasis. However, its utility compared to current methods is unclear. We systematically reviewed the role of 18FDG PET/CT in breast cancer staging. MATERIALS AND METHODS PubMed, Ovid and Cochrane were searched systematically up until August 2020. Included papers had true positive (TP), false positive (FP), true negative (TN) and false negative (FN) rates, sensitivity, specificity, accuracy, positive (PPV) and negative predictive value (NPV). RESULTS Nine studies (n=1486) were included, showing: i) sensitivity=52.2%, ii) specificity=91.6%, iii) PPV=77.8%, iv) NPV=77.2, and v) accuracy=77.3%. CONCLUSION 18FDG-PET/CT has a low sensitivity but high specificity for ALN disease. Therefore, ultrasound-guided biopsy could be considered in a positive CT/PET. Modest accuracy prohibits the use of 18FDG-PET/CT alone in axillary staging. Prospective research using standardised protocols and quantitative cut-off points is warranted.
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Affiliation(s)
- Judi Kasem
- London Breast Institute, Princess Grace Hospital, London, U.K
| | - Umar Wazir
- London Breast Institute, Princess Grace Hospital, London, U.K.,Department of General Surgery, Khyber Teaching Hospital, Peshawar, Pakistan
| | - Kefah Mokbel
- London Breast Institute, Princess Grace Hospital, London, U.K.;
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Iodine Map Radiomics in Breast Cancer: Prediction of Metastatic Status. Cancers (Basel) 2021; 13:cancers13102431. [PMID: 34069795 PMCID: PMC8157278 DOI: 10.3390/cancers13102431] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 05/14/2021] [Accepted: 05/15/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Early and accurate diagnosis of breast cancer that has spread to other organs and tissues is crucial, as therapeutic decisions and outcome expectations might change. Computed tomography (CT) is often used to detect breast cancer’s spread, but this method has its weaknesses. The computer-assisted technique “radiomics” extracts grey-level patterns, so-called radiomic features, from medical images, which may reflect underlying biological processes. Our retrospective study therefore evaluated whether breast cancer spread can be predicted by radiomic features derived from iodine maps, an application on a new generation of CT scanners visualizing tissue blood flow. Based on 77 patients with newly diagnosed breast cancer, we found that this approach might indeed predict cancer spread to other organs/tissues. In the future, radiomics may serve as an additional tool for cancer detection and risk assessment. Abstract Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.
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Byon JH, Park YV, Yoon JH, Moon HJ, Kim EK, Kim MJ, You JK. Added Value of MRI for Invasive Breast Cancer including the Entire Axilla for Evaluation of High-Level or Advanced Axillary Lymph Node Metastasis in the Post-ACOSOG Z0011 Trial Era. Radiology 2021; 300:46-54. [PMID: 33904772 DOI: 10.1148/radiol.2021202683] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background In the post-American College of Surgeons Oncology Group Z0011 trial era, radiologists have increasingly focused on excluding high-level or advanced axillary lymph node metastasis (ALNM) by using an additional MRI scan positioned higher than lower axillae; however, the value of these additional scans remains undetermined. Purpose To evaluate whether a standard MRI protocol is sufficient to exclude high-level or advanced ALNM in breast cancer or additional MRI of entire axilla is needed. Materials and Methods This retrospective study evaluated women with invasive breast cancer who underwent breast MRI from April 2015 to December 2016. Some underwent neoadjuvant chemotherapy (NAC) and others underwent upfront surgery. Standard (routine axial scans including the lower axillae) and combined (routine axial scans plus additional scans including the entire axilla) MRI protocols were compared for high-level or advanced ALNM detection. Clinical-pathologic characteristics were analyzed. Uni- and multivariable logistic regression was performed to identify predictors of high-level or advanced ALNM. Results A total of 435 women (mean age ± standard deviation, 52 years ± 11) were evaluated (65 in the NAC group, 370 in the non-NAC group). With the standard MRI protocol, predictors of high-level ALNM were peritumoral edema (odds ratio [OR], 12.3; 95% CI: 3.9, 39.4; P < .001) and positive axilla (OR, 5.9; 95% CI: 2.0, 15.2; P < .001). Only three of 289 women with negative axillae without peritumoral edema had high-level ALNM. Predictors of advanced ALNM were positive axillae (OR, 8.9; 95% CI: 3.7, 21.5; P < .001) and peritumoral edema (OR, 2.8; 95% CI: 1.1, 6.9; P = .03). Only six of 310 women who had negative axillae without peritumoral edema had advanced ALNM. Conclusion The performance of standard MRI was satisfactory in excluding high-level and advanced axillary lymph node metastasis in most patients with breast cancer. However, the presence of peritumoral edema or positive axillae in the MRI findings emphasizes the benefits of a combined MRI protocol. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Abe in this issue.
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Affiliation(s)
- Jung Hee Byon
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Youngjean Vivian Park
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Jung Hyun Yoon
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Hee Jung Moon
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Eun-Kyung Kim
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Min Jung Kim
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
| | - Jai Kyung You
- From the Department of Radiology, Yonsei University College of Medicine, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea (J.H.B., Y.V.P., J.H.Y., H.J.M., E.K.K., M.J.K.); Department of Radiology and Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Republic of Korea (J.H.B.); Department of Radiology, Yonsei University College of Medicine, Yongin Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yongin, Gyeonggi-do, Republic of Korea (E.K.K.); and Department of Radiology, NHIS Ilsan Hospital, Goyang, Republic of Korea (J.K.Y.)
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Extra-axillary nodal metastases in breast cancer: comparison of ultrasound, MRI, PET/CT, and CT. Clin Imaging 2021; 79:113-118. [PMID: 33933824 DOI: 10.1016/j.clinimag.2021.03.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 03/15/2021] [Accepted: 03/19/2021] [Indexed: 02/05/2023]
Abstract
PURPOSE To evaluate how ultrasound (US), MRI, PET/CT, and CT predict extra-axillary nodal metastases. SUBJECTS AND METHODS This IRB approved, retrospective study consisted of 124 suspicious supraclavicular and 88 internal mammary (IM) nodal cases with US and at least one additional cross-sectional examination (MRI, PET/CT or CT) from a total of 1472 invasive cancers with staging nodal US between January 2016-January 2019. Imaging findings were compared with the true node status, determined by fine needle aspirate (FNA) biopsy or evidence of response to chemotherapy on follow up imaging. RESULTS In the supraclavicular region, US had accuracy 98.2%, consisting of 97 true positives (TP), 27 false positives (FP), and 1348 true negative (TN). 93.5% of suspicious supraclavicular nodes had FNA for a PPV 78.2%. PET/CT had accuracy 88.6% (26 TP, 5 TN and 4 false negatives (FN)). CT exams had accuracy 61.7% (42 TP, 16 TN, 7 FP, and 29 FN). In the IM region, US had accuracy 93.2% (82 TP, 1 FP, 5 FN, and 1384 TN) but only 43.2% of suspicious IM nodes had FNA for a PPV 98.8%. MRI had accuracy 100.0% (all 47 TP). PET/CT exams had accuracy 96.8% (30 TP and 1FN). CT exams had accuracy 62.7% (36 TP, 1 TN, and 22 FN). CONCLUSION US/FNA has accuracy 98.2% and 93.2% in the supraclavicular and IM regions, however only 43.2% of suspicious IM nodes are directly sampled. In these cases, MRI or PET/CT can be used to problem solve and guide treatment decisions.
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Prediction of axillary nodal burden in patients with invasive lobular carcinoma using MRI. Breast Cancer Res Treat 2021; 186:463-473. [PMID: 33389406 DOI: 10.1007/s10549-020-06056-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 12/09/2020] [Indexed: 01/07/2023]
Abstract
PURPOSE To investigate clinical and imaging features associated with a high nodal burden (≥ 3 metastatic lymph nodes [LNs]) and compare diagnostic performance of US and MRI in patients with invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC). METHODS Retrospective search revealed 239 patients with ILC and 999 with IDC who underwent preoperative US and MRI between January 2016 and June 2019. Patients with ILC were propensity-score-matched with patients with IDC. Univariate and multivariate logistic regression analyses were performed to determine factors associated with ≥ 3 metastatic LNs. RESULTS 412 patients (206 ILC and 206 IDC) were evaluated. Of all patients with ILC, 27.2% (56/206) were node-positive and 7.8% (16/206) showed a high nodal burden. In multivariate analysis, the clinical N stage was the only independent factor associated with a high nodal burden in patients with IDC (odds ratio [OR] 6.24; 95% confidence interval [CI] 1.57-24.73; P = 0.009), but not in patients with ILC. Increased cortical thickness with loss of fatty hilum on US was associated with a high nodal burden in patients with ILC (OR 58.40; 95% CI 5.09-669.71; P = 0.001) and IDC (OR 24.14; 95% CI 3.52-165.37; P = 0.001), while suspicious LN findings at MRI were independently associated with a high nodal burden in ILC only (OR 13.94; 95% CI 2.61-74.39; P = 0.002). CONCLUSION In patients with ILC, MRI findings of suspicious LNs were helpful to predict a high nodal disease burden.
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