Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer

Li, Yanbo; Chen, Yongzi; Zhao, Rui; Ji, Yu; Li, Junnan; Zhang, Ying; Lü, Hong

doi:10.1007/s00330-021-08291-0

Cited by 26 publications

(16 citation statements)

References 54 publications

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“…These characteristics may make it possible to monitor the therapeutic effect of anti‐PD‐1/anti‐PD‐L1 antibodies with DCE‐MRI 20 . Several studies have used DKI and DCE‐MRI to assess breast cancer response to treatment, suggesting that the obtained parameters can characterize tumor microstructure and tumor vascular permeability, which can be used to evaluate the efficacy of tumor therapy 21,22 . However, most of the tumor therapy strategies used in these studies were chemotherapy.…”

mentioning

confidence: 99%

Evaluation of the Effects of Anti‐PD‐1 Therapy on Triple‐Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast‐Enhanced Imaging

Tang

Wang

Jin

et al. 2022

Magnetic Resonance Imaging

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Background The monitoring of immunotherapies is still based on changes in the tumor size in imaging, with a long evaluation period and low sensitivity. Purpose To investigate the effectiveness of diffusion kurtosis imaging (DKI) and dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) in assessing the therapeutic efficacy of anti‐programmed death‐1 (PD‐1) therapy in a mouse triple negative breast cancer (TNBC) model. Study Type Prospective. Animal Model A total of 54 BALB/c mouse subcutaneous 4 T1 transplantation models of TNBC. Field Strength/Sequence A 3.0‐T; turbo spin echo (TSE) T2‐weighted imaging, DKI with seven b values (0, 500, 1000, 1500, 2000, 2500, and 3000 sec/mm2) and T1‐twist DCE acquisition series. Assessment DKI and DCE‐MRI parameters were evaluated by two radiologists independently. Regions of interest (ROIs) were drawn manually on the maximum cross‐sectional area of the lesion; care was taken to avoid necrotic areas. The tumor cell density, the CD45 and CD31 levels were analyzed by two pathologists. Statistical Tests The two‐tailed unpaired t‐test, Mann–Whitney U test, Fisher's exact test and Pearson correlation coefficient were performed. A P < 0.05 was considered statistically significant. Results The apparent diffusion coefficient (ADC), mean diffusivity (MD), Ktrans and Kep values were significantly different between the two groups at each time point after treatment. There were significant differences in the mean kurtosis (MK) and Ve values between the two groups at 5 and 10 days after treatment but no significant differences at 15 days (P = 0.317 and 0.183, respectively). The ADC and MD values were significantly correlated with tumor cell density (ADC, r = −0.833; MD, r = 0.890) and the CD45 level (ADC, r = 0.720; MD, r = 0.718). The Ktrans and Kep values were significantly correlated with the CD31 level (Ktrans, r = 0.820; Kep, r = 0.683). Data Conclusion DKI and DCE‐MRI could reflect the changes in tumor microstructure and tumor tissue vasculature after anti‐PD‐1 therapy, respectively. Level of Evidence 1 Technical Efficacy Stage 4.

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confidence: 99%

Evaluation of the Effects of Anti‐PD‐1 Therapy on Triple‐Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast‐Enhanced Imaging

Tang

Wang

Jin

et al. 2022

Magnetic Resonance Imaging

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“…The clinical information, including serum CA153, CA125, and carcinoembryonic antigen (CEA) levels, and body mass index (BMI), were acquired by reviewing the medical records. BMI was calculated by dividing the patient’s weight (kg) by the square of the height (m 2 ), with a cutoff value of 24 kg/m 2 for classification ( 24 ).…”

Section: Methodsmentioning

confidence: 99%

“…The expression levels of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 antigen were measured through Immunohistochemical (IHC) analyses ( 16 , 26 ). ≤1% of carcinoma nuclei with positive staining indicated that ER and PR were negative ( 16 , 24 , 26 ). The IHC score was - or 1 +, indicating that HER-2 was negative, while 3+ indicating the positive expression of HER-2.…”

Section: Methodsmentioning

confidence: 99%

Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound

Zeng

et al. 2022

Front. Oncol.

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PurposeThe aim of this study was to develop a radiomics nomogram based on grayscale ultrasound (US) for preoperatively predicting Lymphovascular invasion (LVI) in patients with pathologically confirmed T1 (pT1) breast invasive ductal carcinoma (IDC).MethodsOne hundred and ninety-two patients with pT1 IDC between September 2020 and August 2022 were analyzed retrospectively. Study population was randomly divided in a 7: 3 ratio into a training dataset of 134 patients (37 patients with LVI-positive) and a validation dataset of 58 patients (19 patients with LVI-positive). Clinical information and conventional US (CUS) features (called clinic_CUS features) were recorded and evaluated to predict LVI. In the training dataset, independent predictors of clinic_CUS features were obtained by univariate and multivariate logistic regression analyses and incorporated into a clinic_CUS prediction model. In addition, radiomics features were extracted from the grayscale US images, and the radiomics score (Radscore) was constructed after radiomics feature selection. Subsequent multivariate logistic regression analysis was also performed for Radscore and the independent predictors of clinic_CUS features, and a radiomics nomogram was developed. The performance of the nomogram model was evaluated via its discrimination, calibration, and clinical usefulness.ResultsThe US reported axillary lymph node metastasis (LNM) (US_LNM) status and tumor margin were determined as independent risk factors, which were combined for the construction of clinic_CUS prediction model for LVI in pT1 IDC. Moreover, tumor margin, US_LNM status and Radscore were independent predictors, incorporated as the radiomics nomogram model, which achieved a superior discrimination to the clinic_CUS model in the training dataset (AUC: 0.849 vs. 0.747; P < 0.001) and validation dataset (AUC: 0.854 vs. 0.713; P = 0.001). Calibration curve for the radiomic nomogram showed good concordance between predicted and actual probability. Furthermore, decision curve analysis (DCA) confirmed that the radiomics nomogram had higher clinical net benefit than the clinic_CUS model.ConclusionThe US-based radiomics nomogram, incorporating tumor margin, US_LNM status and Radscore, showed a satisfactory preoperative prediction of LVI in pT1 IDC patients.

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“…In a study by Li et al [ 79 ], a nomogram based on baseline dynamic CE-MRI was developed to predict pCR; in particular, it was observed that time to peak (TTP), tumor volume measured on CE-MRI and androgen receptor (AR) grade were independent predictors of pCR.…”

Section: Early Prediction Of Pathological Outcome After Nactmentioning

confidence: 99%

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Panico

Ferrara

Woitek

et al. 2022

Cancers

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Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected patients.

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Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer

Cited by 26 publications

References 54 publications

Evaluation of the Effects of Anti‐PD‐1 Therapy on Triple‐Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast‐Enhanced Imaging

Evaluation of the Effects of Anti‐PD‐1 Therapy on Triple‐Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast‐Enhanced Imaging

Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

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