Is the presence of edema and necrosis on T2WI pretreatment breast MRI the key to predict pCR of triple negative breast cancer?

Harada, Taiyo L; Uematsu, Takayoshi; Nakashima, Kazuaki; Sugino, Takashi; Nishimura, S.; Takahashi, Kaoru; Hayashi, Takuma; Tadokoro, Yukiko; Watanabe, Junichiro; Nakamoto, Shogo; Ito, Takahiro

doi:10.1007/s00330-020-06662-7

Cited by 28 publications

(22 citation statements)

References 41 publications

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“…It is also interesting to note that only some semantic features survived to the features selection process, such as the DCE-Kinetic Curve, which represents the tumor intrinsic vascularization, closely connected with the lesion aggressiveness and edema, as strongly reported in literature [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. However, for all the histological labels, the majority of selected features were radiomics, and in particular second-order ones.…”

Section: Discussionmentioning

confidence: 94%

“…Both malignant and benign lesions, such as mastitis, previous radiotherapy, post-surgical inflammation, nephrotic syndrome, lymphoma, venous congestion, and chronic heart disease can be a cause of diffuse breast edema [ 34 ]. Focal edema, studied in T2WI sequences, however, is associated with malignant lesions in most cases [ 10 , 13 , 35 , 36 , 37 , 38 ].…”

Section: Discussionmentioning

confidence: 99%

“…Breast edema is not considered a major prognostic factor in current national and international guidelines (ACR and AIOM) [ 8 , 9 ]. However, several studies have shown a correlation between breast edema and tumor aggressiveness [ 10 , 11 , 12 , 13 , 14 ]. Focal edema is mostly correlated with malignancy, representing an indirect sign of peritumoral vascular invasion and inflammation.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Tumor Edema on T2-Weighted 3T-MRI Invasive Breast Cancer Histological Characterization: A Pilot Radiomics Study

Santucci

Faiella

Cordelli

et al. 2021

Cancers

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Background: to evaluate the contribution of edema associated with histological features to the prediction of breast cancer (BC) prognosis using T2-weighted MRI radiomics. Methods: 160 patients who underwent staging 3T-MRI from January 2015 to January 2019, with 164 histologically proven invasive BC lesions, were retrospectively reviewed. Patient data (age, menopausal status, family history, hormone therapy), tumor MRI-features (location, margins, enhancement) and histological features (histological type, grading, ER, PgR, HER2, Ki-67 index) were collected. Of the 160 MRI exams, 120 were considered eligible, corresponding to 127 lesions. T2-MRI were used to identify edema, which was classified in four groups: peritumoral, pre-pectoral, subcutaneous, or diffuse. A semi-automatic segmentation of the edema was performed for each lesion, using 3D Slicer open-source software. Main radiomics features were extracted and selected using a wrapper selection method. A Random Forest type classifier was trained to measure the performance of predicting histological factors using semantic features (patient data and MRI features) alone and semantic features associated with edema radiomics features. Results: edema was absent in 37 lesions and present in 127 (62 peritumoral, 26 pre-pectoral, 16 subcutaneous, 23 diffuse). The AUC-classifier obtained by associating edema radiomics with semantic features was always higher compared to the AUC-classifier obtained from semantic features alone, for all five histological classes prediction (0.645 vs. 0.520 for histological type, 0.789 vs. 0.590 for grading, 0.487 vs. 0.466 for ER, 0.659 vs. 0.546 for PgR, and 0.62 vs. 0.573 for Ki67). Conclusions: radiomic features extracted from tumor edema contribute significantly to predicting tumor histology, increasing the accuracy obtained from the combination of patient clinical characteristics and breast imaging data.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Impact of Tumor Edema on T2-Weighted 3T-MRI Invasive Breast Cancer Histological Characterization: A Pilot Radiomics Study

Santucci

Faiella

Cordelli

et al. 2021

Cancers

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“…Most studies focused on prognostic biomarkers rather than predictive indicators detected before treatment or at the initiation of NAC [ 15 , 16 , 17 ]. Clinical predictive biomarkers of pCR in TNBC have been reported, but a consensus is not yet well established [ 18 , 19 , 20 ]. The prediction of pCR or residual disease has important clinical implications for patients receiving NAC.…”

Section: Introductionmentioning

confidence: 99%

An Integrative Clinical Model for the Prediction of Pathological Complete Response in Patients with Operable Stage II and Stage III Triple-Negative Breast Cancer Receiving Neoadjuvant Chemotherapy

Chung

Chen

et al. 2022

Cancers

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Triple-negative breast cancer (TNBC) is treated with neoadjuvant chemotherapy (NAC). The response to NAC, particularly the probability of a complete pathological response (pCR), guides the surgical approach and adjuvant therapy. We developed a prediction model using a nomogram integrating blood tests and pre-treatment ultrasound findings for predicting pCR in patients with stage II or III operable TNBC receiving NAC. Clinical data before and after the first cycle of NAC collected from patients between 2012 and 2019 were analyzed using univariate and multivariate analyses to identify correlations with pCR. The coefficients of the significant parameters were calculated using logistic regression, and a nomogram was developed based on the logistic model to predict the probability of pCR. Eighty-eight patients were included. Five parameters correlated with the probability of pCR, including the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte (PLR) ratio, percentage change in PLR, presence of echogenic halo, and tumor height-to-width ratio. The discrimination performance of the nomogram was indicated by an area under the curve of 87.7%, and internal validation showed that the chi-square value of the Hosmer–Lemeshow test was 7.67 (p = 0.363). Thus, the integrative prediction model using clinical data can predict the probability of pCR in patients with TNBC receiving NAC.

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“…T1-weighted, T2-weighted, and fat-suppressed (FS) images are some of the MRI sequences that are useful for detecting and estimating bleeding, fat, edema, and cyst. [9][10][11][12][13][14] However, because of limitations in total scan time for patients, some of these sequences may be omitted. In conventional MRI, the imaging parameters such as RT, TE, and inversion time (TI) are predetermined before the examination is conducted.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Image Quality and Utility of Synthetic MRI in the Breast

et al. 2021

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Purpose: Synthetic MRI reconstructs multiple sequences in a single acquisition. In the present study, we aimed to compare the image quality and utility of synthetic MRI with that of conventional MRI in the breast. Methods:We retrospectively collected the imaging data of 37 women (mean age: 55.1 years; range: 20-78 years) who had undergone both synthetic and conventional MRI of T2-weighted, T1-weighted, and fatsuppressed (FS)-T2-weighted images. Two independent breast radiologists evaluated the overall image quality, anatomical sharpness, contrast between tissues, image homogeneity, and presence of artifacts of synthetic and conventional MRI on a 5-point scale (5 = very good to 1 = very poor). The interobserver agreement between the radiologists was evaluated using weighted kappa.Results: For synthetic MRI, the acquisition time was 3 min 28 s. On the 5-point scale evaluation of overall image quality, although the scores of synthetic FS-T2-weighted images (4.01 ± 0.56) were lower than that of conventional images (4.95 ± 0.23; P < 0.001), the scores of synthetic T1-and T2-weighted images (4.95 ± 0.23 and 4.97 ± 0.16) were comparable with those of conventional images (4.92 ± 0.27 and 4.97 ± 0.16; P = 0.484 and 1.000, respectively). The kappa coefficient of conventional MRI was fair (0.53; P < 0.001), and that of conventional MRI was fair (0.46; P < 0.001). Conclusion:The image quality of synthetic T1-and T2-weighted images was similar to that of conventional images and diagnostically acceptable, whereas the quality of synthetic T2-weighted FS images was inferior to conventional images. Although synthetic MRI images of the breast have the potential to provide efficient image diagnosis, further validation and improvement are required for clinical application.

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Is the presence of edema and necrosis on T2WI pretreatment breast MRI the key to predict pCR of triple negative breast cancer?

Cited by 28 publications

References 41 publications

The Impact of Tumor Edema on T2-Weighted 3T-MRI Invasive Breast Cancer Histological Characterization: A Pilot Radiomics Study

The Impact of Tumor Edema on T2-Weighted 3T-MRI Invasive Breast Cancer Histological Characterization: A Pilot Radiomics Study

An Integrative Clinical Model for the Prediction of Pathological Complete Response in Patients with Operable Stage II and Stage III Triple-Negative Breast Cancer Receiving Neoadjuvant Chemotherapy

Investigating the Image Quality and Utility of Synthetic MRI in the Breast

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