Computer-Aided Diagnosis Evaluation of the Correlation Between Magnetic Resonance Imaging With Molecular Subtypes in Breast Cancer

BackgroundThere is a demand for additional alternative methods that can allow the differentiation of the breast tumor into molecular subtypes precisely and conveniently.PurposeThe present study aimed to determine suitable optimal classifiers and investigate the general applicability of computer-aided diagnosis (CAD) to associate between the breast cancer molecular subtype and the extracted MR imaging features.MethodsWe analyzed a total of 264 patients (mean age: 47.9 ± 9.7 years; range: 19–81 years) with 264 masses (mean size: 28.6 ± 15.86 mm; range: 5–91 mm) using a Unet model and Gradient Tree Boosting for segmentation and classification.ResultsThe tumors were segmented clearly by the Unet model automatically. All the extracted features which including the shape features,the texture features of the tumors and the clinical features were input into the classifiers for classification, and the results showed that the GTB classifier is superior to other classifiers, which achieved F1-Score 0.72, AUC 0.81 and score 0.71. Analyzed the different features combinations, we founded that the texture features associated with the clinical features are the optimal features to different the breast cancer subtypes.ConclusionCAD is feasible to differentiate the breast cancer subtypes, automatical segmentation were feasible by Unet model and the extracted texture features from breast MR imaging with the clinical features can be used to help differentiating the molecular subtype. Moreover, in the clinical features, BPE and age characteristics have the best potential for subtype

Kaplan–Meier analysis of disease-free survival time in the luminal B patients.

<p>Kaplan–Meier analysis of disease-free survival time in the luminal B patients.</p

Kaplan–Meier analysis of disease-free survival time in the enrolled patients.

<p>Kaplan–Meier analysis of disease-free survival time in the enrolled patients.</p

HER2 protein expression detected by IHC.

<p>(×400) A: Negative (score 0). B: Negative (score 1+). C: Equivocal (score 2+). D: Positive (score 3+).</p

HER2 gene status identified by FISH.

<p>Red signals represent HER2 gene, green signals represent CEP17 (×600). A: HER2 gene negative case; B: HER2 gene positive case, HER2/CEP17 ratio of higher than 2.0; C: HER2 gene positive case, HER2 signals are clustered; D: HER2 gene with CEP17 gain, average CEP17 copy number ≥3.76 to 6.</p

Classification of evaluation of HER2 protein expression by IHC of the invasive component of a breast cancer specimen.

<p>Classification of evaluation of HER2 protein expression by IHC of the invasive component of a breast cancer specimen.</p

Clinicopathologic characteristics of 251 patients with papillary thyroid carcinomas.

<p>Clinicopathologic characteristics of 251 patients with papillary thyroid carcinomas.</p

Clinicopathological Features and Prognosis of Papillary Thyroid Microcarcinoma for Surgery and Relationships with the BRAF^V600E Mutational Status and Expression of Angiogenic Factors

<div><p>Objective</p><p>To investigate the clinicopathological characteristics of papillary thyroid microcarcinoma (PTMC) for surgery by comparing the difference between PTMC and larger papillary thyroid carcinoma (LPTC).</p><p>Methods</p><p>We analyzed the differences in the clinicopathological characteristics, prognosis, B-type RAF kinase (BRAF)^V600E mutational status and expression of angiogenic factors, including pigment epithelium-derived factor (PEDF), Vascular Endothelial Growth Factor (VEGF), and hypoxia-inducible factor alpha subunit (HIF-1α), between PTMC and LPTC by retrospectively reviewing the records of 251 patients with papillary thyroid carcinoma, 169 with PTMC, and 82 with LPTC (diameter >1 cm).</p><p>Results</p><p>There were no significant differences in the gender, age, multifocality, Hashimoto’s thyroiditis, TNM stage, PEDF protein expression, rate of recurrence, or mean follow-up duration between patients with PTMC or LPTC. The prevalence of extrathyroidal invasion (EI), lymph node metastasis (LNM), and BRAF mutation in patients with PTMC was significantly lower than in patients with LPTC. In addition, in PTMC patients with EI and/or LNM and/or positive BRAF (high-risk PTMC patients), the prevalence of extrathyroidal invasion, Hashimoto's disease, lymph node metastasis, tumor TNM stage, PEDF positive protein expression, the rate of recurrent disease, and the mRNA expression of anti-angiogenic factors was almost as high as in patients with larger PTC, but with no significant difference.</p><p>Conclusions</p><p>Extrathyroid invasion, lymph node metastases, and BRAF^V600E mutation were the high risk factors of PTMC. PTMC should be considered for the same treatment strategy as LPTC when any of these factors is found. Particularly, PTMC with BRAF^V600E gene mutations needed earlier surgical treatment. In addition, the high cell subtype of PTMC with BRAF^V600E gene mutation is recommended for total thyroidectomy in primary surgery to reduce the risk of recurrence.</p></div

Clinicopathological characteristics in papillary thyroid carcinomas according to tumor size.

<p>Clinicopathological characteristics in papillary thyroid carcinomas according to tumor size.</p

mRNA expression levels of PEDF, VEGF and HIF1α in PTMC and LPTC with EI and/or LNM and/or positive BRAF mutation in each group.

<p>EI, extrathyroidal invasion; LNM, lymph-node metastasis.</p