Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS: In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA). RESULTS: The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models. CONCLUSION: The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Contrast-Enhanced Spectral Mammography-Based Prediction of Non-Sentinel Lymph Node Metastasis and Axillary Tumor Burden in Patients With Breast Cancer.

Purpose: To establish and evaluate non-invasive models for estimating the risk of non-sentinel lymph node (NSLN) metastasis and axillary tumor burden among breast cancer patients with 1-2 positive sentinel lymph nodes (SLNs). Materials and Methods: Breast cancer patients with 1-2 positive SLNs who underwent axillary lymph node dissection (ALND) and contrast-enhanced spectral mammography (CESM) examination were enrolled between 2018 and 2021. CESM-based radiomics and deep learning features of tumors were extracted. The correlation analysis, least absolute shrinkage and selection operator (LASSO), and analysis of variance (ANOVA) were used for further feature selection. Models based on the selected features and clinical risk factors were constructed with multivariate logistic regression. Finally, two radiomics nomograms were proposed for predicting NSLN metastasis and the probability of high axillary tumor burden. Results: A total of 182 patients [53.13 years ± 10.03 (standard deviation)] were included. For predicting the NSLN metastasis status, the radiomics nomogram built by 5 selected radiomics features and 3 clinical risk factors including the number of positive SLNs, ratio of positive SLNs, and lymphovascular invasion (LVI), achieved the area under the receiver operating characteristic curve (AUC) of 0.85 [95% confidence interval (CI): 0.71-0.99] in the testing set and 0.82 (95% CI: 0.67-0.97) in the temporal validation cohort. For predicting the high axillary tumor burden, the AUC values of the developed radiomics nomogram are 0.82 (95% CI: 0.66-0.97) in the testing set and 0.77 (95% CI: 0.62-0.93) in the temporal validation cohort. Discussion: CESM images contain useful information for predicting NSLN metastasis and axillary tumor burden of breast cancer patients. Radiomics can inspire the potential of CESM images to identify lymph node metastasis and improve predictive performance.

Quantitative analysis of contrast enhanced spectral mammography grey value for early prediction of pathological response of breast cancer to neoadjuvant chemotherapy.

A quantitative analysis of contrast-enhanced spectral mammography (CESM) enhancement was conducted for the early prediction of the pathological response after neoadjuvant chemotherapy (NAC). Retrospective analysis of the data of 111 patients was conducted, and all of them underwent NAC in our hospital and surgical resection after the end of all cycles from January 2018 to May 2019. They were divided into pathological complete response (PCR) and non-PCR groups. We determined whether a statistical difference in the percentage of CESM grey value reduction (ΔCGV) was present in the PCR and non-PCR groups and whether a statistical difference was observed in the diagnostic efficiency of craniocaudal (CC) and mediolateral oblique (MLO) view subtraction images. Independent sample t-test was used to compare different groups, the receiver operating characteristic (ROC) curve was used to compare the diagnostic efficacy of CC and MLO for pathological response after NAC, and the Delong test was used to compare the area under the ROC curve (AUC). Statistical significance was considered at P < 0.05. A statistical difference was observed in the ΔCGV in the PCR and non-PCR groups. No statistical difference was observed in the AUCs of CC and MLO view subtraction images. The ΔCGV can be used as a quantitative index to predict PCR early, and no statistical difference was observed in the diagnostic efficacy of CC and MLO view subtraction images.

Background parenchymal enhancement on contrast-enhanced spectral mammography does not represent an influencing factor for breast cancer: A preliminary study.

ABSTRACT: To compare the relationship between background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM), mammographic breast density (MBD), age, in the group with benign vs malignant breast lesions.Four hundred thirty three non-high-risk patients from January 2018 to May 2019 were retrospectively analyzed. Patients were assigned into 4 groups: premenopausal benign lesions, premenopausal malignant lesions, postmenopausal benign lesions, and postmenopausal malignant lesions. The differences in CESM BPE and MBD between premenopausal benign lesions and premenopausal malignant lesions, between postmenopausal benign lesions and postmenopausal malignant lesions, between premenopausal and postmenopausal benign lesions, and between premenopausal and postmenopausal malignant lesions were evaluated. Pearson Chi-Squared test was used to analyze the differences between the above groups. Spearman rank correlation analysis was used to evaluate the correlations between BPE, MBD, and age. Multiple logistic regression was used to analyze the influencing factors of breast cancer. P < .05 was considered statistically significant.There was no significant difference in CESM BPE or MBD of benign and malignant lesions regardless of premenopausal or postmenopausal status, but there was a significant difference in CESM BPE and MBD of premenopausal and postmenopausal patients regardless of the presence of benign or malignant lesions. The intensity of CESM BPE was positively correlated with MBD, and the intensity of CESM BPE and MBD were negatively correlated with age. Multiple logistic regression analysis showed that age was an influencing factor for breast cancer in both premenopausal and postmenopausal patients.For non-high-risk women, CESM BPE and MBD were not correlated with benign or malignant breast lesions, and age was an influencing factor for breast cancer.

Diagnostic value of the enhancement intensity and enhancement pattern of CESM to benign and malignant breast lesions.

This study aimed to improve the diagnostic accuracy of breast diseases by combining breast imaging-reporting and data system (BI-RADS) with the enhancement intensity and pattern of contrast-enhanced spectral mammography (CESM) (this combination of BI-RADS and CESM was designated as BaC).BI-RADS was used to evaluate low-energy CESM images. Spearman nonparametric correlation analysis was performed to analyze the correlation between the enhancement intensity of CESM subtraction images and the pathological results. Odds ratio (OR) values were calculated to determine whether the enhancement pattern of CESM subtraction images is a risk factor for benign and malignant lesions. The diagnostic efficacies of BI-RADS, CESM, and BaC scores for benign and malignant breast diseases were analyzed using the receiver operating characteristic (ROC) curve.Lesions with a high enhancement intensity were more likely to be malignant than those with low enhancement intensity. Lesions with heterogeneous enhancement tended to be malignant, whereas those with homogeneous enhancement tended to be benign. No significant correlation was observed between ring enhancement and the benignity or malignancy of lesions. The area under the ROC curve of BaC was higher than that of BI-RADS or CESM, and the difference was statistically significant.The diagnostic efficacy of BI-RADS combined with CESM enhancement was superior to that of either method alone.

Diagnostic Value of Quantitative Gray-Scale Analysis of Contrast-Enhanced Spectral Mammography for Benign and Malignant Breast Lesions.

OBJECTIVE: The aim of the study was to quantitatively analyze the enhancement of breast lesions by contrast-enhanced spectral mammography to improve the differential diagnosis ability of contrast-enhanced spectral mammography. METHODS: A total of 283 patients with breast lesions admitted from August 2017 to May 2018 were retrospectively analyzed. Quantitative analysis of all enhancing lesions was performed to measure the gray values of the lesion region of interest (ROI), the area close to the lesion (ROI1), the area close to the chest wall (ROI2), and the chest wall (ROI3). Differences in gray values between different ROIs of benign and malignant lesions were compared. Taking the pathological results as the criterion standard, we used the receiver operating characteristic curve to evaluate the diagnostic efficacy of the ROI gray value and relative gray value (rROI) for the lesions. RESULTS: A total of 299 lesions were found in 283 patients, including 101 benign lesions and 198 malignant lesions. The ROI gray value, rROI1, rROI2, and rROI3 of malignant lesions were all significantly greater than those of benign lesions. The areas under the ROC curve of ROI, rROI1, rROI2, and rROI3 gray values of benign and malignant lesions were 0.795, 0.833, 0.812, and 0.741, respectively. The statistically significant difference in the area under the ROC curve was only found between rROI1 and ROI gray value and rROI1 had the greatest diagnostic value. CONCLUSIONS: The gray value of malignant breast lesions was higher than that of benign lesions. The quantitative analysis of the gray value will help in the differential diagnosis of benign and malignant breast lesions.

Diagnostic Value of Contrast-Enhanced Spectral Mammography in Comparison to Magnetic Resonance Imaging in Breast Lesions.

OBJECTIVE: The aim of this study was to evaluate the diagnostic value between contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) in breast disease. METHODS: Two hundred thirty-five patients who were suspected of having breast abnormalities by clinical examination or mammography underwent CESM and MRI examination. Using histopathologic results as the criterion standard, the diagnostic performance of CESM and MRI was investigated. The areas under receiver operating characteristic curves were applied to analyze diagnostic efficiency. The Pearson correlation coefficients between CESM versus pathology and MRI versus pathology were calculated. RESULTS: Two hundred sixty-three breast lesions were found in 235 patients, in which 177 were malignant and 86 were benign. By evaluating the diagnostic value, sensitivity, positive predictive value, negative predictive value, and false-negative rate from CESM examination were comparable to those from MRI (91.5%, 94.7%, 83.7%, and 8.5% vs 91.5%, 90.5%, 82.1%, and 8.5%). Importantly, the accuracy and the specificity were higher for CESM than those for MRI (81% and 89.5% vs 80.2% and 71.7%), whereas the false-positive rate was lower (10.5% vs 19.8%). The areas under receiver operating characteristic curves of CESM and MRI were 0.950 and 0.939, displaying the equivalent diagnostic efficiency (P = 0.48).For the agreement between measurements, mean tumor sizes were 3.1 cm for CESM and 3.4 cm for MRI compared with 3.2 cm on histopathologic results. The Pearson correlation coefficient of CESM versus histopathology (r = 0.774, P = 0.000) was consistent with MRI versus histopathology (r = 0.771, P = 0.000). CONCLUSIONS: Our results show better accuracy, specificity, and false-positive rate of CESM in breast cancer detection than MRI. Contrast-enhanced spectral mammography displayed a good correlation with histopathology in assessing the lesion size of breast cancer, which is consistent with MRI.

Imaging performance and clinical value of contrast-enhanced ultrasonography and computed tomography in the diagnosis of liver cancer.

The imaging performance and clinical value of contrast-enhanced ultrasonography (CEUS) combined with CT in diagnosis of liver cancer were investigated. A total of 426 liver cancer patients treated in Yuhuangding Hospital (Yantai, China) from February 2011 to May 2016 were selected. Among them, 222 patients underwent CEUS examination, 204 patients underwent CT examination, and 102 patients underwent CEUS combined with CT examination. Sensitivity and specificity of the three methods were examined. CT showed a low density in 92.6% of patients (189 patients) and a high-low hybrid density in 6.4% (13 patients), with calcification seen in 2.5% of patients (5 patients) and bleeding in 3.4% (7 patients). Lesions: 76.5% (156 cases) of patients with multiple type, 23.5% (48 cases) with single type. CEUS showed overall enhancement in 53.2% patients (118 cases), heterogenous enhancement in 16.7% (37 cases), peripheral enhancement in 18.9% of patients (42 cases), necrosis of liquefaction in 11.3% (25 cases). In 65.3% (145 cases) of patients, the portal venous phase and the delayed phase showed a low enhancement, while 34.7% (77 cases) showed no enhancement. The sensitivity and specificity rates of CEUS combined with CT detection of liver cancer were 87.8, 88.2 and 94.1%, respectively. The ROC curve analysis showed that the sensitivity and specificity of CEUS in the diagnosis of liver cancer were 76.8 and 78.9%, respectively. The sensitivity and specificity of CT were 81.2 and 85.5%, respectively. The sensitivity and specificity of CEUS combined with CT were 90.4 and 92.7%, respectively. CEUS combined with CT detection can make-up for the deficiencies of each other and effectively improve the coincidence rate of liver cancer diagnosis, which can be used as an effective examination method for the diagnosis of liver cancer.

Modified Glasgow Prognostic Score at Recurrence Predicts Poor Survival in Resected Non-Small Cell Lung Cancer (NSCLC) Patients.

BACKGROUND The purpose of this study was to investigate the impact of the modified Glasgow Prognostic Score (GPS) at the time of recurrence on post-recurrence survival (PRS) in non-small cell lung cancer (NSCLC) patients after surgical resection. MATERIAL AND METHODS The clinicopathologic characteristics and outcome data of 266 patients with recurrent NSCLC were collected and reviewed retrospectively. The prognostic impact of mGPS at recurrence in patients with recurrent NSCLC was investigated in univariate and multivariate analyses. RESULTS A total of 266 patients were analyzed. The mGPS at the time of recurrence of 0, 1, and 2 was assigned to 60.9%, 33.1%, and 6.0% of total patients, respectively. In univariate analyses, the median post-recurrence survival times for those with mGPS 0, 1, and 2 were 19, 14, and 4 months, respectively (log-rank test; P=0.005). No statistically significant difference in post-recurrence survival was observed among the patients with different mGPS before surgery (log-rank test; P=0.064). Age at surgery, histological type, C-reactive protein (CRP), albumin, and mGPS at recurrence significantly predicted PRS. After adjusting for confounding variables in the model, age (hazard ratio 1.59, P=0.003) as well as disease-free interval (DFI) (hazard ratio 1.40, P=0.023), and mGPS at recurrence (hazard ratio 1.47, P=0.002) remained independent predictors of PRS. CONCLUSIONS mGPS at the time of recurrence might be an independent adverse prognostic factor in recurrent NSCLC.

Long non-coding RNA HOTAIR regulates proliferation and invasion via activating Notch signalling pathway in retinoblastoma.

Retinoblastoma is the most frequently occurring tumour in the eyes in early childhood. Novel targets that are important for the diagnosis or treatment of retinoblastoma could be valuable in increasing the survival rate of patients affected by this disease. Long non-coding RNAs (lncRNAs) are a recently discovered type of RNAs with no proteincoding function; yet it has become increasingly clear that lncRNAs are responsible for important gene regulatory functions in various diseases. In this study, the expression of lncRNA HOTAIR was measured by qRT-PCR, and HOTAIR expression was found to be significantly upregulated in human retinoblastomas tissues as compared with that in paracancerous tissues. Knockdown of HOTAIR restricted the proliferation and invasion of the more invasive retinoblastoma Y79 cells, and led to G0/G1 arrest, possibly through inhibiting phospho-RB1, RB1 and CCNE. Furthermore, we found that the Notch signalling pathway was activated abnormally in retinoblastoma cell lines, while knockdown of HOTAIR attenuated the endogenous Notch signalling pathway in vitro and in vivo. In addition, knockdown of HOTAIR could inhibit the tumour progression in a xenograft model of retinoblastoma. In summary, our findings indicate that HOTAIR may play important roles in retinoblastoma progression via Notch pathway. HOTAIR has the potential to enhance the development of novel targeted diagnostic and therapeutic approaches for retinoblastoma.

Upregulation of lncRNA HOTAIR contributes to IL-1ß-induced MMP overexpression and chondrocytes apoptosis in temporomandibular joint osteoarthritis.

Temporomandibular joint osteoarthritis (TMJ OA) is a common and heterogeneous disease that causes painful and progressive joint degeneration, which restricts daily activities, including talking and chewing. Long noncoding RNAs (lncRNAs) are an important class of genes involved in various physiological and pathological functions, including osteoarthritis (OA).The present study aimed to identify the lncRNAs that are important in TMJ OA and their potential functions. Here, we found that HOTAIR was significantly upregulated in the synovial fluid of TMJ OA patients compared with that of normal controls. Increased HOTAIR was similarly observed in the synovial fluid of TMJ OA rabbits as compared to control rabbits. Furthermore, in interleukin-1ß (IL-1ß)-induced TMJ OA in vitro model (primary rabbit condylar chondrocytes), the expressions of matrix metalloproteinase (MMP)-1, MMP3, MMP9 and HOTAIR were all dramatically increased. Most importantly, knockdown of HOTAIR in IL-1ß-induced TMJ OA in vitro model could not only reverse the IL-1ß-stimulated expressions of MMP1, MMP3 and MMP9, but also significantly decrease the apoptosis rate induced by IL-1ß in primary rabbit condylar chondrocytes. Our data provides new insight into the mechanisms of chondrocytes destruction in TMJ OA.

Imaging study on the optic canal using sixty four-slice spiral computed tomography.

BACKGROUND: Rapid advances in multislice computed tomography (MSCT) technology facilitate accurate clinical imaging. The newly developed 64-slice CT increases temporal and spatial resolution efficiently. PURPOSE: The purpose of this study is to evaluate the application of 64 slice spiral computed tomography (CT) on the imaging of the normal optics canal. METHODS AND MATERIALS: 100 healthy adults were investigated using 64 slice spiral CT. The optics canal was scanned, reconstructed and examined. RESULTS: Among the four walls of the optic canal, the medial wall is the longest one. The upper wall and outer wall are inferior to the medial wall while the inferior wall is the shortest one. All the data accomplished by the 64 slice CT was consistent with the results of previous reports using other methods. CONCLUSION: The results suggested that the 64 slice spiral CT could be a valuable and accurate method for measuring the length of optics canal walls.