Fibrosarcomatous Transformation in Dermatofibrosarcoma Protuberans of the Male Breast and its Association with Magnetic Resonance Imaging and Immunohistopathologic Features.

BACKGROUND: Dermatofibrosarcoma Protuberans (DFSP) is a rare soft tissue sarcoma, accounting for approximately 1% of all tumors; however, DFSP of the breast is extremely rare. Moreover, DFSP generally has a low malignant potential and is characterized by a high rate of local recurrence along with a small but definite risk of metastasis. The risk of metastasis is higher in fibrosarcomatous transformation in DFSP than in ordinary DFSP. CASE REPORT: We have, herein, reported a case of a 61-year-old male patient with fibrosarcomatous transformation in DFSP. Preoperative Dynamic Contrastenhanced Magnetic Resonance Imaging (DCE-MRI) of the breast revealed an oval-shaped mass with heterogeneous internal enhancement, a large vessel embedded within, and a washout curve pattern on kinetic curve analysis. The mass exhibited a hyperintense signal on Diffusion-weighted Imaging (DWI), with a low apparent diffusion coefficient value. Histologically, the bland spindle tumor cells were arranged in a storiform pattern. Areas with the highest histological grade demonstrated increased cellularity, cytological atypia, and mitotic activity. Immunohistochemically, Ki-67 and p53 were highly expressed. CONCLUSION: Recognizing the risk and accurately diagnosing fibrosarcomatous transformation in male breast DFSP are critical for improving prognosis and establishing appropriate treatment and follow-up plans. This emphasizes the significance of combining immunohistopathological features with DCE-MRI and DWI to assist clinicians in the early and accurate diagnosis of sarcomas arising from male breast DFSP.

Comparison of Diagnostic Performance between Classic and Modified Abbreviated Breast MRI and the MRI Features Affecting Their Diagnostic Performance.

Abbreviated breast magnetic resonance imaging (AB-MRI) has emerged as a supplementary screening tool, though protocols have not been standardized. The purpose of this study was to compare the diagnostic performance of modified and classic AB-MRI and determine MRI features affecting their diagnostic performance. Classic AB-MRI included one pre- and two post-contrast T1-weighted imaging (T1WI) scans, while modified AB-MRI included a delayed post-contrast axial T1WI scan and an axial T2-weighted interpolated scan obtained between the second and third post-contrast T1WI scans. Four radiologists (two specialists and two non-specialists) independently categorized the lesions. The MRI features investigated were lesion size, lesion type, and background parenchymal enhancement (BPE). The Wilcoxon rank-sum test, Fisher's exact test, and bootstrap-based test were used for statistical analysis. The average area under the curve (AUC) for modified AB-MRI was significantly greater than that for classic AB-MRI (0.76 vs. 0.70, p = 0.010) in all reader evaluations, with a similar trend in specialist evaluations (0.83 vs. 0.76, p = 0.004). Modified AB-MRI demonstrated increased AUCs and better diagnostic performance than classic AB-MRI, especially for lesion size > 10 mm (p = 0.018) and mass lesion type (p = 0.014) in specialist evaluations and lesion size > 10 mm (p = 0.003) and mild (p = 0.026) or moderate BPE (p = 0.010) in non-specialist evaluations.

3D Superclusters with Hybrid Bioinks for Early Detection in Breast Cancer.

The surface-enhanced Raman scattering (SERS) technique has garnered significant interest due to its ultrahigh sensitivity, making it suitable for addressing the growing demand for disease diagnosis. In addition to its sensitivity and uniformity, an ideal SERS platform should possess characteristics such as simplicity in manufacturing and low analyte consumption, enabling practical applications in complex diagnoses including cancer. Furthermore, the integration of machine learning algorithms with SERS can enhance the practical usability of sensing devices by effectively classifying the subtle vibrational fingerprints produced by molecules such as those found in human blood. In this study, we demonstrate an approach for early detection of breast cancer using a bottom-up strategy to construct a flexible and simple three-dimensional (3D) plasmonic cluster SERS platform integrated with a deep learning algorithm. With these advantages of the 3D plasmonic cluster, we demonstrate that the 3D plasmonic cluster (3D-PC) exhibits a significantly enhanced Raman intensity through detection limit down to 10-6 M (femtomole-(10-17 mol)) for p-nitrophenol (PNP) molecules. Afterward, the plasma of cancer subjects and healthy subjects was used to fabricate the bioink to build 3D-PC structures. The collected SERS successfully classified into two clusters of cancer subjects and healthy subjects with high accuracy of up to 93%. These results highlight the potential of the 3D plasmonic cluster SERS platform for early breast cancer detection and open promising avenues for future research in this field.

Quantitative CT Analysis Based on Smoking Habits and Chronic Obstructive Pulmonary Disease in Patients with Normal Chest CT.

Purpose: To assess normal CT scans with quantitative CT (QCT) analysis based on smoking habits and chronic obstructive pulmonary disease (COPD). Materials and Methods: From January 2013 to December 2014, 90 male patients with normal chest CT and quantification analysis results were enrolled in our study [non-COPD never-smokers (n = 38) and smokers (n = 45), COPD smokers (n = 7)]. In addition, an age-matched cohort study was performed for seven smokers with COPD. The square root of the wall area of a hypothetical bronchus of internal perimeter 10 mm (Pi10), skewness, kurtosis, mean lung attenuation (MLA), and percentage of low attenuation area (%LAA) were evaluated. Results: Among patients without COPD, the Pi10 of smokers (4.176 ± 0.282) was about 0.1 mm thicker than that of never-smokers (4.070 ± 0.191, p = 0.047), and skewness and kurtosis of smokers (2.628 ± 0.484 and 6.448 ± 3.427) were lower than never-smokers (2.884 ± 0.624, p = 0.038 and 8.594 ± 4.944, p = 0.02). The Pi10 of COPD smokers (4.429 ± 0.435, n = 7) was about 0.4 mm thicker than never-smokers without COPD (3.996 ± 0.115, n = 14, p = 0.005). There were no significant differences in MLA and %LAA between groups (p > 0.05). Conclusion: Even on normal CT scans, QCT showed that the airway walls of smokers are thicker than never-smokers regardless of COPD and it preceded lung parenchymal changes.

Diagnostic Accuracy of Magnetic Resonance Imaging Features and Tumor-to-Nipple Distance for the Nipple-Areolar Complex Involvement of Breast Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: This systematic review and meta-analysis evaluated the accuracy of preoperative breast magnetic resonance imaging (MRI) features and tumor-to-nipple distance (TND) for diagnosing occult nipple-areolar complex (NAC) involvement in breast cancer. MATERIALS AND METHODS: The MEDLINE, Embase, and Cochrane databases were searched for articles published until March 20, 2022, excluding studies of patients with clinically evident NAC involvement or those treated with neoadjuvant chemotherapy. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Two reviewers independently evaluated studies that reported the diagnostic performance of MRI imaging features such as continuity to the NAC, unilateral NAC enhancement, non-mass enhancement (NME) type, mass size (> 20 mm), and TND. Summary estimates of the sensitivity and specificity curves and the summary receiver operating characteristic (SROC) curve of the MRI features for NAC involvement were calculated using random-effects models. We also calculated the TND cutoffs required to achieve predetermined specificity values. RESULTS: Fifteen studies (n = 4002 breast lesions) were analyzed. The pooled sensitivity and specificity (with 95% confidence intervals) for NAC involvement diagnosis were 71% (58-81) and 94% (91-96), respectively, for continuity to the NAC; 58% (45-70) and 97% (95-99), respectively, for unilateral NAC enhancement; 55% (46-64) and 83% (75-88), respectively, for NME type; and 88% (68-96) and 58% (40-75), respectively, for mass size (> 20 mm). TND had an area under the SROC curve of 0.799 for NAC involvement. A TND of 11.5 mm achieved a predetermined specificity of 85% with a sensitivity of 64%, and a TND of 12.3 mm yielded a predetermined specificity of 83% with a sensitivity of 65%. CONCLUSION: Continuity to the NAC and unilateral NAC enhancement may help predict occult NAC involvement in breast cancer. To achieve the desired diagnostic performance with TND, a suitable cutoff value should be considered.

MRI Features of Primary Breast Lymphoma in Patient with Breast Carcinoma for Differential Diagnosis.

Teaching point: Homogeneous internal enhancement and washout pattern on DCE-MRI and a low ADC value on DWI in women with breast carcinoma help distinguish primary breast lymphoma from bilateral synchronous breast carcinoma.

Analysis of background echotexture on automated breast ultrasound using BI-RADS and modified classification: Association with clinical features and mammographic density.

PURPOSE: To analyze BE on ABUS using BI-RADS and a modified classification in association with mammographic density and clinical features. METHODS: Menopausal status, parity, and family history of breast cancer were collected for 496 women who underwent ABUS and mammography. Three radiologists independently reviewed all ABUS BE and mammographic density. Statistical analyses including kappa statistics (κ) for interobserver agreement, Fisher's exact test, and univariate and multivariate multinomial logistic regression were performed. RESULTS: BE distribution between the two classifications and between each classification and mammographic density were associated (P < 0.001). BI-RADS homogeneous-fibroglandular (76.8%) and modified heterogeneous BE (71.3%, 75.7%, and 87.5% of mild, moderate, and marked heterogeneous background echotexture, respectively) tended to be dense. BE was correlated between BI-RADS homogeneous-fat and modified homogeneous background (95.1%) and between BI-RADS homogeneous-fibroglandular or heterogeneous (90.6%) and modified heterogeneous (86.9%) (P < 0.001). In multinomial logistic regression, age < 50 years was independently associated with heterogeneous BE (OR, 8.89, P = 0.003, in BI-RADS; OR, 3.74; P = 0.020 in modified classification). CONCLUSION: BI-RADS homogeneous-fat and modified homogeneous BE on ABUS was likely to be mammographically fatty. However, BI-RADS homogeneous-fibroglandular or heterogeneous BE might be classified as any modified BE. Younger age was independently associated with heterogeneous BE.

Radiological and Histological Clues in the Diagnosis of Solitary and Synchronous Breast Metastasis From Small Cell Lung Carcinoma.

Breast metastases from small cell lung carcinoma (SCLC) are extremely rare. Although reports of breast metastases from SCLC exist, only three studies have reported solitary and synchronous breast metastases. Herein, we present a case of SCLC with solitary and synchronous breast metastases. This unusual case highlights the importance of the combined use of radiological and immunohistochemical features to accurately distinguish solitary metastatic SCLC from primary breast carcinoma or metastatic carcinoma of other types of lung cancer. It also emphasizes the importance of the differences between solitary metastatic SCLC and primary breast carcinoma or metastatic carcinoma of other types of lung cancer for the respective prognoses and development of appropriate therapeutic plans.

Multiarray Biosensor for Diagnosing Lung Cancer Based on Gap Plasmonic Color Films.

Adaptable and sensitive materials are essential for the development of advanced sensor systems such as bio and chemical sensors. Biomaterials can be used to develop multifunctional biosensor applications using genetic engineering. In particular, a plasmonic sensor system using a coupled film nanostructure with tunable gap sizes is a potential candidate in optical sensors because of its simple fabrication, stability, extensive tuning range, and sensitivity to small changes. Although this system has shown a good ability to eliminate humidity as an interferant, its performance in real-world environments is limited by low selectivity. To overcome these issues, we demonstrated the rapid response of gap plasmonic color sensors by utilizing metal nanostructures combined with genetically engineered M13 bacteriophages to detect volatile organic compounds (VOCs) and diagnose lung cancer from breath samples. The M13 bacteriophage was chosen as a recognition element because the structural protein capsid can readily be modified to target the desired analyte. Consequently, the VOCs from various functional groups were distinguished by using a multiarray biosensor based on a gap plasmonic color film observed by hierarchical cluster analysis. Furthermore, the lung cancer breath samples collected from 70 healthy participants and 50 lung cancer patients were successfully classified with a high rate of over 89% through supporting machine learning analysis.

Basal Ganglia Iron Content Increases with Glioma Severity Using Quantitative Susceptibility Mapping: A Potential Biomarker of Tumor Severity.

BACKGROUND AND PURPOSE: Gliomas have been found to alter iron metabolism and transport in ways that result in an expansion of their intracellular iron compartments to support aggressive tumor growth. This study used deep neural network trained quantitative susceptibility mapping to assess basal ganglia iron concentrations in glioma patients. MATERIALS AND METHODS: Ninety-two patients with brain lesions were initially enrolled in this study and fifty-nine met the inclusion criteria. Susceptibility-weighted images were collected at 3.0 T and used to construct quantitative susceptibility maps via a deep neural network-based method. The regions of interest were manually drawn within basal ganglia structures and the mean voxel intensities were extracted and averaged across multiple slices. One-way ANCOVA tests were conducted to compare the susceptibility values of groups of patients based on tumor grade while controlling for age, sex, and tumor type. RESULTS: The mean basal ganglia susceptibility for patients with grade IV tumors was higher than that for patients with grade II tumors (p = 0.00153) and was also higher for patients with grade III tumors compared to patients with grade II tumors (p = 0.020), after controlling for age, sex, and tumor type. Patient age influenced susceptibility values (p = 0.00356), while sex (p = 0.69) and tumor type (p = 0.11) did not. CONCLUSIONS: The basal ganglia iron content increased with glioma severity. Basal ganglia iron levels may thus be a useful biomarker in glioma prognosis and treatment, especially with regard to iron-based cancer therapies.

Ferric Ammonium Citrate Upregulates PD-L1 Expression through Generation of Reactive Oxygen Species.

Iron plays an important role in macrophage polarization by altering metabolic and redox status. However, the impact of iron on the immune status of macrophages is still controversial. In this study, we report that ferric ammonium citrate (FAC) upregulates PD-L1 expression in macrophages. FAC not only altered the phenotype of macrophages but also led to enriching immune-modulatory T cell subsets. Since iron is known to be a constituent of coenzymes facilitating metabolic processes in mitochondria, we examined the metabolic status of FAC-overloaded macrophages by measuring the oxygen consumption rate (OCR) and the represented coenzyme, aconitase. In addition to enhancement of metabolic processes, FAC accelerated the Fenton reaction in macrophages, which also contributed to the facilitation of oxygen consumption. We reasoned that the enhancement of the OCR leads to the production of reactive oxygen species (ROS), which are directly linked to PD-L1 induction. Using ferrostatin, rotenone, and N-acetyl-L-cysteine, we confirmed that metabolic and redox regulation is responsible for FAC-mediated PD-L1 expression. Furthermore, we suggested that FAC-induced ROS production may explain FAC-mediated pro- and anti-inflammatory responses in macrophages. These findings may extend our understanding of regulating iron concentration during immune checkpoint therapy in cancer patients.

Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging Assessment of Optic Pathway Function in Patients With Anterior Visual Pathway Compression.

BACKGROUND: In patients with sellar or parasellar tumors, it is crucial to evaluate visual field impairment in the preoperative stage and to predict visual field improvement after the surgery. The purpose of this study was to investigate the associations of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters in the optic radiations with preoperative and postoperative visual field impairment. METHODS: This prospective study included 81 participants with sellar or parasellar tumors. Multishell diffusion imaging and a visual field impairment score (VFIS) were acquired before and after the surgery. The multishell diffusion-weighted imaging was acquired to measure the neurite density and neurite orientation dispersion, as well as the diffusivity. DTI parameters were fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity (RD). NODDI provided intracellular volume fraction (Vic), the orientation dispersion index, and isotropic volume fraction (Viso). The associations of DTI and NODDI parameters in the optic radiations with VFIS were investigated, adjusting for age, tumor height, and symptom duration. RESULTS: Among 162 optic radiations, 117 were functionally impaired in the preoperative stage. FA and Vic had significant negative correlations, whereas MD and RD had significant positive correlations with the VFIS (all P < 0.001). In the preoperative stage, lower FA (P = 0.001; odds ratio = 0.750) and Vic (P = 0.003; OR = 0.827) and higher MD (P = 0.007; OR = 1.244) and RD (P < 0.001; OR = 1.361) were significantly associated with the presence of visual field impairment. For the degree of postoperative improvement, preoperative lower Vic (P = 0.034; OR = 0.910) and higher MD (P = 0.037; OR = 1.103) and RD (P = 0.047; OR = 1.090) were significantly associated with more postoperative improvement. CONCLUSIONS: DTI and NODDI parameters in the optic radiations were correlated with VFIS and associated with preoperative visual field impairments and postoperative improvement. It may help in predicting visual field improvement after the surgery in patients with sellar or parasellar tumors.

Ectopic Male Breast Cancer in Suprapubic Area That Relapsed with Hematogenous Metastasis.

Tough ectopic male breast cancer is extremely rare, non-axillary ectopic male breast cancer is even rare. To date, the natural course and prognosis of this disease are not fully understood. Consequently, the appropriate treatment for this disease has not been established. We report on a patient with ectopic male breast cancer in the suprapubic area that relapsed with hematogenous metastasis 3 years after complete surgical resection and adjuvant treatment despite an early diagnosis. This unusual case highlights the need for new prognostic factors such as genomic profiling to predict whether ectopic male breast cancer is aggressive and to guide on the duration between follow-ups and the appropriate method for conducting them.

Intensive pulmonary rehabilitation in a pediatric lung transplantation patient: A case report.

BACKGROUND: The pediatric lung transplant is a very important treatment for patients with end-stage lung diseae, and pulmonary rehabilitation (PR) is also an important factor in determining the prognosis. However, there is no much literature available on pulmonary rehabilitation in pediatric patients' post lung transplant. Through this case report, we would like to present our intensive PR program for pediatric patients' post-lung transplant. PATIENT CONCERNS: The 10-year-old boy's breathing before receiving a lung transplant continued to deteriorate and he eventually became dependent on a wheelchair. DIAGNOSIS: He was diagnosed with infantile acute lymphoblastic leukemia at 6 months of age. At the age of one year, he underwent allogeneic bone marrow transplantation, but was diagnosed with post-transplantation bronchiolitis obliterans (PTBO) two months later. He had a lung transplant at the age of 10. INTERVENTIONS: He was hospitalized and received an initial assessment. This assessment included functional, cognitive, and psychological evaluations. He additionally completed PR exercises twice daily for two weeks. After discharge, he continued to participate in an outpatient-based PR program for three months. During the outpatient phase, PR exercises were performed once weekly, in addition to home-based cognitive training. OUTCOMES: Our intensive post-lung PR program improved our patient's exercise capacity, lung function, and quality of life. As a comprehensive rehabilitation service, our program also included a cognitive training component. CONCLUSION: We describe an intensive PR program tailored to pediatric patients' post-lung transplant. The program was feasible and resulted in improvements in functional exercise capacity, lung function, and quality of life. Future research into our method is necessary for continued improvement of this novel program.

Engineering subtilisin proteases that specifically degrade active RAS.

We describe the design, kinetic properties, and structures of engineered subtilisin proteases that degrade the active form of RAS by cleaving a conserved sequence in switch 2. RAS is a signaling protein that, when mutated, drives a third of human cancers. To generate high specificity for the RAS target sequence, the active site was modified to be dependent on a cofactor (imidazole or nitrite) and protease sub-sites were engineered to create a linkage between substrate and cofactor binding. Selective proteolysis of active RAS arises from a 2-step process wherein sub-site interactions promote productive binding of the cofactor, enabling cleavage. Proteases engineered in this way specifically cleave active RAS in vitro, deplete the level of RAS in a bacterial reporter system, and also degrade RAS in human cell culture. Although these proteases target active RAS, the underlying design principles are fundamental and will be adaptable to many target proteins.

Loss of metabolic flexibility as a result of overexpression of pyruvate dehydrogenase kinases in muscle, liver and the immune system: Therapeutic targets in metabolic diseases.

Good health depends on the maintenance of metabolic flexibility, which in turn is dependent on the maintenance of regulatory flexibility of a large number of regulatory enzymes, but especially the pyruvate dehydrogenase complex (PDC), because of its central role in carbohydrate metabolism. Flexibility in regulation of PDC is dependent on rapid changes in the phosphorylation state of PDC determined by the relative activities of the pyruvate dehydrogenase kinases (PDKs) and the pyruvate dehydrogenase phosphatases. Inactivation of the PDC by overexpression of PDK4 contributes to hyperglycemia, and therefore the serious health problems associated with diabetes. Loss of regulatory flexibility of PDC occurs in other disease states and pathological conditions that have received less attention than diabetes. These include cancers, non-alcoholic fatty liver disease, cancer-induced cachexia, diabetes-induced nephropathy, sepsis and amyotrophic lateral sclerosis. Overexpression of PDK4, and in some situations, the other PDKs, as well as under expression of the pyruvate dehydrogenase phosphatases, leads to inactivation of the PDC, mitochondrial dysfunction and deleterious effects with health consequences. The possible basis for this phenomenon, along with evidence that overexpression of PDK4 results in phosphorylation of "off-target" proteins and promotes excessive transport of Ca2+ into mitochondria through mitochondria-associated endoplasmic reticulum membranes are discussed. Recent efforts to find small molecule PDK inhibitors with therapeutic potential are also reviewed.

Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning.

To assist radiologists in breast cancer classification in automated breast ultrasound (ABUS) imaging, we propose a computer-aided diagnosis based on a convolutional neural network (CNN) that classifies breast lesions as benign and malignant. The proposed CNN adopts a modified Inception-v3 architecture to provide efficient feature extraction in ABUS imaging. Because the ABUS images can be visualized in transverse and coronal views, the proposed CNN provides an efficient way to extract multiview features from both views. The proposed CNN was trained and evaluated on 316 breast lesions (135 malignant and 181 benign). An observer performance test was conducted to compare five human reviewers' diagnostic performance before and after referring to the predicting outcomes of the proposed CNN. Our method achieved an area under the curve (AUC) value of 0.9468 with five-folder cross-validation, for which the sensitivity and specificity were 0.886 and 0.876, respectively. Compared with conventional machine learning-based feature extraction schemes, particularly principal component analysis (PCA) and histogram of oriented gradients (HOG), our method achieved a significant improvement in classification performance. The proposed CNN achieved a >10% increased AUC value compared with PCA and HOG. During the observer performance test, the diagnostic results of all human reviewers had increased AUC values and sensitivities after referring to the classification results of the proposed CNN, and four of the five human reviewers' AUCs were significantly improved. The proposed CNN employing a multiview strategy showed promise for the diagnosis of breast cancer, and could be used as a second reviewer for increasing diagnostic reliability.

Dynamic contrast-enhanced and diffusion-weighted MRI of invasive breast cancer for the prediction of sentinel lymph node status.

BACKGROUND: Although sentinel lymph node biopsy (SLNB) is the current standard for identifying lymph metastasis in breast cancer patients, there are complications of SLNB. PURPOSE: To evaluate preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) of invasive breast cancer for predicting sentinel lymph node metastasis. STUDY TYPE: Retrospective. POPULATION: In all, 309 patients who underwent clinically node-negative invasive breast cancer surgery FIELD STRENGTH/SEQUENCE: 3.0T, DCE-MRI, DWI. ASSESSMENT: We collected clinicopathologic variables (age, histologic and nuclear grade, extensive intraductal carcinoma component, lymphovascular invasion, and immunohistochemical profiles) and preoperative MRI features (tumor size, background parenchymal enhancement, internal enhancement, adjacent vessel sign, whole-breast vascularity, initial enhancement pattern, kinetic curve types, quantitative kinetic parameters, tumoral apparent diffusion coefficient [ADC], peritumoral maximal ADC, and peritumoral-tumoral ADC ratio). STATISTICAL TESTS: Multivariate logistic regressions were performed to determine independent variables associated with SLN metastasis, and the area under the receiver operating characteristic curve (AUC) was analyzed for those variables. RESULTS: 41 (13.3%) of the patients showed SLN metastasis. With MRI, tumor size (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.06-1.17), heterogeneous (OR, 5.33; 95% CI, 1.71-16.58), and rim (OR, 15.54; 95% CI, 2.12-113.72) enhancement and peritumoral-tumoral ADC ratio (OR, 72.79; 95% CI, 7.15-740.82) were independently associated with SLN metastasis. Clinicopathologic variables independently associated with SLN metastasis included age (OR, 0.96; 95% CI, 0.92-0.99) and CD31 (OR, 2.90; 95% CI, 1.04-8.92). The area under the curve (AUC) of MRI features (0.80; 95% CI, 0.73-0.87) was significantly higher than for clinicopathologic variables (0.68; 95% CI, 0.60-0.77; P = 0.048) and was barely below statistical significance for combined MRI features with clinicopathologic variables (0.84; 95% CI 0.78-0.90, P = 0.057). DATA CONCLUSION: Preoperative internal enhancement on DCE-MRI and peritumoral-tumoral ADC ratio on DWI might be useful for predicting SLN metastasis in patients with invasive breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:615-626.

Scoring System to Stratify Malignancy Risks for Mammographic Microcalcifications Based on Breast Imaging Reporting and Data System 5th Edition Descriptors.

OBJECTIVE: To develop a scoring system stratifying the malignancy risk of mammographic microcalcifications using the 5th edition of the Breast Imaging Reporting and Data System (BI-RADS). MATERIALS AND METHODS: One hundred ninety-four lesions with microcalcifications for which surgical excision was performed were independently reviewed by two radiologists according to the 5th edition of BI-RADS. Each category's positive predictive value (PPV) was calculated and a scoring system was developed using multivariate logistic regression. The scores for benign and malignant lesions or BI-RADS categories were compared using an independent t test or by ANOVA. The area under the receiver operating characteristic curve (AUROC) was assessed to determine the discriminatory ability of the scoring system. Our scoring system was validated using an external dataset. RESULTS: After excision, 69 lesions were malignant (36%). The PPV of BI-RADS descriptors and categories for calcification showed significant differences. Using the developed scoring system, mean scores for benign and malignant lesions or BI-RADS categories were significantly different (p < 0.001). The AUROC of our scoring system was 0.874 (95% confidence interval, 0.840-0.909) and the PPV of each BI-RADS category determined by the scoring system was as follows: category 3 (0%), 4A (6.8%), 4B (19.0%), 4C (68.2%), and 5 (100%). The validation set showed an AUROC of 0.905 and PPVs of 0%, 8.3%, 11.9%, 68.3%, and 94.7% for categories 3, 4A, 4B, 4C, and 5, respectively. CONCLUSION: A scoring system based on BI-RADS morphology and distribution descriptors could be used to stratify the malignancy risk of mammographic microcalcifications.