KR158 spheres harboring slow-cycling cells recapitulate GBM features in an immunocompetent system.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment-resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor-microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM-pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Usefulness of Saline Sealing in Preventing Pneumothorax after CT-Guided Biopsies of the Lung.

This study aimed to assess the effectiveness of saline sealing in reducing the incidence of pneumothorax after a CT-guided lung biopsy. This was a retrospective case-control study of patients who underwent CT-guided biopsies for lung tumors using 18 G semiautomatic core needles in conjunction with 17 G coaxial needles. The patients were divided into two consecutive groups: a historical Group A (n = 111), who did not receive saline sealing, and Group B (n = 87), who received saline sealing. In Group B, NaCl 0.9% was injected through the coaxial needle upon its removal. The incidence of pneumothorax and chest tube insertion was compared between the two groups. Multivariate logistic regression was performed to verify the contribution of other pneumothorax risk factors. The study included 198 patients, with 111 in Group A and 87 in Group B. There was a significantly (p = 0.02) higher pneumothorax rate in Group A (35.1%, n = 39) compared to Group B (20.7%, n = 18). The difference regarding chest tube insertion was not significant (p = 0.1), despite a tendency towards more insertions in Group A (5.4%, n = 6), compared to Group B (1.1%, n = 1). Among the risk factors for pneumothorax, only the presence of emphysema (OR = 3.5, p = 0.0007) and belonging to Group A (OR = 2.2, p = 0.02) were significant. Saline sealing of the needle tract after a CT-guided lung biopsy can significantly reduce the incidence of pneumothorax. This technique is safe, readily available, and inexpensive, and should be considered as a routine preventive measure during this procedure.

Urethral Mesh Assessment in Cancer Patients.

Urethral mesh placement has become a common surgical intervention for the management of stress urinary incontinence. While this procedure offers significant benefits, it is not without potential complications. This review article aims to provide a comprehensive overview of urethral mesh assessment in oncologic patients. The article explores normal magnetic resonance imaging (MRI) and computed tomography (CT) mesh appearances and highlights the pathological aspects associated with urethral mesh complications including both short-term and long-term post-operative complications. By understanding the spectrum of normal findings of urethral mesh and the possible complications, clinicians can improve patient outcomes and make informed decisions regarding urethral mesh management in this patient population.

Whole-Tumor ADC Texture Analysis Is Able to Predict Breast Cancer Receptor Status.

There are different breast cancer molecular subtypes with differences in incidence, treatment response and outcome. They are roughly divided into estrogen and progesterone receptor (ER and PR) negative and positive cancers. In this retrospective study, we included 185 patients augmented with 25 SMOTE patients and divided them into two groups: the training group consisted of 150 patients and the validation cohort consisted of 60 patients. Tumors were manually delineated and whole-volume tumor segmentation was used to extract first-order radiomic features. The ADC-based radiomics model reached an AUC of 0.81 in the training cohort and was confirmed in the validation set, which yielded an AUC of 0.93, in differentiating ER/PR positive from ER/PR negative status. We also tested a combined model using radiomics data together with ki67% proliferation index and histological grade, and obtained a higher AUC of 0.93, which was also confirmed in the validation group. In conclusion, whole-volume ADC texture analysis is able to predict hormonal status in breast cancer masses.

MRI Radiomics and Predictive Models in Assessing Ischemic Stroke Outcome-A Systematic Review.

Stroke is a leading cause of disability and mortality, resulting in substantial socio-economic burden for healthcare systems. With advances in artificial intelligence, visual image information can be processed into numerous quantitative features in an objective, repeatable and high-throughput fashion, in a process known as radiomics analysis (RA). Recently, investigators have attempted to apply RA to stroke neuroimaging in the hope of promoting personalized precision medicine. This review aimed to evaluate the role of RA as an adjuvant tool in the prognosis of disability after stroke. We conducted a systematic review following the PRISMA guidelines, searching PubMed and Embase using the keywords: 'magnetic resonance imaging (MRI)', 'radiomics', and 'stroke'. The PROBAST tool was used to assess the risk of bias. Radiomics quality score (RQS) was also applied to evaluate the methodological quality of radiomics studies. Of the 150 abstracts returned by electronic literature research, 6 studies fulfilled the inclusion criteria. Five studies evaluated predictive value for different predictive models (PMs). In all studies, the combined PMs consisting of clinical and radiomics features have achieved the best predictive performance compared to PMs based only on clinical or radiomics features, the results varying from an area under the ROC curve (AUC) of 0.80 (95% CI, 0.75-0.86) to an AUC of 0.92 (95% CI, 0.87-0.97). The median RQS of the included studies was 15, reflecting a moderate methodological quality. Assessing the risk of bias using PROBAST, potential high risk of bias in participants selection was identified. Our findings suggest that combined models integrating both clinical and advanced imaging variables seem to better predict the patients' disability outcome group (favorable outcome: modified Rankin scale (mRS) ≤ 2 and unfavorable outcome: mRS > 2) at three and six months after stroke. Although radiomics studies' findings are significant in research field, these results should be validated in multiple clinical settings in order to help clinicians to provide individual patients with optimal tailor-made treatment.

Texture Analysis in Uterine Cervix Carcinoma: Primary Tumour and Lymph Node Assessment.

The conventional magnetic resonance imaging (MRI) evaluation and staging of cervical cancer encounters several pitfalls, partially due to subjective evaluations of medical images. Fifty-six patients with histologically proven cervical malignancies (squamous cell carcinomas, n = 42; adenocarcinomas, n = 14) who underwent pre-treatment MRI examinations were retrospectively included. The lymph node status (non-metastatic lymph nodes, n = 39; metastatic lymph nodes, n = 17) was assessed using pathological and imaging findings. The texture analysis of primary tumours and lymph nodes was performed on T2-weighted images. Texture parameters with the highest ability to discriminate between the two histological types of primary tumours and metastatic and non-metastatic lymph nodes were selected based on Fisher coefficients (cut-off value > 3). The parameters' discriminative ability was tested using an k nearest neighbour (KNN) classifier, and by comparing their absolute values through an univariate and receiver operating characteristic analysis. Results: The KNN classified metastatic and non-metastatic lymph nodes with 93.75% accuracy. Ten entropy variations were able to identify metastatic lymph nodes (sensitivity: 79.17-88%; specificity: 93.48-97.83%). No parameters exceeded the cut-off value when differentiating between histopathological entities. In conclusion, texture analysis can offer a superior non-invasive characterization of lymph node status, which can improve the staging accuracy of cervical cancers.

Multiparametric MRI Features of Breast Cancer Molecular Subtypes.

Background and Objectives: Breast cancer (BC) molecular subtypes have unique incidence, survival and response to therapy. There are five BC subtypes described by immunohistochemistry: luminal A, luminal B HER2 positive and HER2 negative, triple negative (TNBC) and HER2-enriched. Multiparametric breast MRI (magnetic resonance imaging) provides morphological and functional characteristics of breast tumours and is nowadays recommended in the preoperative setting. Aim: To evaluate the multiparametric MRI features (T2-WI, ADC values and DCE) of breast tumours along with breast density and background parenchymal enhancement (BPE) features among different BC molecular subtypes. Materials and Methods: This was a retrospective study which included 344 patients. All underwent multiparametric breast MRI (T2WI, ADC and DCE sequences) and features were extracted according to the latest BIRADS lexicon. The inter-reader agreement was assessed using the intraclass coefficient (ICC) between the ROI of ADC obtained from the two breast imagers (experienced and moderately experienced). Results: The study population was divided as follows: 89 (26%) with luminal A, 39 (11.5%) luminal B HER2 positive, 168 (48.5%) luminal B HER2 negative, 41 (12%) triple negative (TNBC) and 7 (2%) with HER2 enriched. Luminal A tumours were associated with special histology type, smallest tumour size and persistent kinetic curve (all p-values < 0.05). Luminal B HER2 negative tumours were associated with lowest ADC value (0.77 × 10−3 mm2/s2), which predicts the BC molecular subtype with an accuracy of 0.583. TNBC were associated with asymmetric and moderate/marked BPE, round/oval masses with circumscribed margins and rim enhancement (all p-values < 0.05). HER2 enriched BC were associated with the largest tumour size (mean 37.28 mm, p-value = 0.02). Conclusions: BC molecular subtypes can be associated with T2WI, ADC and DCE MRI features. ADC can help predict the luminal B HER2 negative cases.

Heterogeneity of glioblastoma stem cells in the context of the immune microenvironment and geospatial organization.

Glioblastoma (GBM) is an extremely aggressive and incurable primary brain tumor with a 10-year survival of just 0.71%. Cancer stem cells (CSCs) are thought to seed GBM's inevitable recurrence by evading standard of care treatment, which combines surgical resection, radiotherapy, and chemotherapy, contributing to this grim prognosis. Effective targeting of CSCs could result in insights into GBM treatment resistance and development of novel treatment paradigms. There is a major ongoing effort to characterize CSCs, understand their interactions with the tumor microenvironment, and identify ways to eliminate them. This review discusses the diversity of CSC lineages present in GBM and how this glioma stem cell (GSC) mosaicism drives global intratumoral heterogeneity constituted by complex and spatially distinct local microenvironments. We review how a tumor's diverse CSC populations orchestrate and interact with the environment, especially the immune landscape. We also discuss how to map this intricate GBM ecosystem through the lens of metabolism and immunology to find vulnerabilities and new ways to disrupt the equilibrium of the system to achieve improved disease outcome.

Are Mutation Carrier Patients Different from Non-Carrier Patients? Genetic, Pathology, and US Features of Patients with Breast Cancer.

The purpose of this study is to evaluate the relationship between the pathogenic/likely pathogenic mutations, US features, and histopathologic findings of breast cancer in mutation carriers compared to non-carrier patients. Methods: In this retrospective study, we identified 264 patients with breast cancer and multigene panel testing admitted to our clinic from January 2018 to December 2020. Patient data US findings, US assessment of the axilla, multigene panel tests, histopathology, and immunochemistry reports were reviewed according to the BI-RADS lexicon. Results: The study population was comprised of 40% pathogenic mutation carriers (BRCA1, BRCA2, CHEK2, ATM, PALB, TP 53, NBN, MSH, BRIP 1 genes) and 60% mutation-negative patients. The mean patient age was 43.5 years in the carrier group and 44 years in the negative group. Carrier patients developed breast cancer with benign morphology (acoustic enhancement, soft elastography appearance) compared to non-carriers (p < 0.05). A tendency towards specific US features was observed for each mutation. BRCA1 carriers were associated with BC with microlobulated margins, hyperechoic rim, and soft elastography appearance (p < 0.05). Estrogen receptor (ER)-negative tumors were associated with BRCA1, TP53, and RAD mutations, while BRCA2 and CHEK2 were associated with ER-positive tumors. Conclusions: Patients with pathogenic mutations may exhibit BC with benign US features compared to negative, non-carrier patients. BRCA1, TP53, and RAD carriers account for up to one third of the ER tumors from the carrier group. Axillary US performed worse in depicting involved lymph nodes in carrier patients, compared to negative patients.

The Utility of ADC First-Order Histogram Features for the Prediction of Metachronous Metastases in Rectal Cancer: A Preliminary Study.

This study aims the ability of first-order histogram-based features, derived from ADC maps, to predict the occurrence of metachronous metastases (MM) in rectal cancer. A total of 52 patients with pathologically confirmed rectal adenocarcinoma were retrospectively enrolled and divided into two groups: patients who developed metachronous metastases (n = 15) and patients without metachronous metastases (n = 37). We extracted 17 first-order (FO) histogram-based features from the pretreatment ADC maps. Student's t-test and Mann-Whitney U test were used for the association between each FO feature and presence of MM. Statistically significant features were combined into a model, using the binary regression logistic method. The receiver operating curve analysis was used to determine the diagnostic performance of the individual parameters and combined model. There were significant differences in ADC 90th percentile, interquartile range, entropy, uniformity, variance, mean absolute deviation, and robust mean absolute deviation in patients with MM, as compared to those without MM (p values between 0.002-0.01). The best diagnostic was achieved by the 90th percentile and uniformity, yielding an AUC of 0.74 [95% CI: 0.60-0.8]). The combined model reached an AUC of 0.8 [95% CI: 0.66-0.90]. Our observations point out that ADC first-order features may be useful for predicting metachronous metastases in rectal cancer.

Magnetic resonance imaging characteristics of chronic prostatitis in patients under the age of 50: is it more than the eye can see?

BACKGROUND: The magnetic resonance (MRI) diagnosis of chronic prostatitis (CP) is insufficiently evaluated. PURPOSE: To evaluate the MRI appearance of CP in young patients by comparing it to individuals with non-prostatic related pathology. MATERIAL AND METHODS: The study included 47 patients with prostatitis-like symptoms evaluated by urologists and referred to pelvic MRI examination (mean age=40.23±7 years; age range=23-49 years) and 93 age-matched individuals with non-prostatic related pathology (mean age=37.5±7 years; age range=21-49 years). All MRI examinations were performed on a 1.5-T machine using a prostate-specific protocol for the prostatitis group and different protocols that included high-resolution small field of view T2-weighted (T2WI) and diffusion-weighted imaging (DWI), for the control group, depending on the clinical indication. RESULTS: Four different T2WI intensity patterns were observed: hyperintense homogenous; slightly to moderate homogenous hypointense; inhomogeneous; and marked hypointense. We found statistically significant differences between the two analyzed groups regarding mean ADC values (P<0.001), distribution of T2WI intensity patterns (P<0.0001), and the presence of dilated venous plexus (P=0.0007). No differences were found regarding prostate volume (P=0.15). In multivariate analysis, all four analyzed imaging parameters were independent predictors of chronic prostatitis (R2=0.67; P<0.0001). Considered together, an age >28 years, an inhomogeneous or marked hypointense T2WI intensity pattern (types 3 and 4), an ADC value ≤1250, and the presence of dilated venous plexus are able to predict CP with an AUC of 93% (sensitivity=85.1%, specificity=88.4%). CONCLUSION: MR parameters like T2WI intensity patterns, ADC values, and venous plexus appearance are promising non-invasive tools in the challenging environment of CP diagnosis.

The Role of US in Depicting Axillary Metastasis in High-Risk Breast Cancer Patients.

PURPOSE: The aim of this study is to evaluate the role of US in depicting axillary nodal disease in high-risk patients with and without pathogenic mutations. Methods: The retrospective study included consecutive high-risk breast cancer (BC) patients who underwent a multigene testing panel for hereditary cancers, pre-operative axillary US and breast/axillary surgery. The group was divided into patients with pathogenic mutations (PM group) and patients without PM. Statistical analyses were performed using GraphPad Prism by applying Chi-square and Fisher exact tests, with a reference p-value < 0.05 and a CI of 95%. Results: Out of 190 patients with BC, 96 (51%) were negative and 94 (49%) were positive for PM as follows: 28 (25.5%) BRCA1, 16 (17%) BRCA2, 15 (16%) CHECK2, 14 (14%) RAD Group, 7 (7%) PALB, 6 (6%) NBN, 3 (3%) TP53 and ATM and 2 (2%) BARD1. US was positive in 88 of the patients, 36 with PM and 52 without PM. US and surgery (≥N1 stage) were both positive in 31 (62%) of PM patients and 44 (88%) of patients without genetic changes. There were 19 (61%) false negative US examinations in the PM group and 6 (13%) in the group without genetic changes, respectively. If the US is positive, there is a 2.6 times greater risk of positive nodes in PM patients (p-value < 0.000, 95% CI = 4.2-37.9), and a 6.2 times greater risk of positive nodes in patients without genetic changes (p-value < 0.000, 95%CI = 8.4-37.4). In the PM group, US compared to surgery reached a sensitivity = 62, with PPV = 86 and NPV = 67. In the BRCA1/2 subgroup, there is 2.5 greater times risk of nodal disease if the US is positive (p-value = 0.001, 95%CI = 2.6-76). In patients without PM, US compared to surgery reached a sensitivity = 88, PPV = 84 and NPV = 86. Conclusion: US is more sensitive in depicting axillary nodal disease in high-risk patients without PM compared to PM patients. Furthermore, there are more false negative US examinations in PM patients, compared to surgery patients.

Preoperative Predicting the WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma by Computed Tomography-Based Radiomics Features.

Nuclear grade is important for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). This study aimed to determine the ability of preoperative four-phase multiphasic multidetector computed tomography (MDCT)-based radiomics features to predict the WHO/ISUP nuclear grade. In all 102 patients with histologically confirmed ccRCC, the training set (n = 62) and validation set (n = 40) were randomly assigned. In both datasets, patients were categorized according to the WHO/ISUP grading system into low-grade ccRCC (grades 1 and 2) and high-grade ccRCC (grades 3 and 4). The feature selection process consisted of three steps, including least absolute shrinkage and selection operator (LASSO) regression analysis, and the radiomics scores were developed using 48 radiomics features (10 in the unenhanced phase, 17 in the corticomedullary (CM) phase, 14 in the nephrographic (NP) phase, and 7 in the excretory phase). The radiomics score (Rad-Score) derived from the CM phase achieved the best predictive ability, with a sensitivity, specificity, and an area under the curve (AUC) of 90.91%, 95.00%, and 0.97 in the training set. In the validation set, the Rad-Score derived from the NP phase achieved the best predictive ability, with a sensitivity, specificity, and an AUC of 72.73%, 85.30%, and 0.84. We constructed a complex model, adding the radiomics score for each of the phases to the clinicoradiological characteristics, and found significantly better performance in the discrimination of the nuclear grades of ccRCCs in all MDCT phases. The highest AUC of 0.99 (95% CI, 0.92-1.00, p < 0.0001) was demonstrated for the CM phase. Our results showed that the MDCT radiomics features may play a role as potential imaging biomarkers to preoperatively predict the WHO/ISUP grade of ccRCCs.

Radiomic Analysis of MRI Images is Instrumental to the Stratification of Ovarian Cysts.

The imaging diagnosis of malignant ovarian cysts relies on their morphological features, which are not always specific to malignancy. The histological analysis of these cysts shows specific fluid characteristics, which cannot be assessed by conventional imaging techniques. This study investigates whether the texture-based radiomics analysis (TA) of magnetic resonance (MRI) images of the fluid content within ovarian cysts can function as a noninvasive tool in differentiating between benign and malignant lesions. Twenty-eight patients with benign (n = 15) and malignant (n = 13) ovarian cysts who underwent MRI examinations were retrospectively included. TA of the fluid component was undertaken on an axial T2-weighted sequence. A comparison of resulted parameters between benign and malignant groups was undertaken using univariate, multivariate, multiple regression, and receiver operating characteristics analyses, with the calculation of the area under the curve (AUC). The standard deviation of pixel intensity was identified as an independent predictor of malignant cysts (AUC = 0.738; sensitivity, 61.54%; specificity, 86.67%). The prediction model was able to identify malignant lesions with 84.62% sensitivity and 80% specificity (AUC = 0.841). TA of the fluid contained within the ovarian cysts can differentiate between malignant and benign lesions and potentially act as a noninvasive tool augmenting the imaging diagnosis of ovarian cystic lesions.

Nipple Ultrasound: A Pictorial Essay.

Ultrasound (US) is an attractive diagnostic approach to identify both common and uncommon nipple pathologies, such as duct ectasia, nipple abscess, nipple leiomyoma, nipple adenoma, fibroepithelial polyp, ductal carcinoma in situ (restricted to nipple), invasive carcinoma, and Paget's disease. US is the reliable first-line imaging technique to assess nipple pathologies. It is useful to identify and characterize nipple lesions. Additionally, we have presented the mammography and MRI outcomes correlated with histopathologic features for the relevant cases.

Pre-Treatment T2-WI Based Radiomics Features for Prediction of Locally Advanced Rectal Cancer Non-Response to Neoadjuvant Chemoradiotherapy: A Preliminary Study.

Locally advanced rectal cancer (LARC) response to neoadjuvant chemoradiotherapy (nCRT) is very heterogeneous and up to 30% of patients are considered non-responders, presenting no tumor regression after nCRT. This study aimed to determine the ability of pre-treatment T2-weighted based radiomics features to predict LARC non-responders. A total of 67 LARC patients who underwent a pre-treatment MRI followed by nCRT and total mesorectal excision were assigned into training (n = 44) and validation (n = 23) groups. In both datasets, the patients were categorized according to the Ryan tumor regression grade (TRG) system into non-responders (TRG = 3) and responders (TRG 1 and 2). We extracted 960 radiomic features/patient from pre-treatment T2-weighted images. After a three-step feature selection process, including LASSO regression analysis, we built a radiomics score with seven radiomics features. This score was significantly higher among non-responders in both training and validation sets (p < 0.001 and p = 0.03) and it showed good predictive performance for LARC non-response, achieving an area under the curve (AUC) = 0.94 (95% CI: 0.82-0.99) in the training set and AUC = 0.80 (95% CI: 0.58-0.94) in the validation group. The multivariate analysis identified the radiomics score as an independent predictor for the tumor non-response (OR = 6.52, 95% CI: 1.87-22.72). Our results indicate that MRI radiomics features could be considered as potential imaging biomarkers for early prediction of LARC non-response to neoadjuvant treatment.

Visualization of the shear wave on gray-scale ultrasound: experience with a complex breast cyst.

Shear wave elastography (SWE) is the newer of the two methods of measuring tissue stiffness using ultrasound. We present the case of a 39-year-old patient with fibrocystic breast disease who presented with a left painful breast lump. The patient underwent a breast ultrasound that depicted a complicated cyst with a "pseudo-solid" content. When the SWE mode was turned on, the ultrasound share wave was observed on the gray-scale image, as surface undulations of the "pseudo-solid" component. To the best of our knowledge, this is the first report of the share wave visualization on a gray-scale image. The impact on patient management is discussed.

Prospective investigation of pain associated with ultrasound- and computed tomography-guided percutaneous biopsies in oncological patients.

AimsThe present study aims to investigate the pain, anxiety and other factors that are associated with percutaneous computed tomography (CT)- and ultrasound (US)-guided biopsies of tumors.Material and MethodsThe study prospectively included 60 consecutive patients, of which 24 underwent CT-guided biopsies and 36 US-guided biopsies. The location of targeted tumors was within the thorax, abdomen, pelvis, and limbs. A questionnaire containing numerical rate scales (0-10) regarding procedural and post-procedural pain, anxiety, and other associated parameters was filled out by each patient 2-6 hours after the procedure. CT and ultrasound parameters were compared.  The two groups were then pooled together in order to compare pain scores per targeted organ and to analyze the parameters that were associated with pain.ResultsThere was no significant difference between the CT and US group with the exception of the positional discomfort, which was higher in the CT group (p=0.003). The average procedural pain score (2.0) was significantly higher than the post-procedural pain (1.3, p=0.006) and the phlebotomy pain (0.8, p<0.0001). There was no significant difference between the targeted organs with regards to the pain score. The factors that showed a positive correlation with the procedural pain were procedure-related anxiety (p=0.005), positional discomfort (p=0.01), and phlebotomy pain (p=0.0008). The pre interventional use of an analgesic was negatively correlated with the procedural pain (p=0.02).ConclusionsCT- and US- guided percutaneous biopsies are associated with low levels of pain that are generally well tolerated by patients irrespective of the targeted organ.

Association between cardiovascular risk factors and coronary artery disease assessed using CAD-RADS classification: a cross-sectional study in Romanian population.

OBJECTIVES: This study aimed to evaluate the association between cardiovascular risk factors and Coronary Artery Disease-Reporting and Data System (CAD-RADS) score in the Romanian population. CAD-RADS is a new, standardised method to assess coronary artery disease (CAD) using coronary CT angiography (CCTA). DESIGN: A cross-sectional observational, patient-based study. SETTING: Referred imaging centre for CAD in Transylvania, Romania. PARTICIPANTS: We retrospectively reviewed 674 patients who underwent CCTA between January 2017 and August 2018. The exclusion criteria included: previously known CAD, defined as prior myocardial infarction, percutaneous coronary intervention or coronary artery bypass graft surgery (n=91), cardiac CT for other than evaluation of possible CAD (n=85), significant arrhythmias compromising imaging quality (n=23). Finally, 475 patients fulfilled the inclusion criteria. METHODS: Demographical, clinical and CCTA characteristics of the patients were obtained. CAD was evaluated using CAD-RADS score. Obstructive CAD was defined as ≥50% stenosis of ≥1 coronary segment on CCTA. RESULTS: We evaluated the association between risk factors and CAD-RADS score in univariate and multivariable analysis. We divided the patients into two groups according to the CAD-RADS system: group 1: CAD-RADS score between 0 and 2 (stenosis <50%) and group 2: CAD-RADS score ≥3 (stenosis ≥50%). On univariate analysis, male gender, age, hypertension, dyslipidaemia, smoking and diabetes mellitus were positively associated with a CAD-RADS score ≥3. The multivariate analysis showed that male sex, age, dyslipidaemia, hypertension and smoking were independently associated with obstructive CAD. CONCLUSION: This study demonstrated a significant association between multiple cardiovascular risk factors and a higher coronary atherosclerotic burden assessed using CAD-RADS system in the Romanian population.

Impact of Strain Elastography on BI-RADS classification in small invasive lobular carcinoma.

AIMS: The purpose of this study was to determine the impact of strain elastography (SE) on the Breast Imaging Reporting Data System (BI-RADS) classification depending on invasive lobular carcinoma (ILC) lesion size. MATERIALS AND METHODS: We performed a retrospective analysis on a sample of 152 female subjects examined between January 2010 - January 2017. SE was performed on all patients and ILC was subsequently diagnosed by surgical or ultrasound-guided biopsy. BI-RADS 1, 2, 6 and Tsukuba BGR cases were omitted. BI-RADS scores were recorded before and after the use of SE. The differences between scores were compared to the ILC tumor size using nonparametric tests and logistic binary regression. We controlled for age, focality, clinical assessment, heredo-collateral antecedents, B-mode and Doppler ultrasound examination. An ROC curve was used to identify the optimal cut-off point for size in relationship to BI-RADS classificationdifference using Youden's index. RESULTS: The histological subtypes of ILC lesions (n=180) included in the sample were luminal A (70%, n=126), luminal B (27.78%, n=50), triple negative (1.67%, n=3) and HER2+ (0.56%, n=1). The BI-RADS classification was higher when SE was performed (Z=- 6.629, p<0.000). The ROC curve identified a cut-off point of 13 mm for size in relationship to BI-RADS classification difference (J=0.670, p<0.000). Small ILC tumors were 17.92% more likely to influence BI-RADS classification (p<0.000). CONCLUSIONS: SE offers enhanced BI-RADS classification in small ILC tumors (<13 mm). Sonoelastography brings added value to B-mode breast ultrasound as an adjacent to mammography in breast cancer screening.