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Background: Imaging of the postoperative breast is a challenging issue for the interpreting physician with many variable findings that may require additional assessment through targeted ultrasound, more mammography views, or other investigations. Artificial intelligence (AI) is a fast-developing field with various applications in the breast imaging including the detection and classification of lesions, the prediction of therapy response, and the prediction of breast cancer risk. This study aimed to identify whether Artificial Intelligence improves the mammographic detection and diagnosis of breast post-operative changes and hence improves follow-up and diagnostic workflow and reduces the need for additional exposure to extra radiation or contrast material doses as in Contrast Enhanced Mammography, and the need for interventional procedures as biopsy. Methods: This cross-sectional analytic study included 66 female patients following breast-conserving surgeries coming with breast complaints or for follow-up, with mammographically diagnosed changes. Results: Mammography had a sensitivity of 91.7%, a specificity of 94.4%, a positive predictive value (PPV) of 78.6%, a negative predictive value (NPV) of 98.1%, and an accuracy of 93.9%, while the AI method indices were sensitivity 91.7%, specificity 92.6%, (PPV) 73.3%, (NPV) 98%, and accuracy 92.4%. The calculated cut-off point for the quantitative AI (probability of malignancy "POM" score) was 51.5%. There was a statistically significantly higher average in the percentage of POM in malignant cases (76.5 ± 27.3%) compared to benign cases (27.1 ± 19.7%). However, the final indices for the combined use of mammography and (AI) were sensitivity 100%, specificity 88.9%, (PPV) 66.7%, (NPV) 100%, and accuracy 90.9%. Conclusion: Applying the AI algorithm on mammograms showed positive impacts on the sensitivity of the post-operative breast assessment, with an excellent reduction of the mammographic missed cancers. [ABSTRACT FROM AUTHOR]

Background: The staging and management of patients with breast cancer are significantly influenced by the pathological state of the axillary lymph nodes (ALN). Thus, it is very desirable to have a differential diagnosis of metastatic ALN. Purpose: The aim of this research is to assess the effectiveness of non-invasive ALN staging using PEM versus traditional breast mammography and ultrasound in patients presenting with early-stage breast cancer. This study focuses on determining if PEM can reliably stage ALNs and potentially eliminate the need for more invasive methods. Methods: In a study involving 94 breast cancer patients, PEM was used to assess ALNs. The nodes were visually evaluated for positive or negative uptake, and further categorized as non-specific, indeterminate, or malignant based on their maximum uptake values. This classification was then compared with histopathological results. Results: There were a total of 94 breast cancer patients; the results from PEM demonstrated an ALN detection sensitivity of 83.3%. The specificity of PEM in this context was found to be 98.08%, and the overall accuracy rate was 91.49%. Additionally, the Positive Predictive Value (PPV) was calculated to be 97.2%, and the Negative Predictive Value (NPV) was 87.9%. Conclusions: The initial study has shown encouraging outcomes in terms of accurate lymph node assessment. [ABSTRACT FROM AUTHOR]

Background: Adnexal masses (AMs) are prevalent, leading to a substantial clinical effort including imaging for diagnosis, surgery, and pathology. Aim of the study: The goal of this research was to evaluate the reliability of the Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) scale for diagnosing the sonographically indeterminate adnexal masses and to discriminate between malignant and benign ones using the O-RADS MRI scoring system. Methods: This study included 72 cases with indeterminate adnexal masses in any age group. We excluded patients with previous history of operated adnexal lesion and patients who had contraindications for MRI as pacemakers or iron clips. Results: Based on O-RADS MRI score, 44.4% of masses were diagnosed as O-RADS II indicating that they were almost certainly benign, 11.1% as O-RADS III indicating low risk malignancy, 8.3% as O-RADS IV indicating intermediate risk malignancy and 36.1% were diagnosed as O-RADS V indicating high risk malignancy. O-RADS MRI score for malignancy gave sensitivity of 92.31% (95%CI 63.97–99.81), specificity of 82.61% (95%CI 61.22–95.05), PPV of 75% (95%CI 54.84–88.11) and NPV of 95% (95%CI 74.12–99.21) with an overall accuracy of 86.11% (95%CI 70.50–95.33). Conclusions: The O-RADS MRI score has excellent accuracy and validity in determining whether an AM is malignant or benign. Using this score in clinical practice may enable a tailored, patient-centered approach for masses that are sonographically indeterminate, avoiding unnecessary surgery, and in certain cases allows less extensive surgery, or even fertility preservation when appropriate. [ABSTRACT FROM AUTHOR]

Background and aims: Oral nutritional supplements (ONS) are considered a cornerstone in the treatment plan of malnutrition in cancer patients. However, the prevalence of inappropriate prescription of ONS is high. In this study, we aim to investigate the effect of inappropriate oral nutritional supplementation (consisting of prescription of ONS without evident clinical indication, or the absence of ONS when at risk of malnutrition) on the quality of life of cancer outpatients. Methods: A cross-sectional comparative study was conducted in 104 cancer outpatients, receiving ONS without prior malnutrition risk screening (n = 51), and patients not receiving ONS (n = 53). Nutritional risk screening was performed using the abridged patient-generated subjective global assessment (ab-PG-SGA). The quality of life was assessed using EORTC QLQ-C30 version 3.0 questionnaire. Multivariate analysis was conducted to determine the predictors of quality-of-life scales. Age (years), malnutrition (ab-PG-SGA scores), BMI (kg/m2), TSF (mm), MUAC (cm), ONS (yes, no) were entered into the linear regression analysis as predictors (backward stepwise linear regression analysis). Results: The prevalence of malnutrition risk (ab-PG-SGA ≥ 6) was 74%. The median score of the ab-PG-SGA for ONS receiving group was significantly higher (p = 0.045). Furthermore, univariate analysis showed that the scores of the global health status (QoL) and the role functioning (RF) scales were significantly lower for the ONS receiving group (p = 0.020 and p = 0.016, respectively). Multivariately, malnutrition, inappropriate ONS prescription, and triceps skin fold were found to be predictors of the RF scale, while malnutrition was the only predictor for the QoL. Conclusion: The inappropriate ONS prescription does not improve nutritional status or quality of life of cancer outpatients. [ABSTRACT FROM AUTHOR]

Background: Given the burden and poor outcome of end-stage renal disease in sickle cell disease (SCD), early markers of sickle cell nephropathy (SN) are desirable. Disordered angiogenesis underlies many complications of SCD. We aimed to determine the relationship between serum FMS-like tyrosine kinase-1 (sFLT-1) and other biomarkers of renal damage for the early diagnosis of SN. Methods: Forty-seven SCD patients and 49 healthy controls were enrolled. Microalbuminuria was determined in patient urine samples. Blood samples were tested for sFLT-1, serum creatinine, and various hemolysis and inflammation markers. Peripheral blood monocyte expression of sFLT-1 was measured using real-time polymerase chain reaction (PCR). Results: The serum level of sFLT-1 (pg/ml) in SCD patients was higher than controls (median/range/IQR = 142/ 60-1300/61 pg/ml vs. 125/ 110-187/52 pg/ml, respectively) ( p = 0.006). Median (range) of sFLT-1 level was higher in SCD patients with microalbuminuria compared to SCD patients with normoalbuminuria, 185 (140-1300) vs. 125 (60-189) mg/g, respectively) ( p = 0.004). There was a significant positive correlation between serum sFLT-1 and microalbuminuria, lactate dehydrogenase (LDH), and indirect bilirubin ( r = 0.59, 0.39, 0.30, and p = <0.001, 0.007, 0.041, respectively). sFLT-1 sensitivity in early detection of renal affection in SCD was 93.6 %, while specificity was 68.6 %. Finally, peripheral blood monocytes (PBM) sFLT-1 expression was significantly higher in SCD patients compared to controls ( p = 0.05). Conclusions: sFLT-1 may contribute to pathogenesis of albuminuria in SCD patients and constitute a novel renal biomarker of SN. [ABSTRACT FROM AUTHOR]