Background: Despite recent advancements, medical technology has not yet reached its peak. Precision medicine is growing rapidly, thanks to machine learning breakthroughs powered by increased computational capabilities. This article explores a deep learning application for computer-aided diagnosis in dermatology. Methods: Using a custom model based on EfficientNetB3 and deep learning, we propose an approach for skin lesion classification that offers superior results with smaller, cheaper, and faster inference times compared to other models. The skin images dataset used for this research includes 8222 files selected from the authors\' collection and the ISIC 2019 archive, covering six dermatological conditions. Results: The model achieved 95.4% validation accuracy in four categories-melanoma, basal cell carcinoma, benign keratosis-like lesions, and melanocytic nevi-using an average of 1600 images per category. Adding two categories with fewer images (about 700 each)-squamous cell carcinoma and actinic keratoses-reduced the validation accuracy to 88.8%. The model maintained accuracy on new clinical test images taken under the same conditions as the training dataset. Conclusions: The custom model demonstrated excellent performance on the diverse skin lesions dataset, with significant potential for further enhancements.

OBJECTIVE: In this study, a radiomics model was created based on High-Resolution Computed Tomography (HRCT) images to noninvasively predict whether the sub-centimeter pure Ground Glass Nodule (pGGN) is benign or malignant.
METHODS: A total of 235 patients (251 sub-centimeter pGGNs) who underwent preoperative HRCT scans and had postoperative pathology results were retrospectively evaluated. The nodules were randomized in a 7:3 ratio to the training (n=175) and the validation cohort (n=76). The volume of interest was delineated in the thin-slice lung window, from which 1316 radiomics features were extracted. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to select the radiomics features. Univariate and multivariable logistic regression were used to evaluate the independent risk variables. The performance was assessed by obtaining Receiver Operating Characteristic (ROC) curves for the clinical, radiomics, and combined models, and then the Decision Curve Analysis (DCA) assessed the clinical applicability of each model.
RESULTS: Sex, volume, shape, and intensity mean were chosen by univariate analysis to establish the clinical model. Two radiomics features were retained by LASSO regression to build the radiomics model. In the training cohort, the Area Under the Curve (AUC) of the radiomics (AUC=0.844) and combined model (AUC=0.871) was higher than the clinical model (AUC=0.773). In evaluating whether or not the sub-centimeter pGGN is benign, the DCA demonstrated that the radiomics and combined model had a greater overall net benefit than the clinical model.
CONCLUSIONS: The radiomics model may be useful in predicting the benign and malignant sub-centimeter pGGN before surgery.

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UNASSIGNED: Tobacco is consumed mainly as smoking or smokeless tobacco [SLT]. \"Smokeless tobacco\" (SLT) term is used for the consumption of tobacco mixed with other constituents in form of chewing, spitting and dipping. Consumers of smokeless tobacco chew the products and spit out the juice that builds up in oral cavity which leads to various malignant and pre malignant lesions of oral cavity.
UNASSIGNED: Descriptive observational study was conducted in the city of Jodhpur through department of ENT, Head & Neck Surgery, Dr. SN medical college, Jodhpur.
UNASSIGNED: Male to female ratio of smokeless tobacco usage was almost same. Increasing age was associated with occurrence of oral lesions and 43% patients developed oral lesions in the group > 64 yrs of age. Duration was another associating factor and 66% developed symptoms within < 10 years of usage. Oral submucous fibrosis is the most common lesion. Malignant lesions were seen in 0.3% cases. Around 78% cases developed dependency. Diabetic patients were seen more prone to development of oral lesions.
UNASSIGNED: Development of lesions in the oral cavity by smokeless tobacco depends on various factors such as quantity of tobacco usage per day, place of putting tobacco and duration. Awareness regarding its fatal effects and timely diagnosis and management can save many lives.

This study presents an innovative application of artificial intelligence (AI) in distinguishing dermoscopy images depicting individuals with benign and malignant skin lesions. Leveraging the collaborative capabilities of Google\'s platform, the developed model exhibits remarkable efficiency in achieving accurate diagnoses. The model underwent training for a mere one hour and 33 minutes, utilizing Google\'s servers to render the process both cost-free and carbon-neutral. Utilizing a dataset representative of both benign and malignant cases, the AI model demonstrated commendable performance metrics. Notably, the model achieved an overall accuracy, precision, recall (sensitivity), specificity, and F1 score of 92%. These metrics underscore the model\'s proficiency in distinguishing between benign and malignant skin lesions. The use of Google\'s Collaboration platform not only expedited the training process but also exemplified a cost-effective and environmentally sustainable approach. While these findings highlight the potential of AI in dermatopathology, it is crucial to recognize the inherent limitations, including dataset representativity and variations in real-world clinical scenarios. This study contributes to the evolving landscape of AI applications in dermatologic diagnostics, showcasing a promising tool for accurate lesion classification. Further research and validation studies are recommended to enhance the model\'s robustness and facilitate its integration into clinical practice.

Of note, one third of oral cancer or oral tissue dysfunction cases are from India, primarily resulting from the consumption of Gutkha, a type of smokeless tobacco prevalent among several Indian populations. Gutkha is a mixture of tobacco, areca nut, slaked lime, catechu, spices, sweeteners and essences. Oral submucous fibrosis (OSMF), which is linked to the consumption of areca nut products and tobacco, is a chronic, precancerous condition of the submucosal tissues. OSMF transforms into oral squamous cell carcinoma (OSCC) at a rate of 7-13%. Gutkha also contains various trace elements, such as copper (Cu), zinc (Zn), selenium (Se) and molybdenum (Mo). Alterations in trace element levels in the body are associated with cancer progression. The present study aimed to determine the levels of serum and salivary trace elements in patients with OSMF and OSCC. A total of 80 patients were selected for the study and were divided into four groups of 20 patients in each (Group A, gutkha intake without OSMF; group B, gutkha intake with OSMF; group C, OSCC; and group D, control). The level of Cu was found to be increased and the levels of Zn, Se and Mo were decreased in the serum of patients with OSMF and OSCC compared with the controls. The salivary levels of these elements were lower compared with those in the serum. Age and sex had no significant effect on the levels of these trace elements. The results of the present study affirm the fact that serum and salivary trace elements are altered in pre-malignant and malignant lesions as the disease progresses. As the composition of saliva often varies, monitoring serum trace element levels as diagnostic and prognostic markers may aid in the early detection of the disease and in the management of the treatment efficacy.

OBJECTIVE: The study aims at assessing the quantitative features which distinguish focal liver lesions (FLLs) in gadoxetic acid (GA) enhanced liver MRI and at determining whether these features can accurately differentiate benign from malignant lesions.
METHODS: 107 patients with 180 unequivocal FLLs in previous examinations were included in a single-center retrospective study. All patients underwent a MRI test of the liver with GA. 99 benign and 74 malignant lesions were included. The group of benign lesions consisted of 60 focal nodular hyperplasias (FNH), 22 hemangiomas (HMG), 6 hepatic adenomas (HA), and 11 other benign lesions (1 angiomyolipioma, 6 lesions histopathology diagnoses as benign without further specification, or ones lacking features of malignancy, and 4 lesions radiologically diagnosed as benign which remained stable in the follow-up studies). The group of malignant lesions consisted of primary 51 hepatocellular carcinomas, 12 metastases, and 11 metastases from melanoma malignum (MM meta). 7 FLLs were excluded (4 cases of uncertain histopathological diagnosis, 2 cholangiocarcinomas, and 1 regenerative nodule). For the included lesions ROI (region of interest) measurements were taken by two observers in the T2-w, ADC (apparent diffusion coefficient) and in the T1-w sequence in the hepatobiliary phase (HBP). The interobserver agreement was evaluated with the Wilcoxon test. The Kruskal - Wallis, Mann - Whitney U and post hoc Dunn\'s tests were applied to assess if there were any significant differences in the ROI values between individual lesions. The variables with the p values of < 0.05 were considered statistically significant.
RESULTS: We found significant differences in the ROI values between lesions with p < 0.0001. Strikingly high ROI values in the T2-w sequence were found for HMG. The lowest ADC values were encountered for metastases and MM metastases. The highest ROI values in the HBP were found for FNH, and the lowest for metastases. We also found statistically significant differences in the ROI values between benign and malignant lesions with benign lesions presenting statistically higher ROI values compared to malignant lesions.
CONCLUSIONS: There were significant differences in the ROI values among different types of FLLs. The predominant quantitative feature in the T2-w sequence was a strikingly high ROI value for HMG. Benign lesions presented statistically higher ROI values in the T2-w, ADC, and HBP sequences compared to malignant lesions. This was true for all lesions except for HA.

BACKGROUND: The most common technique for treating benign and early malignant rectal lesions is transanal endoscopic microsurgery (TEM). Local excision is an acceptable technique for high-risk and elderly patients, but there are hardly any data regarding young patients.
OBJECTIVE: To describe TEM outcomes in patients under 50 years of age.
METHODS: We collected demographic, clinical, and pathological data from all patients under the age of 50 years who underwent the TEM procedure at Hasharon Rabin Medical Center from January 2005 to December 2018.
RESULTS: During the study period, a total of 26 patients under the age of 50 years underwent TEM procedures. Their mean age was 43.3 years. Eleven (42.0%) were male. The mean operative time was 67 min, and the mean tumor size was 2.39 cm, with a mean anal verge distance of 8.50 cm. No major intraoperative or postoperative complications were recorded. The median length of stay was 2 d. Seven (26.9%) lesions were adenomas with low-grade dysplasia, four (15.4%) were high-grade dysplasia adenomas, two were T1 carcinomas (7.8%), and three were T2 carcinomas (11.5%). No residual disease was found following endoscopic polypectomy in two patients (7.8%), but four (15.4%) had other pathologies. Surgical margins were negative in all cases. Local recurrence was detected in one patient 33 mo following surgery.
CONCLUSIONS: Among young adult patients, TEM for benign rectal lesions has excellent outcomes. It may also offer a balance between the efficacy of complete oncologic resection and postoperative quality of life in the treatment of rectal cancer. In some cases, it may be considered an alternative to radical surgery.

UNASSIGNED: The primary objective is to optimize the population eligible for Mammotome Minimally Invasive Surgery (MIS) by refining selection criteria. This involves maximizing procedure benefits, minimizing malignancy risk, and reducing the rate of malignant outcomes.
UNASSIGNED: A total of 1158 female patients who came to our hospital from November 2016 to August 2021 for the Mammotome MIS were analyzed retrospectively. Following χ2 tests to screen for risk variables, binary logistic regression analysis was used to determine the independent predictors of malignant lesions. In addition, the correlation between age and lesion diameter was investigated for BI-RADS ultrasound (US) category 4a lesions in order to better understand the relationship between these variables.
UNASSIGNED: The malignancy rates of BI-RADS US category 3, category 4a and category 4b patients who underwent the Mammotome MIS were 0.6% (9/1562), 6.4% (37/578) and 8.3% (2/24) respectively. Malignant lesions were more common in patients over the age of 40, have visible blood supply, and BI-RADS category 4 of mammography. In BI-RADS US category 4a lesions, the diameter of malignant tumor was highly correlated with age, and this correlation was strengthened in patients over the age of 40 and with BI-RADS category 4 of mammography.
UNASSIGNED: The results of this study demonstrate that the clinical data and imaging results, particularly age, blood supply, and mammography classification, offer valuable insights to optimize patients\' surgical options and decrease the incidence of malignant outcomes.

OBJECTIVE: To investigate the segmentation approaches for bone metastases in differentiating benign from malignant bone lesions and characterizing malignant bone lesions.
METHODS: The literature search was conducted in Scopus, PubMed, IEEE and MedLine, and Web of Science electronic databases following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A total of 77 original articles, 24 review articles, and 1 comparison paper published between January 2010 and March 2022 were included in the review.
RESULTS: The results showed that most studies used neural network-based approaches (58.44%) and CT-based imaging (50.65%) out of 77 original articles. However, the review highlights the lack of a gold standard for tumor boundaries and the need for manual correction of the segmentation output, which largely explains the absence of clinical translation studies. Moreover, only 19 studies (24.67%) specifically mentioned the feasibility of their proposed methods for use in clinical practice.
CONCLUSIONS: Development of tumor segmentation techniques that combine anatomical information and metabolic activities is encouraging despite not having an optimal tumor segmentation method for all applications or can compensate for all the difficulties built into data limitations.

BACKGROUND: Early diagnosis of prostate cancer improves its prognosis, while it is essential to upgrade screening tools. This study aimed to explore the value of a novel functional magnetic resonance imaging (MRI) technique, namely amide proton transfer (APT)-weighted MRI, combined with serum prostate-specific antigen (PSA) levels to differentiate malignant prostate lesions from benign prostate lesions.
METHODS: Data of patients who underwent prostate examinations at Chongqing University Cancer Hospital between July 2019 and March 2022 were retrospectively analyzed. All patients underwent T2-weighted imaging (T2WI), APT, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI. Two radiologists analyzed the images independently. The ability of the quantitative parameters alone or in different combinations in differentiating malignant prostate lesions from benign prostate lesions were compared by using receiver operating characteristic (ROC) curves. According to the DeLong test, the combined parameters were significantly different from the corresponding single parameter (P < 0.05).
RESULTS: A total of 79 patients were finally enrolled, including 52 patients in the malignant group and 27 patients in the benign group. The separate assessment of indexes revealed that APTmax, APTmean, mean apparent diffusion coefficient (ADCmean), ADCmax, ADCmin, tPAD, free prostate-specific antigen (FPSA), FPSA/total prostate-specific antigen (tPSA), and PSA density (PSAD) were significantly different between the two groups (P < 0.05), while APTmin was not significantly different between the two groups (P > 0.05). APTmax and APTmean had the high values of area under the ROC curve (AUC), which were 0.780 and 0.710, respectively. APTmax had a high sensitivity, and APTmean had a high specificity. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest AUC value (AUC: 0.880, sensitivity: 86.540, specificity: 78.260).
CONCLUSIONS: APTmax, APTmean, ADCmean, ADCmin, tPAD, FPSA, and PSAD showed to have a high value in differentiating malignant prostate lesions from benign prostate lesions in the separate assessment of indexes. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest diagnostic value.