What is the effect of percutaneous cholesistostomy in patients with acute cholecystitis? when is the right time for the procedure?

BACKGROUND: Acute cholecystitis (AC) is one of the most common emergency diseases in surgical practice. Although the gold standard treatment is laparoscopic cholecystectomy, percutaneous cholecystostomy (PC) is performed in some patients due to age, comorbidity, and delays in admission. We aimed to investigate the effect of timing on the clinical process of patients undergoing PC. METHODS: Patients who underwent PC between February 2017 and December 2021 were included in the study. Those who un-derwent PC in the first 72 h were determined as the early PC group, and those who underwent PC after 72 h were determined as the late PC group. Demographic information of the patients, clinical information before drainage, biochemical values of the first 3 days, length of hospital stay, morbidity and mortality in the early and late period after drainage, and elective cholecystectomy information were recorded. These data were compared between the two groups. RESULTS: One hundred and twenty-two patients were included in the study. Early PC was performed in 98 patients (80.3%) and late PC was performed in 24 patients (19.7%). The median follow-up period was 26.6 months (min: 0.25-max: 67) in the early PC group and 26.4 months (min: 0.6-max: 66) in the late PC group (P=0.408). There was no statistically significant difference in mean age, distribu-tion of males and women, concomitant disease, Charlson Comorbidity Index, hepatopancreatobiliary pathology (HPBP), endoscopic retrograde cholangiopancreatography in history and grade (TG18) compared to Tokyo classification (P>0.05). There was no difference between the biochemical parameters (P>0.05). In our study, the median length of hospital stay was 6 (min: 2-max: 36) days in the early PC group, and the median was 9 days (min: 5-max: 20) in the late PC group (P<0.001). A total of 25 patients developed HPBP after PC, 16 of which were AC. There was no statistically significant difference between the early and late PC groups in terms of HPBP develop-ment after PC (P=0.576). There was no statistically significant difference between the early and late PC group in terms of the rate of surgery and type of operation (emergency/elective, open/laparoscopic/conversion, total/subtotal, duration) (P>0.05). CONCLUSION: Discussions about the right timing are ongoing. In our study, we found that patients who underwent early PC had shorter hospital stays. There was no difference between the early and late groups in terms of patient characteristics and severity of AC. PC procedure in AC should be based on algorithms determined by objective data instead of patient-based indications with ran-domized controlled trials.

Diagnostic Performance of AI for Cancers Registered in A Mammography Screening Program: A Retrospective Analysis.

Purpose: To evaluate the performance of an artificial intelligence (AI) algorithm in a simulated screening setting and its effectiveness in detecting missed and interval cancers. Methods: Digital mammograms were collected from Bahcesehir Mammographic Screening Program which is the first organized, population-based, 10-year (2009-2019) screening program in Turkey. In total, 211 mammograms were extracted from the archive of the screening program in this retrospective study. One hundred ten of them were diagnosed as breast cancer (74 screen-detected, 27 interval, 9 missed), 101 of them were negative mammograms with a follow-up for at least 24 months. Cancer detection rates of radiologists in the screening program were compared with an AI system. Three different mammography assessment methods were used: (1) 2 radiologists' assessment at screening center, (2) AI assessment based on the established risk score threshold, (3) a hypothetical radiologist and AI team-up in which AI was considered to be the third reader. Results: Area under curve was 0.853 (95% CI = 0.801-0.905) and the cut-off value for risk score was 34.5% with a sensitivity of 72.8% and a specificity of 88.3% for AI cancer detection in ROC analysis. Cancer detection rates were 67.3% for radiologists, 72.7% for AI, and 83.6% for radiologist and AI team-up. AI detected 72.7% of all cancers on its own, of which 77.5% were screen-detected, 15% were interval cancers, and 7.5% were missed cancers. Conclusion: AI may potentially enhance the capacity of breast cancer screening programs by increasing cancer detection rates and decreasing false-negative evaluations.

Does visceral adiposity have an effect on the survival outcomes of the patients with endometrial cancer?

AIM: Endometrial cancer is the most common cancer of the female reproductive tract in the developed countries. There are many risk factors defined for the development of endometrial cancer, including obesity. We aimed to evaluate the significance of adiposity on the survival outcomes of the patients with endometrial cancer. METHODS: The patients diagnosed with endometrial cancer and underwent surgery between April 2009 and October 2017 were retrospectively reviewed. The visceral adipose tissue and subcutaneous adipose tissue volumes were measured at the level of umbilicus on single-slice magnetic resonance imaging. Visceral adiposity index was calculated. Patients were compared regarding their clinical, demographical, pathologic and survival characteristics. Patients divided into low visceral adiposity (≤0.265, group 1) and high visceral adiposity (>0.265, group 2). RESULTS: A total of 186 patients were included in this retrospective study. There was no significant difference in terms of the demographical, clinical and tumor characteristics of the patients, except age, menopausal status, subcutaneous adipose tissue and visceral adipose tissue. Although no significant difference in progression-free survival and disease-specific survival was noted between groups (P = 0.181), more patients in group 2 died because of endometrial cancer as statistically significant (P = 0.024). Disease-specific survival showed a significant difference between groups according to the log-rank test. CONCLUSION: Visceral adiposity tissue is a significant and reliable prognostic indicator for endometrial cancer prognosis. Women diagnosed with endometrial cancer should be informed about the deleterious effects of visceral adiposity on disease-specific survival.

Comparison between body composition parameters and response to neoadjuvant chemotherapy by using pre-treatment PET CT in locally advanced breast cancer.

PURPOSE: To compare the adipose and muscle tissue areas in patients who responded differently to neoadjuvant chemotherapy. METHODS: One hundred and eighty six patients diagnosed with breast cancer who underwent neoadjuvant chemotherapy between January 2015- October 2019 and were operated after the treatment were retrospectively included in the study. Pathological results were divided into five groups using the Miller-Payne grading systems. Grade 1 indicating no significant reduction in malignant cells; Grade 2: a minor loss of malignant cells (≤ 30 %); Grade 3: reduction in malignant cells between 30 % and 90 %; Grade 4: disappearance of malignant cells >90 %; Grade 5: no malignant cells identifiable. Pre-treatment PET CT scans were evaluated, and calculation of body composition parameters were performed on a single axial section passing through the L3 vertebrae. Spearman's correlation test was used to analyze the correlation between SAT, VAT, MT parameters and pathological responses. RESULTS: There was no strong correlation between the 5 groups separated according to neoadjuvant chemotherapy treatment response and tissue distributions. However, that there was a very low correlation found between superficial adipose tissue and pathological response (r=, 156). CONCLUSION: In conclusion, our results have provided a very low correlation between SAT and more than 30 % response. More research is required to evaluate the role of the body fat and muscle parameters in response to neoadjuvant chemotherapy in larger patient populations.

Diffusion Weighted MR Imaging of Breast and Correlation of Prognostic Factors in Breast Cancer.

BACKGROUND: Through Diffusion Weighted Imaging (DWI), information related to early molecular changes, changes in the permeability of cell membranes, and early morphologic and physiologic changes such as cell swelling can be obtained. AIMS: We investigated the correlation between the prognostic factors of breast cancer and apparent diffusion coefficient (ADC) in DWI sequences of malignant lesions. STUDY DESIGN: Retrospective cross-sectional study. METHODS: Patients who were referred to our clinic between September 2012 and September 2013, who underwent dynamic breast MRI before or after biopsy and whose biopsy results were determined as malignant, were included in our study. Before the dynamic analysis, DWI sequences were taken. ADC relationship with all prognostic factors was investigated. Pearson correlation test was used to compare the numerical data, while Spearman correlation and Fisher exact tests were used to compare the categorical data. The advanced relationships were evaluated with linear regression analysis and univariate analysis. The efficiency of the parameters was evaluated using ROC analysis. The significance level (P) was accepted as 0.05. RESULTS: In total, 41 female patients with an average age of 49.4 years (age interval 21-77) and 44 lesions were included into the study. In the Pearson correlation test, no statistically significant difference was determined between ADC and the patient's age and tumor size. In the Spearman correlation test, a statistically significant difference was determined between nuclear grade (NG) and ADC (r=-0.424, p=0.04); no statistically significant correlation was observed between the other prognostic factors with each other and ADC values. In the linear regression analysis, the relationship of NG with ADC was found to be more significant alone than when comparing all parameters (corrected r2=0.196, p=0.005). Further evaluations between the NG and ADC correlation were carried out with ROC analysis. A statistically significant difference was determined when NG 1 separately was compared with NG 2 and 3 (p=0.03). A statistically significant difference was also determined (p=0.05) in the comparison of NG 1 with only NG 3. No statistically significant difference was determined when NG 2 separately was compared with NG 1 and NG 3 and when NG 3 separately was compared with NG 1 and 2 (p=0.431, p=0.097). CONCLUSION: We found that ADC values obtained by breast DWI showed a higher correlation with the NG of breast cancer, which is an important factor in the patient's treatment. Predictions can be made about NG by analyzing the ADC values. Additional studies are needed, however, and the ADC value of the lesion can be used as a prognostic factor proving the aggressiveness.