The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide for selecting and integrating AI solutions, focusing on interpretative tasks that require the active involvement of radiologists. Our approach is not to list available applications or review scientific evidence, as this information is readily available in previous studies; instead, we concentrate on the essential factors radiology departments must consider when choosing AI solutions. These factors include clinical relevance, performance and validation, implementation and integration, clinical usability, costs and return on investment, and regulations, security, and privacy. We illustrate each factor with hypothetical scenarios to provide a clearer understanding and practical relevance. Through our experience and literature review, we provide insights and a practical roadmap for radiologists to navigate the complex landscape of AI in radiology. We aim to assist in making informed decisions that enhance diagnostic precision, improve patient outcomes, and streamline workflows, thus contributing to the advancement of radiological practices and patient care.

Background: A valid measure to describe the most important needs and concerns of people with life-threatening illnesses is missing in Cyprus. Our aim was to adapt and test the cross-cultural validity and responsiveness of the Integrated Palliative care Outcome Scale (IPOS) in a cohort of Turkish speaking cancer patients. Methods: The IPOS (English) patient-reported measure was translated into Turkish following published guidelines including, 2 independent forward, 2 independent blind backward translations, expert panel review by 7 members and field testing with 11 cognitive interviews (5 patients and 6 specialists) and final approval of the copyright holder. Consecutive cancer patients (n = 234) seen by the community palliative care services were recruited from Help Those with Cancer Society (KHYD); of those 82 were followed-up. The instrument was administered by personal interview. Confirmatory Factor Analysis was used to validate the factor structure of Turkish IPOS. Internal consistency reliability of the subscales was evaluated by Cronbach’s alpha and Intraclass Correlation Coefficient respectively. Validity was assessed by calculating Pearson’s correlation coefficient (r) between Turkish IPOS scores and Turkish version of EQ-5D-3L - a validated generic measure of health status developed by the EuroQol Group. Results: Turkish IPOS is conceptually and semantically equivalent to the English version and linguistically valid. The CFA was inconclusive for the three factor structure due to low sample size, as the SRMR and CFI tests only approached the defined minimums warranting further investigation. There were low levels of missing values, and no ceiling or floor effects. The Physical (α = 0.91) and the Social and Quality of Care Issues (α = 0.75) sub-scales showed good internal consistencies, however Emotional sub-scale showed poor internal consistency (α = 0.64). The reliability of the Physical (ICC = 0.51, 0.45–0.56 95% CI) and Social Quality of Care Issues (ICC = 0.50, 0.42–0.57 95% CI) were moderate. Poor internal consistency (α =0.64) and reliability (ICC = 0.31, 0.24–0.39, 95% CI) was obtained for Emotional Subscale. Construct validity was evidenced through significant correlations in the predicted directions and strength with EQ-5D. Turkish IPOS showed higher needs and concerns in participants at more advanced stages than those at earlier stages of cancer. The standardized response mean (SRM) of − 0.94 suggested large internal responsiveness to clinical change. Conclusion: Turkish IPOS is a clear, relevant, acceptable measure and responsive to the needs and concerns of cancer patients, observing regional differences, it may have implications for use in other Turkish speaking communities. Future studies are needed to clarify the factor structure, assess its external responsiveness and to improve the properties of its Emotional subscale.

Aim: This study aimed to assess the predictive role of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and mean platelet volume, on catheter survival in chronic hemodialysis patients, analyzing both infectious and non-infectious complications. Methods: A retrospective analysis encompassed 1279 tunneled catheter insertion procedures involving 902 patients between March 2014 and October 2018. Patients were categorized into two main groups: (i) initial placement and (ii) exchange. The exchange group was further stratified into four subgroups: infection, dysfunction, displacement, and transitioning temporary hemodialysis catheters to long-term ones. Hematologic ratios were calculated from baseline hemogram data, including neutrophil, lymphocyte, monocyte, and platelet counts, while mean platelet volume was derived from the same hemogram. Results: The patients in the exchange group displayed significantly higher lymphocyte and monocyte values ( p < 0.001), while lower values were noted for neutrophil–lymphocyte ratio and platelet-lymphocyte ratio ( p < 0.001). The transition group displayed higher monocyte values and lower mean platelet volume and lymphocyte-monocyte ratio values ( p < 0.05). In the infection-related exchange subgroup, higher neutrophil count, mean platelet volume, neutrophil–lymphocyte ratio, and platelet-lymphocyte ratio values were observed compared to other groups ( p < 0.05). Cases related to catheter dysfunction exhibited increased lymphocyte-monocyte ratio but lower neutrophil, monocyte, neutrophil–lymphocyte ratio, and platelet-lymphocyte ratio values ( p < 0.05). Conclusion: This study highlights the interest of specific inflammatory markers, particularly monocytes, neutrophil–lymphocyte ratio, and platelet-lymphocyte ratio, in the management of tunneled catheters, notably in patients undergoing exchanges. However, cut-off values, essential for constructing management algorithms, are currently lacking, and prospective multicenter studies are needed for further elucidation. Graphical

Background: Magnetic resonance imaging (MRI) has a superior sensitivity for the diagnosis of breast cancer, leading to lesions primarily detected by MRI. Some of these lesions cannot be identified by targeted second-look ultrasound (SLUS) examinations and are thus referred to as MRI-only lesions. We hypothesize that biologically more aggressive cancers lead to more distinct tissue damage improving visibility on SLUS. Objective: To investigate whether there are differences in cancer subtypes between MRI-only and SLUS-detected malignant lesions. Methods: This retrospective single-center observational study evaluated 435 patients who received breast MRI examinations between January 2017 and December 2022, with at least one lesion primarily detected on MRI and histologically confirmed as malignant. Demographic characteristics, lesion type (mass or non-mass), MRI-assessed lesion size (mm), histological diagnosis, stage, immunohistochemical analysis (ER, PR, HER-2, Ki-67), and lymph node status were assessed and compared between MRI-only and SLUS-detected. Results: Among 435 patients (mean age of 57.4 +/- 13.3), 34.02 % (n = 148) were in the MRI-only group, while the remaining 65.98 % (n = 287) were identified by SLUS. MRI-only cases were significantly smaller in size (10 mm vs 20 mm), mostly staged as T1 (66.9 %) and showed features associated with less biological aggressiveness (higher pure ductal carcinoma in situ rates: 30.4 % vs 5.2 %; lower Ki-67, median values: 10 vs 20) compared to SLUS-detected cases (P < 0.001). SLUS-detected cancers had higher ratios of microscopic (4.9 % vs 3.4 %) and macroscopic axillary metastasis (26.8 % vs 7.4 %) compared to MRI-only lesions (P < 0.001). Conclusion: MRI-only lesions presented histologically and immunohistochemically with less aggressive patterns compared to those detected via SLUS.

Background and Objectives: Cachexia is a systemic wasting syndrome associated with poor outcomes in chronic diseases, including heart failure (HF). Although the cachexia index (CXI), which integrates skeletal muscle mass, serum albumin, and the neutrophil-to-lymphocyte ratio, has shown prognostic value in oncology, its clinical significance in HF remains poorly defined. Materials and Methods: This retrospective single-center cohort study evaluated a selected subgroup of adults hospitalized with decompensated heart failure between January 2020 and January 2025 who had undergone abdominal computed tomography within the preceding 6 months, enabling CT-based body composition assessment. Skeletal muscle index was measured at the L3 vertebral level, and CXI was calculated as (SMI × serum albumin)/neutrophil-to-lymphocyte ratio. Patients were followed for all-cause mortality and HF-related rehospitalizations. Results: A total of 127 patients were included (mean age 70.45 ± 12.73 years; 51.2% male). CXI showed excellent discrimination for mortality (AUC 0.951; 95% CI 0.905–0.996), with an optimal cut-off value of <20.87. Patients with low CXI had significantly higher all-cause mortality (80.5% vs. 4.7%, p < 0.001) and more HF-related hospitalizations [4 (3–5) vs. 0.5 (0–1), p < 0.001] than those with high CXI. Conclusions: In patients hospitalized with decompensated HF, low CXI was strongly associated with all-cause mortality and recurrent hospitalization, suggesting that CXI may serve as an integrative prognostic marker in this population.