Aims/Background Growth hormone (GH) supplementation contributes to improved reproductive and pregnancy outcomes in in vitro fertilization (IVF)-embryo transfer (ET) in polycystic ovary syndrome (PCOS) women. This study aimed to explore the effects of GH on the oxidative stress, ovarian reactivity, and pregnancy outcomes of IVF-ET in PCOS patients of different ages. Methods The clinical data of 342 women with PCOS undergoing in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET) were collected for retrospective analysis. Based on age, patients were divided into three groups: <35 years (n = 118), 35-40 years (n = 120), and >40 years (n = 104). Each age group was further subdivided into a GH subgroup and a control subgroup, according to whether GH was supplemented during ovarian stimulation. Ovarian stimulation parameters and IVF/ICSI-ET outcomes were recorded. Levels of malondialdehyde (MDA) and superoxide dismutase (SOD) in both follicular fluid and serum were measured using commercial assay kits. Results In the 35-40 years group, the total number of oocytes retrieved, metaphase II (MII) oocytes, and ovarian sensitivity index (OSI) were significantly higher in the GH group compared to the control group (p = 0.012, 0.049, 0.006, respectively). In the >40 years group, the total number of oocytes retrieved and OSI were also significantly increased in the GH group compared to the control group (p = 0.001, 0.002, respectively). In the <35, 35-40, and >40 years groups, the serum SOD level on the trigger day was significantly higher in the GH groups than in the control groups (p = 0.004, 0.001, 0.012, respectively), while the serum MDA level was significantly lower (p = 0.032, 0.015, 0.004, respectively). In the 35-40 and >40 years groups, the fertilization rate was significantly higher in the GH subgroups compared to the control subgroups (p = 0.040, 0.001, respectively). A total of 43 ET cycles were cancelled, and 299 ET cycles were analyzed. In the 35-40 years group, the GH subgroup showed a significantly higher pregnancy rate compared to the control subgroup (p = 0.043); although the live birth rate was slightly higher, the difference was not statistically significant (p = 0.064). In the <35 years and >40 years groups, no significant differences were observed in pregnancy rate, miscarriage rate, or live birth rate between the GH and control subgroups (p > 0.05). Conclusion GH improves serum oxidative stress and ovarian reactivity in women with PCOS, and increases both the number of oocytes retrieved and the fertilization rate in those aged ≥35 years. Additionally, GH increases the pregnancy rate in PCOS patients aged 35-40 years, although it does not show a significant benefit in live birth rate.

Aims/Background Acute myeloid leukemia (AML) is a hematologic malignancy that often requires prolonged hospitalization and intensive treatment, leading to substantial psychological distress and impaired quality of life (QoL). The positive psychology-based PERMA (positive emotion, engagement, relationships, meaning, and accomplishment) model encompasses five dimensions and has demonstrated benefits in various chronic diseases, though evidence in AML remains limited. This study aims to investigate the effects of PERMA model-based nursing on psychological well-being and QoL in hospitalized AML patients. Methods We conducted a single-center, retrospective case-control study of 555 AML inpatients admitted between March 2022 and March 2025. Patients received either PERMA model-based nursing (PERMA group) or conventional nursing (control group). Propensity score matching (PSM; 1:1; caliper = 0.2) was applied to balance baseline characteristics, resulting in 242 matched patients (121 per group). Psychological status was assessed using the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS), and QoL was evaluated using the Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ‑C30). Results After matching, baseline characteristics were comparable across the two groups. In the control group, SAS scores increased significantly (p = 0.001) while SDS scores showed a slight decrease. Scores of global health status-quality of life (GHS-QoL), physical functioning (PF), emotional functioning (EF), and social functioning (SF) declined markedly (all p < 0.001); nausea/vomiting (NV) and appetite loss (AP) increased, diarrhea (DI) decreased, and financial difficulties (FI) increased significantly. In the PERMA group, SAS and SDS scores decreased significantly (both p < 0.001), PF declined (p < 0.001), role functioning (RF) improved (p = 0.024), while fatigue (FA), NV, AP, and FI all increased significantly. At discharge, the PERMA group recorded significantly lower SAS and SDS scores and higher GHS-QoL, EF, and SF scores than the control group (p < 0.01). Conclusion PERMA model-based nursing significantly alleviated anxiety and depression and improved key QoL domains in hospitalized AML patients. This structured, low-cost intervention is feasible in clinical practice and merits further validation in multicenter prospective studies.

The global cancer burden is increasing, with disproportionate morbidity and mortality in low- and middle-income countries. Imaging is essential for cancer diagnosis, staging, and follow-up, yet access in these settings remains poor. Barriers include insufficient availability of appropriate equipment, shortages of trained personnel, limited interventional services, and socioeconomic constraints. This review examines these barriers and challenges in global access to imaging for common cancers such as breast, lung, prostate, and hepatocellular carcinoma. Potential solutions are discussed, including innovations such as fit-for-purpose imaging hardware, artificial intelligence-assisted image interpretation, and governmental, policy, and international initiatives aimed at improving cancer imaging access in low- and middle-income countries. Keywords: Multimodal Applications, CT, Ultrasound, MRI, Artificial Intelligence, PET/CT © RSNA, 2025.

Purpose To evaluate an MRI-based strategy for quantifying intra- and peritumoral heterogeneity (ITH and PTH) in hepatocellular carcinoma (HCC) and develop ITH- and PTH-based models for diagnosing microvascular invasion (MVI) and stratifying prognostic risk. Materials and Methods Patients with HCC (≤5 cm) were retrospectively included from three different institutions from March 2012 to September 2023 and divided into internal training, internal testing, and external testing cohorts. Tumor and peritumoral tissues in MR images were categorized into distinct habitats using unsupervised clustering algorithms. High-throughput radiomic features were extracted from each habitat. The degree of feature variation within each habitat was quantified to derive characteristics representing ITH and PTH. Engineered features were developed to train machine learning models for MVI diagnosis. Kaplan-Meier survival curves and Cox regression analysis were used for survival analysis. Results A total of 432 patients (mean age, 54.31 years ± 11.15 [SD]; 371 male) were included. The TH_DNN model, constructed using ITH- and PTH-based quantitative features combined with a deep neural network (DNN), demonstrated the best predictive performance for MVI across the three datasets (area under the receiver operating characteristic curve range = 0.82-0.99). The subgroup predicted as MVI positive with the TH_DNN model exhibited a poorer prognosis than the MVI-negative subgroup. In terms of overall survival and postoperative recurrence, the hazard ratios for MVI diagnosis were 2.79 (95% CI: 1.35, 5.75; P = .006) and 2.17 (95% CI: 1.38, 3.43; P < .001), respectively. Conclusion This study developed a strategy for quantifying ITH and PTH, which was valuable for noninvasive and accurate identification of MVI and prognostic risk in patients with HCC. Keywords: Liver, MRI, Oncology, Hepatocellular Carcinoma, Microvascular Invasion, Tumor habitat, Intratumoral Heterogeneity, Peritumoral Heterogeneity Supplemental material is available for this article. © The Author(s) 2025. Published by the Radiological Society of North America under a CC BY 4.0 license.

Purpose To evaluate predictors of mammography engagement at the county level to better understand the challenges associated with population-based screening in the United States. Materials and Methods This retrospective, geospatial, cross-sectional study conducted from March 2024 to September 2024 used data from the 2023 National Cancer Institute's Small Area Estimates, County Health Rankings, and the Atlas of Rural and Small-Town America. Univariable linear regression analyses were conducted to evaluate the relationship between sociodemographic variables and county-level mammography screening rates. Multivariable linear regression was performed to create an average model of mammography screening rates as a function of county-level sociodemographic variables, which was then used to assess county screening performance after adjusting for these factors. Results Information obtained from 3121 counties was included in this study. Higher percentages of White residents, residents older than 18 years, women, rural residents, and high school graduates were positively associated with county-level screening rates, while higher percentages of non-Black minority residents, residents with limited English proficiency, and uninsured residents were negatively associated with county-level mammography screening rates (P < .001). After accounting for sociodemographic composition, counties with a higher proportion of Black residents (P < .001), residents with limited English proficiency (P = .009), insured residents (P < .001), high school graduates (P < .001), and residents with higher median income (P < .001) exceeded expected screening rates based on national county-level data. Conclusion In this national county-level model, population-based characteristics associated with mammography engagement at the county level could be used to estimate expected screening rates based on each county's sociodemographic profile. Keywords: Mammography, Breast, Screening, Socioeconomic Issues, Oncology, Epidemiology, Statistics, Health Policy and Practice ©RSNA, 2025.

Despite diagnostic advancements in India, the scarcity of Indian polycystic ovary syndrome (PCOS) data and varied diagnostic standards contribute to delays in PCOS detection, particularly in rural areas.

We aim to build a predictive model based on an extensive dataset derived from Indian studies and perform risk-based stratification of samples.

The PubMed database was queried for studies focused on the pathophysiology of PCOS in Indian women. Based on inclusion and exclusion criteria, six studies were selected. Corresponding clinical data was statistically synthesised based on study-specific baseline characteristics. The integrated dataset consisted of 11,258 samples (nPCOS = 7342; nControl = 3916) with 14 attributes: disease (PCOS vs control), age, body mass index, cholesterol, triglycerides, high-density and low-density lipoproteins, LH, FSH, testosterone, menarche age, systolic and diastolic blood pressure, and yearly menstrual cycles. After data pre-processing, missing values imputation, and feature engineering, model benchmarking was conducted using LazyPredict. LightGBM was selected for further hyperparameter tuning based on performance metrics. Lastly, feature importance analysis was performed, and predictive probabilities were utilised to categorise samples into different risk categories.

The optimised LightGBM model achieved 96.18% accuracy, 97.51% precision, 96.65% recall, and 99.31% receiver operating characteristic area under curve (ROC-AUC) score. Further, testosterone, menstrual cycles per year, triglycerides, LH, and diastolic blood pressure were the top five key attributes in PCOS. Risk categorisation of samples demonstrated substantial alignment with real diagnoses, validating the model's clinical significance.

This study introduces the first comprehensively synthesised PCOS dataset for Indian women.

Our framework facilitates prompt risk detection, providing an adaptable methodology for decision-making in PCOS management.

To describe patterns of skin checks for potential skin cancers in general practice and subsequent skin-related healthcare, and the associated costs.

Retrospective longitudinal health record linkage.

Patient encounters between 2010 and 2017 were extracted from clinical information systems at 73 general practice sites in Victoria, Australia, including Medicare billing information, from the MedicineInsight primary care dataset. The main outcomes were skin checks, skin-related healthcare up to 3 months after the skin check, and health system costs.

There were 59 046 skin check encounters (0.7% of all general practice encounters) identified for 40 014 people with a median age of 52 years (interquartile range 36-67). Of these people, 26% had multiple skin checks. Of the subsequent skin checks, 28% were within 3 months of the initial skin check and 15% were after > 2 years. There was subsequent skin-related healthcare ≤ 3 months after 20% of all skin checks: 8% had a skin biopsy, 11% had a skin excision (of which 2% indicated a melanoma diagnosis, 29% keratinocyte carcinoma and 68% benign or other skin lesion), 2% had skin-related medicine prescribed and 5% had other skin-related treatment such as cryotherapy (not mutually exclusive). Ninety per cent of skin checks were billed as general practitioner (GP) consultations, including 65% as GP consultations of < 20 minutes although the proportion of longer consultations increased over time. The mean 3-month skin-related general practice health system costs for people without and with subsequent skin-related healthcare were A$58 and A$240, respectively, and up to a mean of A$595 for those having a melanoma excised.

Skin checks for potential skin cancers occur frequently in Australian general practice and accumulate substantial health system costs, with one in five skin checks resulting in subsequent treatment. This study adds to scarce real-world skin check and cost data in Australia.

The justification for the research was the economic approach to breast cancer in order to introduce improvements. The objectives were to know the final cost in each subgroup of women with non-metastatic breast cancer, to know the average cost per patient, to predict the cost and to identify groups with the greatest economic impact for health systems.

A retrospective descriptive study was carried out in 411 women, after systematic random sampling, diagnosed with non-metastatic breast cancer and undergoing surgery in Abente y Lago Hospital (A Coruña) during 2010-2013. The information was obtained from medical records and databases. For cost evaluation, rates for health services in the Galician Health Service were taken into account. Univariates and multivariates analysis were performed.

The average cost of non-metastatic breast cancer in women was €23,752.16±€16,015.82 and varied according to ten care profiles based on therapeutic management (p<0.001 in six of the profiles in relation to non-adjuvant surgery; in one, p=0.004; in one, p=0.022; not demonstrable in one with p=0.132). In the profiles with immunotherapy (14.6%) the cost was €54,190.54; €55,238; €69,278.45 and €57,364.81.

In non-metastatic breast cancer, ten care profiles according to therapeutic management best approximate the cost. In addition to having the average cost, the cost per patient can be predicted with a mathematical formula that includes age, origin of screening, infiltrated nodes and care profile. The groups with anti-HER2 treatment have a greater economic impact.

The incidence and prognosis of high-grade gliomas differ according to histopathological and molecular features. The WHO 2021 CNS classification emphasized IDH status, but historical cohorts often lacked systematic molecular profiling.

We conducted a retrospective population-based study including adult patients diagnosed with IDH-wildtype glioblastoma or IDH-mutant astrocytoma in a Spanish tertiary center (2011-2021). Incidence trends and survival outcomes were analyzed according to treatment modality and sex.

A total of 1057 patients were included: 530 (50.1%) with IDH-wildtype glioblastoma and 137 (13%) with IDH-mutant astrocytoma. Incidence of both subtypes significantly increased during the study period (p < 0.01). Median overall survival (OS) was 12.3 months for IDH-wildtype glioblastoma and 38.4 months for IDH-mutant astrocytoma. Multimodal therapy (surgery, radiotherapy, chemotherapy) significantly improved OS and progression-free survival (PFS) in both subgroups (p < 0.001). Male sex was associated with longer OS in both tumor types (p < 0.05).

IDH-wildtype glioblastoma shows persistently poor outcomes despite increasing incidence, while IDH-mutant astrocytoma demonstrates better survival, particularly in male patients and those receiving multimodal therapy. These findings reflect real-world practice and provide epidemiological and survival data from Southern Europe to guide future clinical and public health strategies.

Background/Objectives: Sentinel lymph node biopsy (SLNB) is currently the standard approach for axillary staging in breast cancer. Conventional techniques are radioisotope-based (Technetium-99m, Tc99m) and remain widely used, but novel tracers like Indocyanine Green (ICG) fluorescence provide potential advantages regarding feasibility and logistics. Methods: We conducted a prospective, observational study including 476 female patients diagnosed with primary invasive breast cancer who underwent SLNB at the Institute of Oncology "Prof. Dr. I. Chiricuță", Cluj-Napoca, Romania, between January 2022 and May 2025. Clinical, surgical, and pathological variables were systematically extracted. SLNB was performed using either Tc99m or ICG, according to institutional protocols. Comparative analyses were performed to evaluate sentinel node characteristics, histopathological parameters, and positive surgical margins predictors. Results: The median age was 60 years (IQR: 52-69). Breast-conserving surgery (BCS) was performed in 77.9% of cases, while mastectomy was performed in 22.1%. Sentinel lymph node positivity was reported in 25.6% of cases, with no significant differences in the number of excised or metastatic nodes between Tc99m and ICG (mean nodes: 3.23 vs. 3.20, p = 0.860; mean positive nodes: 0.35 vs. 0.36, p = 0.897). Histologically, invasive carcinoma NST was predominant (90.1%), and surgical margins were negative in 96.8% of patients, with all margin-positive cases occurring following BCS. No pathological markers (grade, Ki67, TILs, DCIS extent) predicted margin status or nodal involvement. Notably, younger age correlated inversely with the extent of ductal carcinoma in situ (r = -0.21, p < 0.00001). Conclusions: Tc99m and ICG provided comparable diagnostic performance in performing SLNB, with equivalent rates of nodal detection and pathological yield. These findings support that ICG is a safe and effective alternative for routine axillary staging in breast cancer.