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It is prospective study conducted over a two-year period (February 2022 to January 2024) at the Diagnostic and Interventional Radiology Department of our institution. The study was approved by the research ethics committee of the Radiology Department of the Faculty of Medicine Mansoura University (Reference number of approval: MD.22.03.626) and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent to participate in this study. Clinical trial number: not applicable. Throughout the study, strict polices were taken to ensure the confidentiality and privacy of patient data.

Thirty-four patients with histologically confirmed EC were enrolled in this study. Participants were included in the study if they were 18 years of age or older and provided written informed consent. All participants had a histologically confirmed diagnosis of endometrial carcinoma. Participants were excluded if they presented with contraindications to MRI (including cochlear implants, cardiac pacemakers, metallic stents, claustrophobia, or morbid obesity), a diagnosis of endometrial stromal sarcoma, or a history of neoadjuvant chemotherapy or radiotherapy.

All participants underwent non-contrast MRI, encompassing DWI and IVIM sequences. Histopathological diagnosis of the neoplastic lesions served as the reference standard for the study’s findings.

Two radiologists with 7 and 14 years of experience, respectively, interpreted the images using a consensus reading approach.

All patients were subject to MRI examinations using a 1.5 Tesla Siemens Symphony scanner with an abdominal coil positioned around the pelvis. Prior to the examination, patients were instructed to Abstain from food and drink for 4–6 h and maintain a comfortably full bladder.

Conventional MRI

MRI imaging T2 Fast-Spin Echo (FSE) Weighted Imaging (TR/TE, 4000–6000/100–110 ms) in two planes: Sagittal and Axial (short axis upon the endometrial cavity), Axial STIR and T1 WI sequences were acquired using a TR of 400–600 ms (ms) and an TE of 10–14 ms. The field of view (FOV) was 38 × 26 cm², with 5 mm slice thickness, 1 mm interslice gap, and 24 slices acquired.

Diffusion weighted imaging and ADC value

DWI was carried out through a multi-section single-shot spin-echo sequence with b-values of 0, 400 and 800 s/mm². Diffusion gradients were applied in three orthogonal directions. The imaging parameters were: TR/TE = 7000/77 ms, matrix size = 128 × 128 with same slice thickness, interslice gap, and field of view.

Initial DWI evaluation consisted of interpretation of signal intensity within the endometrial mass. Restricted diffusion was identified by a hyperintense signal on the b-800 image and a corresponding low signal on the ADC map.

ADC maps were automatically produced, followed by manual segmentation of regions of interest (ROIs) on areas of maximum restriction of tumoral tissue with careful exclusion of areas showing necrosis, cystic changes, or hemorrhage. Necrotic areas were avoided during ROI placement by using the anatomical images as a guide. ROI sizes ranged from 1 to 2.5 cm². The final parametric values were derived from the mean measurements across all ROIs. The inter-reader agreement between the two radiologists was substantial (Cohen’s κ = 0.82, p < 0.001).

Intravoxel incoherent motion

Ten-b-value DWI sequence was acquired including (0, 30, 70, 100, 200, 400, 800, 1000, 1500, and 2000 mm²/s).

Regions of interest (ROIs) were consistently delineated on ADC maps and then applied to the equivalent IVIM maps. A biexponential model was used to calculate D, D*, and f. Color maps were generated from the IVIM model and were overlaid on anatomical reference images, with a continuous color scale ranging from low values (blue) to high values (red). D represents the true diffusivity of water molecules within the extracellular space, reflecting tissue microstructure; the color bar on the side indicates the D values, where blue represents lower diffusivity and red represents higher diffusivity. D* reflects the motion of blood water within the capillary network. The perfusion fraction (f) quantifies the proportion of tissue occupied by perfused blood Color maps of the perfusion fraction (f, %) were generated from the IVIM biexponential fitting model. These maps display the fractional volume of microvascular blood flow within each voxel. A continuous color scale was applied, with blue representing low f values and red representing high f values, as indicated by the accompanying scale bar. ROIs were drawn over the solid portion of the tumor on the f maps, referencing anatomical images to avoid necrotic or cystic regions, and mean values were recorded for statistical analysis.”

Histopathological analysis

Twenty-seven cases were candidates for total abdominal hysterectomy and bilateral salpingo-oophrectomy underwent full post-surgical histopathological analysis to determine tumor type, However the other seven cases were shifted to chemoradiotherapy following D and C only for the extensive spread of the disease beyond the pelvic cavity (four case) or due to the age and general condition of the patient (three cases).

Statistical analysis

Data were analyzed using SPSS version 15 for Windows®. Frequencies and percentages described categorical variables, with group comparisons performed using Chi-square tests. Quantitative data normality was assessed via the Kolmogorov–Smirnov test. Normally distributed data are reported as means ± standard deviations, while non-normally distributed data are presented as medians and ranges (minimum–maximum). The Mann–Whitney U test was employed for non-parametric group comparisons. A p-value < 0.05 was considered statistically significant.

The third BBVA Spark Summit in Barcelona brought together more than 350 ecosystem leaders, over half from startups, and 45 venture capital funds from eight countries. The event has become a key venue for matching talent, capital and innovation, and for showcasing Catalonia as one of Europe’s leading tech hubs.

During his dialogue, Torres Vila said BBVA’s push to deploy AI across the organization is helping it differentiate the customer experience, support bankers, manage risk, develop software and streamline processes.

He added that AI has sped up how the bank designs and rolls out processes and applications, and noted BBVA’s large AI operations “factory” for automation and software development, which lifts efficiency and lets teams focus on higher‑value work. He added that analytics and ready access to data are essential to make these models work and to translate them into better services and processes for customers.

BBVA Spark reaffirmed its backing for innovative entrepreneurship, calling it vital to regional economic development. In its three years of operation, the unit has attracted 1,700 customers and channeled more than €750 million in working‑capital and long‑term financing. BBVA has also invested over €900 million in private‑equity funds that support startups and technology‑based companies worldwide.

The BBVA Chair praised entrepreneurs, saying success stems from passion, a focus on value‑based impact, and the courage and conviction to build something great. BBVA Spark has a London‑based team covering Europe, and offices in Madrid, Barcelona, Mexico City, Bogota and Buenos Aires.

The collaboration brings together IUCN’s global scientific expertise and APRIL’s operational reach in Indonesia to generate robust conservation science, expand the use of conservation tools in APRIL’s conservation and restoration landscapes, and build capacity that supports national and international biodiversity goals.

A key focus of the collaboration is the expansion of IUCN’s Red List of Ecosystems (RLE), one of the world’s most important indicators of ecosystem health under the Global Biodiversity Framework. This will contribute to a Global RLE Peatlands Assessment, aiming to provide stronger evidence to guide the conservation of this critical ecosystem and important global carbon sink. 

The collaboration will also pilot the IUCN RHINO approach for Rapid, High-Integrity Nature-positive Outcomes within APRIL’s operations, including its 150,693-hectare Restorasi Ekosistem Riau (RER) forest conservation and restoration programme, located on Sumatra’s Kampar Peninsula.

The collaboration will evaluate and provide strategic guidance on ways to further enhance APRIL’s biodiversity conservation and restoration programmes, while generating practical lessons for the wider forestry and land-use sector on how they can measure, improve, and share progress on biodiversity outcomes.

“The world is running out of time to reverse biodiversity loss, and science must guide every step we take,” said Dr Grethel Aguilar, IUCN Director General. “This collaboration with APRIL allows us to scale up the Red List of Ecosystems and test new approaches like IUCN RHINO in real-world scenarios. By combining IUCN’s science with APRIL’s operational reach in Indonesia, we can turn data into action and create a sustainable model for how business and conservation can work together to meet global biodiversity targets.“

The collaboration further provides a unique opportunity for IUCN to strengthen its work with its Indonesian members and conservation actors, catalysing on-the-ground action at scale. As part of the collaboration, IUCN will deepen engagement with a range of stakeholders in Indonesia, contributing to the advancement of national efforts to conserve and restore biodiversity with strong integration of the perspectives of communities and experts in Indonesia.

“For us, conservation is about taking practical action. Businesses today are expected to move beyond pledges and deliver results that are credible, practical and measurable on the ground. Our collaboration with IUCN strengthens APRIL’s science-based approach to landscape management and accelerates delivery of our APRIL2030 commitments. By combining global science with local action, this partnership enhances our conservation and restoration programmes and engages a wider network of experts and stakeholders to achieve meaningful biodiversity outcomes,” said Anderson Tanoto, Managing Director at RGE and member of the Executive Committee at APRIL.

The IUCN–APRIL collaboration supports the delivery of the Global Biodiversity Framework, demonstrating how private sector engagement can align with international conservation priorities.

By fostering resilience in ecosystems, strengthening community engagement, and advancing biodiversity science, the partnership represents APRIL’s commitment to collaborate with IUCN represents a concrete step toward fostering resilience in ecosystems and communities while supporting global biodiversity targets.