3D printing and reverse engineering are innovative technologies that are revolutionizing scientific research in the health sciences and related clinical practice. Such technologies are able to improve the development of various custom-made medical devices while also lowering design and production costs. Recent advances allow the printing of particularly complex prototypes whose geometry is drawn from precise computer models designed on in vivo imaging data. This review summarizes a new method for histological sample processing (applicable to e.g., the brain, prostate, liver, and renal mass) which employs a personalized mold developed from diagnostic images through computer-aided design software and 3D printing. Through positioning the custom mold in a coherent manner with respect to the organ of interest (as delineated by in vivo imaging data), the cutting instrument can be precisely guided in order to obtain blocks of tissue which correspond with high accuracy to the slices imaged. This approach appeared crucial for validation of new quantitative imaging tools, for an accurate imaging-histopathological correlation and for the assessment of radiogenomic features extracted from oncological lesions. The aim of this review is to define and describe 3D printing technologies which are applicable to oncological assessment and slicer design, highlighting the radiological and pathological perspective as well as recent applications of this approach for the histological validation of and correlation with MR images.
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http://dx.doi.org/10.1155/2019/1071453 | DOI Listing |
Front Artif Intell
January 2025
Department of Rehabilitation Medicine, The First Affiliated Hospital of Shenzhen University, The Second People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
Background: The Department of Rehabilitation Medicine is key to improving patients' quality of life. Driven by chronic diseases and an aging population, there is a need to enhance the efficiency and resource allocation of outpatient facilities. This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models.
View Article and Find Full Text PDFUrol Oncol
January 2025
Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
Introduction: The American Urology Association (AUA) recently introduced in their guidelines a subtype-agnostic, 4-tiered risk classification score to assess oncologic outcomes after surgery in patients with localized renal cell carcinoma (RCC). We provide a head-to-head comparison of the AUA score with 3, internationally validated and EAU recommended, histological-specific models.
Materials And Methods: We retrieved from a prospectively-maintained database 2,560 surgically-treated patients with localized RCC in a single high-volume European center (1987-2023).
J Craniomaxillofac Surg
January 2025
Digital Technology Center, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China. Electronic address:
Objectives: This study aimed to evaluate the anthropometric accuracy of 3D face reconstruction based on neural networks (3DFRBN) using 2D images, including the assessment of global errors and landmarks, as well as linear and angular measurements.
Methods: Thirty healthy volunteers were recruited in this study. For each volunteer, five standard photos were taken, capturing anterior, 45° to left and right, and 90° to left and right views.
Neurosurgery
January 2025
Service de Neurochirurgie, GHU-Paris Psychiatrie et Neurosciences, Paris, France.
Background And Objectives: The risk-to-benefit ratio of transopercular awake resection for recurrent insular diffuse gliomas is poorly studied. We assessed feasibility, safety, and efficacy of awake surgical resection of recurrent insular diffuse gliomas in patients with previous treatments (resection and/or radiotherapy and/or chemotherapy and/or combination).
Methods: Observational, retrospective, single-institution cohort analysis (2010-2023) of 123 consecutive adult patients operated on for an insular diffuse glioma (2021 World Health Organization classification) under awake conditions.
Int J Gynecol Cancer
January 2025
Nazionale dei Tumori di Milano, Fondazione IRCCS Istituto Gynecological Oncology Unit, Milan, Italy.
Objective: Endometrial cancers can be classified into 4 molecular sub-groups: (1) POLE mutated (POLEmut), (2) mismatch repair deficiency/microsatellite-instable (MMRd/MSI-H), (3) TP53-mutant or p53 abnormal (p53abn), and (4) no specific mutational profile (NSMP). Although molecular classification is increasingly applied in oncology, its role in guiding fertility-sparing treatments for endometrial cancer remains unclear. This study examines the prognostic role of molecular classification in fertility-sparing treatment and its potential to guide treatment decisions.
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