3D printing in medicine: current applications and future directions

Technical developments in medical imaging techniques have led to significant improvements in the diagnostic performance of less-invasive imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), nuclear medicine and ultrasound. Quantitative analysis of these imaging modalities allows for detection and diagnosis of various diseases with high accuracy (1-10). Despite promising results available in the literature, traditional two-dimensional (2D) and three-dimensional (3D) visualization tools are still limited to a 2D screen, which affect realistic visualization of anatomical structures and pathologies of 3D datasets, and this is particularly apparent when dealing with complex pathologies. This has created potential opportunities for the use of 3D printing technique in medical applications

A systematic review of clinical value of three-dimensional printing in renal disease

The aim of this systematic review is to analyse current literature related to the clinical value of three-dimensional (3D) printed models in renal disease. A literature search of PubMed and Scopus databases was performed to identify studies reporting the clinical application and usefulness of 3D printed models in renal disease. Fifteen studies were found to meet the selection criteria and were included in the analysis. Eight of them provided quantitative assessments with five studies focusing on dimensional accuracy of 3D printed models in replicating renal anatomy and tumour, and on measuring tumour volume between 3D printed models and original source images and surgical specimens, with mean difference less than 10%. The other three studies reported that the use of 3D printed models significantly enhanced medical students and specialists’ ability to identify anatomical structures when compared to two-dimensional (2D) images alone; and significantly shortened intraoperative ultrasound duration compared to without use of 3D printed models. Seven studies provided qualitative assessments of the usefulness of 3D printed kidney models with findings showing that 3D printed models improved patient’s understanding of renal anatomy and pathology; improved medical trainees’ understanding of renal malignant tumours when compared to viewing medical images alone; and assisted surgical planning and simulation of renal surgical procedures with significant reductions of intraoperative complications. The cost and time associated with 3D printed kidney model production was reported in 10 studies, with costs ranging from USD$100 to USD$1,000, and duration of 3D printing production up to 31 h. The entire process of 3D printing could take up to a few days. This review shows that 3D printed kidney models are accurate in delineating renal anatomical structures and renal tumours with high accuracy. Patient-specific 3D printed models serve as a useful tool in preoperative planning and simulation of surgical procedures for treatment of renal tumours. Further studies with inclusion of more cases and with a focus on reducing the cost and 3D model production time deserve to be investigated

VI-RADS for bladder cancer: current applications and future developments

Bladder cancer (BCa) is among the ten most frequent cancers globally. It is the tumor with the highest lifetime treatment-associated costs, and among the tumors with the heaviest impacts on postoperative quality of life. The purpose of this article is to review the current applications and future perspectives of the Vesical Imaging Reporting and Data System (VI-RADS). VI-RADS is a newly developed scoring system aimed at standardization of MRI acquisition, interpretation, and reporting for BCa. An insight will be given on the BCa natural history, current MRI applications for local BCa staging with assessment of muscle invasiveness, and clinical implications of the score for disease management. Future applications include risk stratification of nonmuscle invasive BCa, surveillance, and prediction and monitoring of therapy response. Level of Evidence: 3. Technical Efficacy Stage: 2

DDR2 controls breast tumor stiffness and metastasis by regulating integrin mediated mechanotransduction in CAFs

Biomechanical changes in the tumor microenvironment influence tumor progression and metastases. Collagen content and fiber organization within the tumor stroma are major contributors to biomechanical changes (e., tumor stiffness) and correlated with tumor aggressiveness and outcome. What signals and in what cells control collagen organization within the tumors, and how, is not fully understood. We show in mouse breast tumors that the action of the collagen receptor DDR2 in CAFs controls tumor stiffness by reorganizing collagen fibers specifically at the tumor-stromal boundary. These changes were associated with lung metastases. The action of DDR2 in mouse and human CAFs, and tumors in vivo, was found to influence mechanotransduction by controlling full collagen-binding integrin activation via Rap1-mediated Talin1 and Kindlin2 recruitment. The action of DDR2 in tumor CAFs is thus critical for remodeling collagen fibers at the tumor-stromal boundary to generate a physically permissive tumor microenvironment for tumor cell invasion and metastases

Semiautomated 3D liver segmentation using computed tomography and magnetic resonance imaging

Le foie est un organe vital ayant une capacité de régénération exceptionnelle et un rôle crucial dans le fonctionnement de l’organisme. L’évaluation du volume du foie est un outil important pouvant être utilisé comme marqueur biologique de sévérité de maladies hépatiques. La volumétrie du foie est indiquée avant les hépatectomies majeures, l’embolisation de la veine porte et la transplantation. La méthode la plus répandue sur la base d'examens de tomodensitométrie (TDM) et d'imagerie par résonance magnétique (IRM) consiste à délimiter le contour du foie sur plusieurs coupes consécutives, un processus appelé la «segmentation». Nous présentons la conception et la stratégie de validation pour une méthode de segmentation semi-automatisée développée à notre institution. Notre méthode représente une approche basée sur un modèle utilisant l’interpolation variationnelle de forme ainsi que l’optimisation de maillages de Laplace. La méthode a été conçue afin d’être compatible avec la TDM ainsi que l' IRM. Nous avons évalué la répétabilité, la fiabilité ainsi que l’efficacité de notre méthode semi-automatisée de segmentation avec deux études transversales conçues rétrospectivement. Les résultats de nos études de validation suggèrent que la méthode de segmentation confère une fiabilité et répétabilité comparables à la segmentation manuelle. De plus, cette méthode diminue de façon significative le temps d’interaction, la rendant ainsi adaptée à la pratique clinique courante. D’autres études pourraient incorporer la volumétrie afin de déterminer des marqueurs biologiques de maladie hépatique basés sur le volume tels que la présence de stéatose, de fer, ou encore la mesure de fibrose par unité de volume.The liver is a vital abdominal organ known for its remarkable regenerative capacity and fundamental role in organism viability. Assessment of liver volume is an important tool which physicians use as a biomarker of disease severity. Liver volumetry is clinically indicated prior to major hepatectomy, portal vein embolization and transplantation. The most popular method to determine liver volume from computed tomography (CT) and magnetic resonance imaging (MRI) examinations involves contouring the liver on consecutive imaging slices, a process called “segmentation”. Segmentation can be performed either manually or in an automated fashion. We present the design concept and validation strategy for an innovative semiautomated liver segmentation method developed at our institution. Our method represents a model-based approach using variational shape interpolation and Laplacian mesh optimization techniques. It is independent of training data, requires limited user interactions and is robust to a variety of pathological cases. Further, it was designed for compatibility with both CT and MRI examinations. We evaluated the repeatability, agreement and efficiency of our semiautomated method in two retrospective cross-sectional studies. The results of our validation studies suggest that semiautomated liver segmentation can provide strong agreement and repeatability when compared to manual segmentation. Further, segmentation automation significantly shortens interaction time, thus making it suitable for daily clinical practice. Future studies may incorporate liver volumetry to determine volume-averaged biomarkers of liver disease, such as such as fat, iron or fibrosis measurements per unit volume. Segmental volumetry could also be assessed based on subsegmentation of vascular anatomy

Diseases of the Abdomen and Pelvis 2018-2021: Diagnostic Imaging - IDKD Book

Gastrointestinal disease; PET/CT; Radiology; X-ray; IDKD; Davo

Innovations, challenges, and minimal information for standardization of humanized mice

Mice xenotransplanted with human cells and/or expressing human gene products (also known as humanized mice ) recapitulate the human evolutionary specialization and diversity of genotypic and phenotypic traits. These models can provide a relevant in vivo context for understanding of human-specific physiology and pathologies. Humanized mice have advanced toward mainstream preclinical models and are now at the forefront of biomedical research. Here, we considered innovations and challenges regarding the reconstitution of human immunity and human tissues, modeling of human infections and cancer, and the use of humanized mice for testing drugs or regenerative therapy products. As the number of publications exploring different facets of humanized mouse models has steadily increased in past years, it is becoming evident that standardized reporting is needed in the field. Therefore, an international community-driven resource called Minimal Information for Standardization of Humanized Mice (MISHUM) has been created for the purpose of enhancing rigor and reproducibility of studies in the field. Within MISHUM, we propose comprehensive guidelines for reporting critical information generated using humanized mice

Innovations, challenges, and minimal information for standardization of humanized mice.

Mice xenotransplanted with human cells and/or expressing human gene products (also known as "humanized mice") recapitulate the human evolutionary specialization and diversity of genotypic and phenotypic traits. These models can provide a relevant in vivo context for understanding of human-specific physiology and pathologies. Humanized mice have advanced toward mainstream preclinical models and are now at the forefront of biomedical research. Here, we considered innovations and challenges regarding the reconstitution of human immunity and human tissues, modeling of human infections and cancer, and the use of humanized mice for testing drugs or regenerative therapy products. As the number of publications exploring different facets of humanized mouse models has steadily increased in past years, it is becoming evident that standardized reporting is needed in the field. Therefore, an international community-driven resource called "Minimal Information for Standardization of Humanized Mice" (MISHUM) has been created for the purpose of enhancing rigor and reproducibility of studies in the field. Within MISHUM, we propose comprehensive guidelines for reporting critical information generated using humanized mice

Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC.

BACKGROUND: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. METHODS: A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds. RESULTS/CONCLUSIONS: Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified