Post-printing processing and aging effects on Polyjet materials intended for the fabrication of advanced surgical simulators.

Material Jetting (MJ) 3D printing technology is promising for the fabrication of highly realistic surgical simulators, however, the changes in the mechanical properties of MJ materials after post-printing treatments and over time remain quite unknown. In this study, we investigate the effect of different post-printing processes and aging on the mechanical properties of a white opaque and rigid MJ photopolymer, a white flexible MJ photopolymer and on a combination of them. Tensile and Shore hardness tests were conducted on homogeneous 3D-printed specimens: two different post-printing procedures for support removal (dry and water) and further surface treatment (with glycerol solution) were compared. The specimens were tested within 48 h from printing and after aging (30-180 days) in a controlled environment. All groups of specimens treated with different post-printing processes (dry, water, glycerol) exhibited a statistically significant difference in mechanical properties (i.e. elongation at break, elastic modulus, ultimate tensile strength). Particularly, the treatment with glycerol makes the flexible photopolymer more rigid, but then with aging the initial elongation of the material tends to be restored. For the rigid photopolymer, an increase in deformability was observed as a major effect of aging. The hardness tests on the printed specimens highlighted a significant overestimation of the Shore values declared by the manufacturer. The study findings are useful for guiding the material selection and post-printing processing techniques to manufacture realistic and durable models for surgical training.

Morpho-functional analysis of the temporomandibular joint following mandible-first bimaxillary surgery with mandible-only patient-specific implants.

The aim of this study was to evaluate condylar and glenoid fossa remodeling after bimaxillary orthognathic surgery guided by patient-specific mandibular implants. In total, 18 patients suffering from dentofacial dysmorphism underwent a virtually planned bimaxillary mandibular PSI-guided orthognathic procedure. One month prior to surgery, patients underwent a CBCT scan and optical scans of the dental arches; these datasets were re-acquired 1 month and at least 9 months postsurgery. Three-dimensional models of the condyles, glenoid fossae, and interarticular surface space (IASS) were obtained and compared to evaluate the roto-translational positional discrepancy and surface variation of each condyle and glenoid fossa, and the IASS variation. The condylar position varied by an average of 4.31° and 2.18 mm, mainly due to surgically unavoidable ramus position correction. Condylar resorption remodeling was minimal (average ≤ 0.1 mm), and affected skeletal class III patients the most. Later condylar remodeling was positively correlated with patient age. No significant glenoid fossa remodeling was observed. No postoperative orofacial pain was recorded at clinical follow-up. The procedure was accurate in minimizing the shift in relationship between the bony components of the TMJ and their remodeling, and was effective in avoiding postoperative onset of orofacial pain. An increase in sample size, however, would be useful to confirm our findings.

Dissecting human anatomy learning process through anatomical education with augmented reality: AEducAR 2.0, an updated interdisciplinary study.

Anatomical education is pivotal for medical students, and innovative technologies like augmented reality (AR) are transforming the field. This study aimed to enhance the interactive features of the AEducAR prototype, an AR tool developed by the University of Bologna, and explore its impact on human anatomy learning process in 130 second-year medical students at the International School of Medicine and Surgery of the University of Bologna. An interdisciplinary team of anatomists, maxillofacial surgeons, biomedical engineers, and educational scientists collaborated to ensure a comprehensive understanding of the study's objectives. Students used the updated version of AEducAR, named AEducAR 2.0, to study three anatomical topics, specifically the orbit zone, facial bones, and mimic muscles. AEducAR 2.0 offered two learning activities: one explorative and one interactive. Following each activity, students took a test to assess learning outcomes. Students also completed an anonymous questionnaire to provide background information and offer their perceptions of the activity. Additionally, 10 students participated in interviews for further insights. The results demonstrated that AEducAR 2.0 effectively facilitated learning and students' engagement. Students totalized high scores in both quizzes and declared to have appreciated the interactive features that were implemented. Moreover, interviews shed light on the interesting topic of blended learning. In particular, the present study suggests that incorporating AR into medical education alongside traditional methods might prove advantageous for students' academic and future professional endeavors. In this light, this study contributes to the growing research emphasizing the potential role of AR in shaping the future of medical education.

Registration Sanity Check for AR-guided Surgical Interventions: Experience From Head and Face Surgery.

Achieving and maintaining proper image registration accuracy is an open challenge of image-guided surgery. This work explores and assesses the efficacy of a registration sanity check method for augmented reality-guided navigation (AR-RSC), based on the visual inspection of virtual 3D models of landmarks. We analyze the AR-RSC sensitivity and specificity by recruiting 36 subjects to assess the registration accuracy of a set of 114 AR images generated from camera images acquired during an AR-guided orthognathic intervention. Translational or rotational errors of known magnitude up to ±1.5 mm/±15.5°, were artificially added to the image set in order to simulate different registration errors. This study analyses the performance of AR-RSC when varying (1) the virtual models selected for misalignment evaluation (e. g., the model of brackets, incisor teeth, and gingival margins in our experiment), (2) the type (translation/rotation) of registration error, and (3) the level of user experience in using AR technologies. Results show that: 1) the sensitivity and specificity of the AR-RSC depends on the virtual models (globally, a median true positive rate of up to 79.2% was reached with brackets, and a median true negative rate of up to 64.3% with incisor teeth), 2) there are error components that are more difficult to identify visually, 3) the level of user experience does not affect the method. In conclusion, the proposed AR-RSC, tested also in the operating room, could represent an efficient method to monitor and optimize the registration accuracy during the intervention, but special attention should be paid to the selection of the AR data chosen for the visual inspection of the registration accuracy.

Augmented reality for orthopedic and maxillofacial oncological surgery: a systematic review focusing on both clinical and technical aspects.

This systematic review offers an overview on clinical and technical aspects of augmented reality (AR) applications in orthopedic and maxillofacial oncological surgery. The review also provides a summary of the included articles with objectives and major findings for both specialties. The search was conducted on PubMed/Medline and Scopus databases and returned on 31 May 2023. All articles of the last 10 years found by keywords augmented reality, mixed reality, maxillofacial oncology and orthopedic oncology were considered in this study. For orthopedic oncology, a total of 93 articles were found and only 9 articles were selected following the defined inclusion criteria. These articles were subclassified further based on study type, AR display type, registration/tracking modality and involved anatomical region. Similarly, out of 958 articles on maxillofacial oncology, 27 articles were selected for this review and categorized further in the same manner. The main outcomes reported for both specialties are related to registration error (i.e., how the virtual objects displayed in AR appear in the wrong position relative to the real environment) and surgical accuracy (i.e., resection error) obtained under AR navigation. However, meta-analysis on these outcomes was not possible due to data heterogenicity. Despite having certain limitations related to the still immature technology, we believe that AR is a viable tool to be used in oncological surgeries of orthopedic and maxillofacial field, especially if it is integrated with an external navigation system to improve accuracy. It is emphasized further to conduct more research and pre-clinical testing before the wide adoption of AR in clinical settings.

Pretreatment Tumor Volume and Tumor Sphericity as Prognostic Factors in Patients with Oral Cavity Squamous Cell Carcinoma: A Prospective Clinical Study in 95 Patients.

The prognostic impact of tumor volume and tumor sphericity was analyzed in 95 patients affected by oral cancer. The pre-operative computed tomography (CT) scans were used to segment the tumor mass with threshold tools, obtaining the corresponding volume and sphericity. Events of recurrence and tumor-related death were detected for each patient. The mean follow-up time was 31 months. A p-value of 0.05 was adopted. Mean tumor volume resulted higher in patients with recurrence or tumor-related death at the Student's t-test (respectively, 19.8 cm3 vs. 11.1 cm3, p = 0.03; 23.3 cm3 vs. 11.7 cm3, p = 0.02). Mean tumor sphericity was higher in disease-free patients (0.65 vs. 0.59, p = 0.04). Recurrence-free survival and disease-specific survival were greater for patients with a tumor volume inferior to the cut-off values of 21.1 cm3 (72 vs. 21 months, p < 0.01) and 22.4 cm3 (85 vs. 32 months, p < 0.01). Recurrence-free survival and disease-specific survival were higher for patients with a tumor sphericity superior to the cut-off value of 0.57 (respectively, 49 vs. 33 months, p < 0.01; 56 vs. 51 months, p = 0.01). To conclude, tumor volume and sphericity, three-dimensional parameters, could add useful information for better stratification of prognosis in oral cancer.

Preclinical Application of Augmented Reality in Pediatric Craniofacial Surgery: An Accuracy Study.

BACKGROUND: Augmented reality (AR) allows the overlapping and integration of virtual information with the real environment. The camera of the AR device reads the object and integrates the virtual data. It has been widely applied to medical and surgical sciences in recent years and has the potential to enhance intraoperative navigation. MATERIALS AND METHODS: In this study, the authors aim to assess the accuracy of AR guidance when using the commercial HoloLens 2 head-mounted display (HMD) in pediatric craniofacial surgery. The Authors selected fronto-orbital remodeling (FOR) as the procedure to test (specifically, frontal osteotomy and nasal osteotomy were considered). Six people (three surgeons and three engineers) were recruited to perform the osteotomies on a 3D printed stereolithographic model under the guidance of AR. By means of calibrated CAD/CAM cutting guides with different grooves, the authors measured the accuracy of the osteotomies that were performed. We tested accuracy levels of ±1.5 mm, ±1 mm, and ±0.5 mm. RESULTS: With the HoloLens 2, the majority of the individuals involved were able to successfully trace the trajectories of the frontal and nasal osteotomies with an accuracy level of ±1.5 mm. Additionally, 80% were able to achieve an accuracy level of ±1 mm when performing a nasal osteotomy, and 52% were able to achieve an accuracy level of ±1 mm when performing a frontal osteotomy, while 61% were able to achieve an accuracy level of ±0.5 mm when performing a nasal osteotomy, and 33% were able to achieve an accuracy level of ±0.5 mm when performing a frontal osteotomy. CONCLUSIONS: despite this being an in vitro study, the authors reported encouraging results for the prospective use of AR on actual patients.

First Ex Vivo Animal Study of a Biological Heart Valve Prosthesis Sensorized with Intravalvular Impedance.

IntraValvular Impedance (IVI) sensing is an innovative concept for monitoring heart valve prostheses after implant. We recently demonstrated IVI sensing feasible in vitro for biological heart valves (BHVs). In this study, for the first time, we investigate ex vivo the IVI sensing applied to a BHV when it is surrounded by biological tissue, similar to a real implant condition. A commercial model of BHV was sensorized with three miniaturized electrodes embedded in the commissures of the valve leaflets and connected to an external impedance measurement unit. To perform ex vivo animal tests, the sensorized BHV was implanted in the aortic position of an explanted porcine heart, which was connected to a cardiac BioSimulator platform. The IVI signal was recorded in different dynamic cardiac conditions reproduced with the BioSimulator, varying the cardiac cycle rate and the stroke volume. For each condition, the maximum percent variation in the IVI signal was evaluated and compared. The IVI signal was also processed to calculate its first derivative (dIVI/dt), which should reflect the rate of the valve leaflets opening/closing. The results demonstrated that the IVI signal is well detectable when the sensorized BHV is surrounded by biological tissue, maintaining the similar increasing/decreasing trend that was found during in vitro experiments. The signal can also be informative on the rate of valve opening/closing, as indicated by the changes in dIVI/dt in different dynamic cardiac conditions.

Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer.

BACKGROUND: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC). METHOD: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor's zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification. RESULTS: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17. CONCLUSIONS: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models.

Assessment of a novel patient-specific 3D printed multi-material simulator for endoscopic sinus surgery.

Background: Three-dimensional (3D) printing is an emerging tool in the creation of anatomical models for surgical training. Its use in endoscopic sinus surgery (ESS) has been limited because of the difficulty in replicating the anatomical details. Aim: To describe the development of a patient-specific 3D printed multi-material simulator for use in ESS, and to validate it as a training tool among a group of residents and experts in ear-nose-throat (ENT) surgery. Methods: Advanced material jetting 3D printing technology was used to produce both soft tissues and bony structures of the simulator to increase anatomical realism and tactile feedback of the model. A total of 3 ENT residents and 9 ENT specialists were recruited to perform both non-destructive tasks and ESS steps on the model. The anatomical fidelity and the usefulness of the simulator in ESS training were evaluated through specific questionnaires. Results: The tasks were accomplished by 100% of participants and the survey showed overall high scores both for anatomy fidelity and usefulness in training. Dacryocystorhinostomy, medial antrostomy, and turbinectomy were rated as accurately replicable on the simulator by 75% of participants. Positive scores were obtained also for ethmoidectomy and DRAF procedures, while the replication of sphenoidotomy received neutral ratings by half of the participants. Conclusion: This study demonstrates that a 3D printed multi-material model of the sino-nasal anatomy can be generated with a high level of anatomical accuracy and haptic response. This technology has the potential to be useful in surgical training as an alternative or complementary tool to cadaveric dissection.

Application of Augmented Reality to Maxillary Resections: A Three-Dimensional Approach to Maxillofacial Oncologic Surgery.

In the relevant global context, although virtual reality, augmented reality, and mixed reality have been emerging methodologies for several years, only now have technological and scientific advances made them suitable for revolutionizing clinical care and medical settings through the provision of advanced features and improved healthcare services. Over the past fifteen years, tools and applications using augmented reality (AR) have been designed and tested in the context of various surgical and medical disciplines, including maxillofacial surgery. The purpose of this paper is to show how a marker-less AR guidance system using the Microsoft® HoloLens 2 can be applied in mandible and maxillary demolition surgery to guide maxillary osteotomies. We describe three mandibular and maxillary oncologic resections performed during 2021 using AR support. In these three patients, we applied a marker-less tracking method based on recognition of the patient's facial profile. The surgeon, using HoloLens 2 smart glasses, could see the virtual surgical planning superimposed on the patient's anatomy. We showed that performing osteotomies under AR guidance is feasible and viable, as demonstrated by comparison with osteotomies performed using CAD-CAM cutting guides. This technology has advantages and disadvantages. However, further research is needed to improve the stability and robustness of the marker-less tracking method applied to patient face recognition.

3D renal model for surgical planning of partial nephrectomy: A way to improve surgical outcomes.

Objective: to evaluate the impact of 3D model for a comprehensive assessment of surgical planning and quality of partial nephrectomy (PN). Materials and methods: 195 patients with cT1-T2 renal mass scheduled for PN were enrolled in two groups: Study Group (n= 100), including patients referred to PN with revision of both 2D computed tomography (CT) imaging and 3D model; Control group (n= 95), including patients referred to PN with revision of 2D CT imaging. Overall, 20 individuals were switched to radical nephrectomy (RN). The primary outcome was the impact of 3D models-based surgical planning on Trifecta achievement (defined as the contemporary absence of positive surgical margin, major complications and ≤30% postoperative eGFR reduction). The secondary outcome was the impact of 3D models on surgical planning of PN. Multivariate logistic regressions were used to identify predictors of selective clamping and Trifecta's achievement in patients treated with PN (n=175). Results: Overall, 73 (80.2%) patients in Study group and 53 (63.1%) patients in Control group achieved the Trifecta (p=0.01). The preoperative plan of arterial clamping was recorded as clampless, main artery and selective in 22 (24.2%), 22 (24.2%) and 47 (51.6%) cases in Study group vs. 31 (36.9%), 46 (54.8%) and 7 (8.3%) cases in Control group, respectively (p<0.001). At multivariate logistic regressions, the use of 3D model was found to be independent predictor of both selective or super-selective clamping and Trifecta's achievement. Conclusion: 3D-guided approach to PN increase the adoption of selective clamping and better predict the achievement of Trifecta.

Innovative IntraValvular Impedance Sensing Applied to Biological Heart Valve Prostheses: Design and In Vitro Evaluation.

Subclinical valve thrombosis in heart valve prostheses is characterized by the progressive reduction in leaflet motion detectable with advanced imaging diagnostics. However, without routine imaging surveillance, this subclinical thrombosis may be underdiagnosed. We recently proposed the novel concept of a sensorized heart valve prosthesis based on electrical impedance measurement (IntraValvular Impedance, IVI) using miniaturized electrodes embedded in the valve structure to generate a local electric field that is altered by the cyclic movement of the leaflets. In this study, we investigated the feasibility of the novel IVI-sensing concept applied to biological heart valves (BHVs). Three proof-of-concept prototypes of sensorized BHVs were assembled with different size, geometry and positioning of the electrodes to identify the optimal IVI-measurement configuration. Each prototype was tested in vitro on a hydrodynamic heart valve assessment platform. IVI signal was closely related to the electrodes' positioning in the valve structure and showed greater sensitivity in the prototype with small electrodes embedded in the valve commissures. The novel concept of IVI sensing is feasible on BHVs and has great potential for monitoring the valve condition after implant, allowing for early detection of subclinical valve thrombosis and timely selection of an appropriate anticoagulation therapy.

AEducaAR, Anatomical Education in Augmented Reality: A Pilot Experience of an Innovative Educational Tool Combining AR Technology and 3D Printing.

Gross anatomy knowledge is an essential element for medical students in their education, and nowadays, cadaver-based instruction represents the main instructional tool able to provide three-dimensional (3D) and topographical comprehensions. The aim of the study was to develop and test a prototype of an innovative tool for medical education in human anatomy based on the combination of augmented reality (AR) technology and a tangible 3D printed model that can be explored and manipulated by trainees, thus favoring a three-dimensional and topographical learning approach. After development of the tool, called AEducaAR (Anatomical Education with Augmented Reality), it was tested and evaluated by 62 second-year degree medical students attending the human anatomy course at the International School of Medicine and Surgery of the University of Bologna. Students were divided into two groups: AEducaAR-based learning ("AEducaAR group") was compared to standard learning using human anatomy atlas ("Control group"). Both groups performed an objective test and an anonymous questionnaire. In the objective test, the results showed no significant difference between the two learning methods; instead, in the questionnaire, students showed enthusiasm and interest for the new tool and highlighted its training potentiality in open-ended comments. Therefore, the presented AEducaAR tool, once implemented, may contribute to enhancing students' motivation for learning, increasing long-term memory retention and 3D comprehension of anatomical structures. Moreover, this new tool might help medical students to approach to innovative medical devices and technologies useful in their future careers.

3D Patient-Specific Virtual Models for Presurgical Planning in Patients with Recto-Sigmoid Endometriosis Nodules: A Pilot Study.

Background and Objective: In recent years, 3D printing has been used to support surgical planning or to guide intraoperative procedures in various surgical specialties. An improvement in surgical planning for recto-sigmoid endometriosis (RSE) excision might reduce the high complication rate related to this challenging surgery. The aim of this study was to build novel presurgical 3D models of RSE nodules from magnetic resonance imaging (MRI) and compare them with intraoperative findings. Materials and Methods: A single-center, observational, prospective, cohort, pilot study was performed by enrolling consecutive symptomatic women scheduled for minimally invasive surgery for RSE between November 2019 and June 2020 at our institution. Preoperative MRI were used for building 3D models of RSE nodules and surrounding pelvic organs. 3D models were examined during multi-disciplinary preoperative planning, focusing especially on three domains: degree of bowel stenosis, nodule's circumferential extension, and bowel angulation induced by the RSE nodule. After surgery, the surgeon was asked to subjectively evaluate the correlation of the 3D model with the intra-operative findings and to express his evaluation as "no correlation", "low correlation", or "high correlation" referring to the three described domains. Results: seven women were enrolled and 3D anatomical virtual models of RSE nodules and surrounding pelvic organs were generated. In all cases, surgeons reported a subjective "high correlation" with the surgical findings. Conclusion: Presurgical 3D models could be a feasible and useful tool to support surgical planning in women with recto-sigmoidal endometriotic involvement, appearing closely related to intraoperative findings.

Novel Volumetric and Morphological Parameters Derived from Three-dimensional Virtual Modeling to Improve Comprehension of Tumor's Anatomy in Patients with Renal Cancer.

BACKGROUND: Three-dimensional (3D) models improve the comprehension of renal anatomy. OBJECTIVE: To evaluate the impact of novel 3D-derived parameters, to predict surgical outcomes after robot-assisted partial nephrectomy (RAPN). DESIGN, SETTING, AND PARTICIPANTS: Sixty-nine patients with cT1-T2 renal mass scheduled for RAPN were included. Three-dimensional virtual modeling was achieved from computed tomography. The following volumetric and morphological 3D parameters were calculated: VT (volume of the tumor); VT/VK (ratio between tumor volume and kidney volume); CSA3D (ie, contact surface area); UCS3D (contact to the urinary collecting system); Tumor-Artery3D: tumor's blood supply by tertiary segmental arteries (score = 1), secondary segmental artery (score = 2), or primary segmental/main renal artery (scoren = 3); ST (tumor's sphericity); ConvT (tumor's convexity); and Endophyticity3D (ratio between the CSA3D and the global tumor surface). INTERVENTION: RAPN with a 3D model. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Three-dimensional parameters were compared between patients with and without complications. Univariate logistic regression was used to predict overall complications and type of clamping; linear regression was used to predict operative time, warm ischemia time, and estimated blood loss. RESULTS AND LIMITATIONS: Overall, 11 (15%) individuals experienced overall complications (7.2% had Clavien ≥3 complications). Patients with urinary collecting system (UCS) involvement at 3D model (UCS3D = 2), tumor with blood supply by primary or secondary segmentary arteries (Tumor-Artery3D = 1 and 2), and high Endophyticity3D values had significantly higher rates of overall complications (all p ≤ 0.03). At univariate analysis, UCS3D, Tumor-Artery3D, and Endophyticity3D are significantly associated with overall complications; CSA3D and Endophyticity3D were associated with warm ischemia time; and CSA3D was associated with selective clamping (all p ≤ 0.03). Sample size and the lack of interobserver variability are the main limits. CONCLUSIONS: Three-dimensional modeling provides novel volumetric and morphological parameters to predict surgical outcomes after RAPN. PATIENT SUMMARY: Novel morphological and volumetric parameters can be derived from a three-dimensional model to describe surgical complexity of renal mass and to predict surgical outcomes after robot-assisted partial nephrectomy.

Improving total body irradiation with a dedicated couch and 3D-printed patient-specific lung blocks: A feasibility study.

Introduction: Total body irradiation (TBI) is an important component of the conditioning regimen in patients undergoing hematopoietic stem cell transplants. TBI is used in very few patients and therefore it is generally delivered with standard linear accelerators (LINACs) and not with dedicated devices. Severe pulmonary toxicity is the most common adverse effect after TBI, and patient-specific lead blocks are used to reduce mean lung dose. In this context, online treatment setup is crucial to achieve precise positioning of the lung blocks. Therefore, in this study we aim to report our experience at generating 3D-printed patient-specific lung blocks and coupling a dedicated couch (with an integrated onboard image device) with a modern LINAC for TBI treatment. Material and methods: TBI was planned and delivered (2Gy/fraction given twice a day, over 3 days) to 15 patients. Online images, to be compared with planned digitally reconstructed radiographies, were acquired with the couch-dedicated Electronic Portal Imaging Device (EPID) panel and imported in the iView software using a homemade Graphical User Interface (GUI). In vivo dosimetry, using Metal-Oxide Field-Effect Transistors (MOSFETs), was used to assess the setup reproducibility in both supine and prone positions. Results: 3D printing of lung blocks was feasible for all planned patients using a stereolithography 3D printer with a build volume of 14.5×14.5×17.5 cm3. The number of required pre-TBI EPID-images generally decreases after the first fraction. In patient-specific quality assurance, the difference between measured and calculated dose was generally<2%. The MOSFET measurements reproducibility along each treatment and patient was 2.7%, in average. Conclusion: The TBI technique was successfully implemented, demonstrating that our approach is feasible, flexible, and cost-effective. The use of 3D-printed patient-specific lung blocks have the potential to personalize TBI treatment and to refine the shape of the blocks before delivery, making them extremely versatile.

Interpreting nephrometry scores with three-dimensional virtual modelling for better planning of robotic partial nephrectomy and predicting complications.

OBJECTIVE: 3D models are increasingly used as additional preoperative tools for renal surgery. We aim to evaluate the impact of 3D renal models in the assessment of PADUA, RENAL, Contact Surface Area (CSA) and Arterial Based Complexity (ABC) for the prediction of complications after Robot assisted Partial Nephrectomy (RAPN). METHODS AND MATERIALS: Overall, 57 patients with T1 and 1 patient with T2 renal mass referred to RAPN, were prospectively enrolled. 3D virtual modelling was obtained from 2D computed tomography (CT). Two radiologists recorded PADUA2D, RENAL2D, CSA2D and ABC2D by evaluation of 2D images; two bioengineers recorded PADUA3D, RENAL3D, CSA3D and ABC3D by evaluation of the 3D model, using MeshMixer software. To evaluate the concordance between 2D and 3D nephrometry scores, Cohen's j coefficient was calculated. Receiver-operating characteristic (ROC) curves were generated to evaluate the accuracy of 3D and 2D nephrometry scores to predict overall complications. Finally, the impact of 3D model on clamping approach during RAPN was compared to 2D imaging. RESULTS: PADUA3D, RENAL3D, CSA3D and ABC3D scores had a significant different distribution compared to PADUA2D, RENAL2D, CSA2D and ABC2D (all p≤0.03). 2D nephrometry scores may be unchanged, reduced or increased after assessment by 3D models: CSA3D, PADUA3D, RENAL3D and ABC3D were reduced in14%, 26%, 29% and 16% and increased in 16%, 36%, 38% and 29% of cases, respectively. At ROC curve analysis, PADUA3D, RENAL3D and ABC3D showed were significantly better accuracy to predict complications compared to PADUA2D, RENAL2D and ABC2D. PADUA3D (OR: 1.66), RENAL3D (OR: 1.69) and ABC3D (OR: 2.44) revealed a significant correlation with postoperative complications (all P ≤0.03). CONCLUSION: Nephrometry scores calculated via 3D models predict complications after RAPN with higher accuracy than conventional 2D imaging.

The Use of Augmented Reality to Guide the Intraoperative Frozen Section During Robot-assisted Radical Prostatectomy.

BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) can guide the surgical plan during robot-assisted radical prostatectomy (RARP), and intraoperative frozen section (IFS) can facilitate real-time surgical margin assessment. OBJECTIVE: To assess a novel technique of IFS targeted to the index lesion by using augmented reality three-dimensional (AR-3D) models in patients scheduled for nerve-sparing RARP (NS-RARP). DESIGN, SETTING, AND PARTICIPANTS: Between March 2019 and July 2019, 20 consecutive prostate cancer patients underwent NS-RARP with IFS directed to the index lesion with the help of AR-3D models (study group). Control group consists of 20 patients matched with 1:1 propensity score for age, clinical stage, Prostate Imaging Reporting and Data System score v2, International Society of Urological Pathology grade, prostate volume, NS approach, and prostate-specific antigen in which RARP was performed by cognitive assessment of mpMRI. SURGICAL PROCEDURE: In the study group, an AR-3D model was superimposed to the surgical field to guide the surgical dissection. Tissue sampling for IFS was taken in the area in which the index lesion was projected by AR-3D guidance. MEASUREMENTS: Chi-square test, Student t test, and Mann-Whitney U test were used to compare, respectively, proportions, means, and medians between the two groups. RESULTS AND LIMITATIONS: Patients in the AR-3D group had comparable preoperative characteristics and those undergoing the NS approach were referred to as the control group (all p ≥ 0.06). Overall, positive surgical margin (PSM) rates were comparable between the two groups; PSMs at the level of the index lesion were significantly lower in patients referred to AR-3D guided IFS to the index lesion (5%) than those in the control group (20%; p = 0.01). CONCLUSIONS: The novel technique of AR-3D guidance for IFS analysis may allow for reducing PSMs at the level of the index lesion. PATIENT SUMMARY: Augmented reality three-dimensional guidance for intraoperative frozen section analysis during robot-assisted radical prostatectomy facilitates the real-time assessment of surgical margins and may reduce positive surgical margins at the index lesion.

A Novel Non-Invasive Device for the Assessment of Central Venous Pressure in Hospital, Office and Home.

BACKGROUND: Venous congestion can be quantified by central venous pressure (CVP) and its monitoring is crucial to understand and follow the hemodynamic status of patients with cardio-respiratory diseases. The standard technique for CVP measurement is invasive, requiring the insertion of a catheter into a jugular vein, with potential complications. On the other hand, the current non-invasive methods, mainly based on ultrasounds, remain operator-dependent and are unsuitable for use in the home environment. In this paper, we will introduce a novel, non-invasive device for the hospital, office and home assessment of CVP. METHODS: After describing the measurement concept, we will report a preliminary experimental study enrolling 5 voluntary healthy subjects to evaluate the VenCoM measurements' repeatability, and the system's capability in measuring small elicited venous pressure variations (2 mmHg), as well as an induced venous hypertension within a pathological range (12÷20 mmHg). RESULTS: The experimental measurements showed a repeatability of ±1mmHg. The VenCoM device was able to reliably detect the elicited venous pressure variations and the simulated congestive status. DISCUSSION AND CONCLUSION: The proposed non-invasive VenCoM device is able to provide a fast and repeatable CVP estimate, having a wide spectrum of potential clinical applications, including the monitoring of venous congestion in heart failure patients and in subjects with renal and hepatic dysfunction, as well as pulmonary hypertension (PH) that can be extended to pneumonia COVID-19 patients even after recovery. The device needs to be tested further on a large sample size of both healthy and pathological subjects, to systematically validate its reliability and impact in clinical setting.