Optimizing anterior urethral stricture assessment: leveraging AI-assisted three-dimensional sonourethrography in clinical practice.

PURPOSE: This investigation sought to validate the clinical precision and practical applicability of AI-enhanced three-dimensional sonographic imaging for the identification of anterior urethral stricture. METHODS: The study enrolled 63 male patients with diagnosed anterior urethral strictures alongside 10 healthy volunteers to serve as controls. The imaging protocol utilized a high-frequency 3D ultrasound system combined with a linear stepper motor, which enabled precise and rapid image acquisition. For image analysis, an advanced AI-based segmentation process using a modified U-net algorithm was implemented to perform real-time, high-resolution segmentation and three-dimensional reconstruction of the urethra. A comparative analysis was performed against the surgically measured stricture lengths. Spearman's correlation analysis was executed to assess the findings. RESULTS: The AI model completed the entire processing sequence, encompassing recognition, segmentation, and reconstruction, within approximately 5 min. The mean intraoperative length of urethral stricture was determined to be 14.4 ± 8.4 mm. Notably, the mean lengths of the urethral strictures reconstructed by manual and AI models were 13.1 ± 7.5 mm and 13.4 ± 7.2 mm, respectively. Interestingly, no statistically significant disparity in urethral stricture length between manually reconstructed and AI-reconstructed images was observed. Spearman's correlation analysis underscored a more robust association of AI-reconstructed images with intraoperative urethral stricture length than manually reconstructed 3D images (0.870 vs. 0.820). Furthermore, AI-reconstructed images provided detailed views of the corpus spongiosum fibrosis from multiple perspectives. CONCLUSIONS: The research heralds the inception of an innovative, efficient AI-driven sonographic approach for three-dimensional visualization of urethral strictures, substantiating its viability and superiority in clinical application.

Development and promotion of a 3D-printed phantom model for ultrasound-guided caudal block followed by intracavitary/interstitial brachytherapy for gynecological cancer.

PURPOSE: We developed a 3D-printed phantom model for ultrasound-guided caudal block for educational or training purposes because there have been no reports of the 3D-printed phantom model for ultrasound-guided caudal block. This study aimed to identify the needs for the phantom model in a lecture and demonstration at hands-on training (HoT) to promote the use of caudal block for sufficient pain control during high-dose-rate intracavitary/interstitial brachytherapy for gynecological cancers. MATERIALS AND METHODS: The sacrum and formwork were designed by computed tomography imaging. A 3D-modeling software program was used to create the sacrum and formwork. The phantom was solidified by injecting a gelatin-based gel. Ultrasonography was performed to visualize the sacral hiatus and puncture needle in the phantom. In October 2023, 10 radiation oncologists who did not perform caudal block in daily clinical practice from ten Japanese facilities participated in HoT on ultrasound-guided caudal block. After the HoT, questionnaires were distributed to each participant, and feedback was obtained through online channels. RESULTS: After receiving a lecture and demonstration on ultrasound-guided caudal block, 90% of the respondents would like to practice the procedure in their daily clinical practice. Moreover, 100% of the respondents would like to use the 3D-printed phantom model for ultrasound-guided caudal block for educational or training purposes. CONCLUSION: The 3D-printed phantom model for ultrasound-guided caudal block can be used in training and is in demand for facilities introducing caudal block.

The Accuracy of Three-Dimensional Soft Tissue Simulation in Orthognathic Surgery-A Systematic Review.

Three-dimensional soft tissue simulation has become a popular tool in the process of virtual orthognathic surgery planning and patient-surgeon communication. To apply 3D soft tissue simulation software in routine clinical practice, both qualitative and quantitative validation of its accuracy are required. The objective of this study was to systematically review the literature on the accuracy of 3D soft tissue simulation in orthognathic surgery. The Web of Science, PubMed, Cochrane, and Embase databases were consulted for the literature search. The systematic review (SR) was conducted according to the PRISMA statement, and 40 articles fulfilled the inclusion and exclusion criteria. The Quadas-2 tool was used for the risk of bias assessment for selected studies. A mean error varying from 0.27 mm to 2.9 mm for 3D soft tissue simulations for the whole face was reported. In the studies evaluating 3D soft tissue simulation accuracy after a Le Fort I osteotomy only, the upper lip and paranasal regions were reported to have the largest error, while after an isolated bilateral sagittal split osteotomy, the largest error was reported for the lower lip and chin regions. In the studies evaluating simulation after bimaxillary osteotomy with or without genioplasty, the highest inaccuracy was reported at the level of the lips, predominantly the lower lip, chin, and, sometimes, the paranasal regions. Due to the variability in the study designs and analysis methods, a direct comparison was not possible. Therefore, based on the results of this SR, guidelines to systematize the workflow for evaluating the accuracy of 3D soft tissue simulations in orthognathic surgery in future studies are proposed.

Causal mediation analysis with a three-dimensional image mediator.

Causal mediation analysis is increasingly abundant in biology, psychology, and epidemiology studies and so forth. In particular, with the advent of the big data era, the issue of high-dimensional mediators is becoming more prevalent. In neuroscience, with the widespread application of magnetic resonance technology in the field of brain imaging, studies on image being a mediator emerged. In this study, a novel causal mediation analysis method with a three-dimensional image mediator is proposed. We define the average casual effects under the potential outcome framework, explore several sufficient conditions for the valid identification, and develop techniques for estimation and inference. To verify the effectiveness of the proposed method, a series of simulations under various scenarios is performed. Finally, the proposed method is applied to a study on the causal effect of mother's delivery mode on child's IQ development. It is found that cesarean section may have a negative effect on intellectual performance and that this effect is mediated by white matter development. Additional prospective and longitudinal studies may be necessary to validate these emerging findings.

Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.

Purpose: Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (CNN) using a multichannel input method. Methods: A target conformal plan (TCP) was created based on the maximum planning target volume (PTV). Input data included TCP dose distribution, images, target structures, and organ-at-risk (OAR) information. The role of target conformal plan dose (TCPD) was assessed by comparing the TCPD-CNN (with dose information) and NonTCPD-CNN models (without dose information) using statistical analyses with the ranked Wilcoxon test (P < .05 considered significant). Results: The TCPD-CNN model showed no statistical differences in predicted target indices, except for PTV60, where differences in the D98% indicator were < 0.5%. For OARs, there were no significant differences in predicted results, except for some small-volume or closely located OARs. On comparing TCPD-CNN and NonTCPD-CNN models, TCPD-CNN's dose-volume histograms closely resembled clinical plans with higher similarity index. Mean dose differences for target structures (predicted TCPD-CNN and NonTCPD-CNN results) were within 3% of the maximum prescription dose for both models. TCPD-CNN and NonTCPD-CNN outcomes were 67.9% and 54.2%, respectively. 3D gamma pass rates of the target structures and the entire body were higher in TCPD-CNN than in the NonTCPD-CNN models (P < .05). Additional evaluation on previously unseen volumetric modulated arc therapy plans revealed that average 3D gamma pass rates of the target structures were larger than 90%. Conclusions: This study presents a novel framework for dose distribution prediction using deep learning and multichannel input, specifically incorporating TCPD information, enhancing prediction accuracy for IMRT in NPC treatment.

Visible Korean based on true color sectioned images for making realistic digital human, twenty years' record: a review.

PURPOSE: Visible Korean (VK) consists of two-dimensional (2D) images and three-dimensional (3D) models. The VK is used in various educational tools and research sources for anatomy. In this paper, we report on the records of the VK over 20 years. METHODS: Research papers related to Visible Korean were reviewed. RESULTS: Through this report of VK records, we highlighted the essential points for making true color and ultra-high-resolution sectioned images of human and animal bodies, for making various 2D and 3D applications from the sectioned images, and for good use of the sectioned images and their applications. CONCLUSION: In this metaverse age that various virtual environments are required in medical education and research, the VK dataset meets the reality of virtual human models as fundamental data owing to the actual color and high resolution of the VK dataset.

Simultaneous analysis of shape and internal structure of a curved Hibiscus cannabinus pulvinus: X-ray microtomography and semi-automated quantification.

In the Malvaceae family, dynamic solar tracking by leaves is actuated by the deformation of the pulvinus, a thickened region at the leaf blade-petiole junction. While the internal structure is believed to play a crucial role in this process, experimental verification has been challenging due to technical limitations. To address this gap, we developed a semi-automated workflow, which integrates data analysis and image processing to simultaneously analyze the shape and internal structure of a Malvaceae pulvinus using X-ray microtomography. Firstly, we found that kenaf (Hibiscus cannabinus L.), a Malvaceae species with curved pulvini, exhibited solar-tracking leaf movement and selected it as a model system. We employed diffusible iodine-based contrast-enhanced computed tomography to visualize the internal structure of the kenaf pulvinus. Analysis of the pulvini's shape revealed variations in pulvinus morphology, yet plausible prediction of the centerline was accomplished using polar polynomial regression. Upon slicing the pulvini perpendicular to the centerline, we observed distinct gray value gradients along the proximo-distal and adaxial-abaxial axes, challenging threshold-based tissue segmentation. This workflow successfully generated three modified 3D images and derived quantitative parameters. Using these quantitative parameters, we conducted network analysis and found the linkage between the size-normalized cortex cross-sectional area and curvature. Polynomial least absolute shrinkage and selection operator (LASSO) regression revealed the relationship between the size-normalized cortex cross-sectional area and curvature commonly in all three tested samples. This workflow enables simultaneous analysis of the shape and internal structure, significantly improving the reproducibility of Malvaceae leaf pulvinus characterization.

Using the depth deviation based on three-dimensional images to evaluate the correction of nasolabial folds: A prospective and quantitative analysis.

BACKGROUND AND OBJECTIVE: The deepening of the nasolabial fold (NLF) is a common occurrence during the aging process, necessitating the development of an objective method to evaluate changes in NLFs. The objective of our study was to introduce a method of depth deviation based on three-dimensional (3D) image for evaluating the efficacy of hyaluronic acid (HA) injection in correcting NLFs. METHODS: Between May 2019 and November 2019, we recruited 56 Chinese volunteers with moderate to severe NLFs for this study. The participants received HA injections and were followed up for a period of 12 months. Pre and posttreatment, we collected the Wrinkle Severity Rating Scale (WSRS) scores and 3D images. To assess the efficacy of NLF correction, we used the maximum value of depth deviation (MVD) based on 3D images and the Global Aesthetic Improvement Scale (GAIS) score. Additionally, we compared the relationship between MVD and other clinical parameters. RESULTS: Fifty-four female participants completed the study and were included in the analysis. The HA injection resulted in a significant decrease in NLF severity (p < 0.05). One month after the injection, the average GAIS score was 4.72 ± 0.45, and the average MVD was 2.10 ± 0.56 mm. Both the GAIS score and the average MVD exhibited a decline over time during the follow-up period, with the average MVD showing a significant correlation with the GAIS score at all time points (p < 0.05). CONCLUSIONS: Using 3D technology, we demonstrated that the quantitative data provided by MVD can serve as an objective method for evaluating the correction of NLFs.

Usefulness of sectional images in dural AVF for the interpretation of venous anatomy.

Knowledge of the venous anatomy is essential for appropriately treating dural arteriovenous fistulas (AVFs). It is challenging to determine the overall venous structure despite performing selective angiography for dural AVFs with feeder from multiple selected arteries. This is because only a part of the veins can be observed through the shunt in the selected artery. Therefore, after performing selective angiography of all vessels to understand the approximate venous anatomy, the venous anatomy can be easily understood by closely examining the source image of computed tomographic angiography or magnetic resonance angiography. Through this, it is possible to specify the vein that is to be blocked (target embolization), thereby avoiding extensive blocking of the vein and avoiding various complications. In the case of dural AVF with feeder from single selected artery, if the multiplanar reconstruction image of the three-dimensional rotational computed tomography obtained by performing angiography is analyzed thoroughly, a shunted pouch can be identified. If embolization is performed by targeting this area, unnecessary sinus total packing can be avoided.

Evaluation of cardiac contractility of fetuses from pregestational diabetes mellitus pregnancies by three-dimensional ultrasound

SUMMARY OBJECTIVE: This study aimed to evaluate cardiac contractility in fetuses from pregestational diabetes mellitus pregnancies by three-dimensional ultrasound using spatiotemporal image correlation in rendering mode. METHODS: A retrospective cross-sectional study was performed on 40 fetuses from nondiabetic pregnancies and 28 pregestational diabetic pregnancies between 20 and 33 weeks and 6 days. Cardiac contractility was assessed by measuring the ventricular myocardial area in diastole subtracted from the ventricular myocardial area in systole. RESULTS: Pregestational diabetic pregnancies had a lower maternal age than nondiabetic pregnancies (26.7 vs. 39.9 years, p=0.019). Cardiac contractility in fetuses from diabetic and nondiabetic pregnancies was similar (p=0.293). A moderately positive and significant correlation was observed between gestational age and cardiac contractility (r=0.46, p=0.0004). A 1-week increase in gestational age was responsible for a 0.1386 cm2 increase in cardiac contractility. CONCLUSION: Cardiac contractility as evaluated by three-dimensional ultrasound using spatiotemporal image correlation in rendering mode showed no significant differences across fetuses with and without pregestational diabetes.

Evaluating the precision and accuracy of digital dental models with a low-cost structured light device

ABSTRACT Objective: This study evaluated the accuracy and precision of digital models acquisition using a home-built, low-cost scanning system based on the structured light method. Methods: a plaster model (PM) was scanned using the experimental device (SL) and a dental desktop scanner (DS). The teeth dimensions of PM and SL models were measured in triplicate, with a caliper and digitally, respectively. The agreement of the measurements of each model was evaluated using the intraclass correlation coefficient, and the validity between the different measurement techniques was assessed using the Bland-Altman analysis. The accuracy and precision of the models were qualitatively investigated using the mesh superposition of the SL and DS models. Results: A high intraclass correlation coefficient was observed in all models (PM=0.964; SL1=0.998; SL2=0.995; SL3=0.998), and there was no statistical difference between the measurements of the SL models (p>0.05). PM and SL model measurements were found to be in good agreement, with only 3.57% of the observed differences between the same measurement being located outside 95% limits of agreement according to Bland and Altman (0.43 and -0.40 mm). In the superimpositions of SL-SL and SL-DS models, areas of discrepancy greater than 0.5 mm were observed mainly in interproximal, occlusal, and cervical sites. Conclusion: These results indicate that the home-built SL scanning system did not possess sufficient accuracy and precision for many clinical applications. However, the consistency in preserving the dental proportions suggests that the equipment can be used for planning, storage, and simple clinical purposes.

RESUMO Objetivo: Este estudo avaliou a acurácia e a precisão da aquisição de modelos digitais utilizando um sistema de digitalização caseiro e de baixo custo baseado no método de luz estruturada. Material e Métodos: Para isso, um modelo de gesso (MG) foi digitalizado utilizando o dispositivo experimental (LE) e um scanner dental de mesa (SD). As dimensões dos dentes dos modelos MG e LE foram medidas em triplicata com um paquímetro e digitalmente, respectivamente. A concordância das medidas de cada modelo foi avaliada usando o coeficiente de correlação intraclasse, e a validade entre as diferentes técnicas de medição foi avaliada usando a análise de Bland-Altman. A acurácia e a precisão dos modelos foram investigadas qualitativamente usando a sobreposição de malhas dos modelos LE e SD. Resultados: Um alto coeficiente de correlação intraclasse foi observado em todos os modelos (MG=0,964; LE1=0,998; LE2=0,995; LE3=0,998) e não houve diferença estatística entre as medições dos modelos LE (p>0,05). As medições dos modelos MG e LE mostraram boa concordância, com apenas 3,57% das diferenças observadas entre as mesmas medições localizadas fora dos limites de concordância de 95% de acordo com a análise de Bland-Altman (0,43 e -0,40 mm). Nas sobreposições dos modelos LE-LE e LE-SD, foram observadas áreas de discrepância maiores que 0,5 mm principalmente nos sítios interproximais, oclusais e cervicais. Conclusões: Esses resultados indicam que o sistema de digitalização por luz estruturada caseiro não possui precisão e acurácia suficientes para muitas aplicações clínicas. No entanto, a consistência na preservação das proporções dentárias sugere que o equipamento pode ser usado para planejamento, armazenamento e propósitos clínicos simples.

Lymph Node Stations of Pancreas Which Are Identified in Real Color Sectioned Images of a Cadaver With Pancreatic Cancer.

BACKGROUND: In pancreatic cancer surgery, anatomical understanding of lymph node metastases is required. Distinguishing lymph nodes in computed tomography or magnetic resonance imaging is challenging for novice doctors and medical students because of their small size and similar color to surrounding tissues. This study aimed to enhance our understanding of the clinical anatomy of lymph node stations relevant to pancreatic cancer using newly sectioned images of a cadaver with true color and high resolution and their three-dimensional (3D) models. METHODS: An 88-year-old female cadaver who died of pancreatic cancer was serially sectioned. Among the sectioned images of the whole body (0.05 mm-sized pixel, 48 bits color), images of the abdomen were selected, and examined to identify lymph nodes and nearby structures. 34 structures (9 in digestive system; 1 in urinary system; 2 in cardiovascular system; 22 in lymphatic system) were segmented on the sectioned images. Based on the sectioned and segmented images, volume and surface models were produced. RESULTS: Among the known 28 lymph node stations, 21 stations were identified through location, size, and color of normal and abnormal structures in the sectioned images and 3D models. Two near the splenic artery could not be separated from the cancer tissue, and the remaining five were not clearly identified. In the surface models, the shape and location of lymph node stations could be confirmed with nearby structures. CONCLUSION: The lymph node stations relevant to pancreatic cancer can be anatomically understood by using the sectioned images and 3D models which contain true color and high resolution.

Radiographic comparison of atelocollagen versus deproteinized bovine bone minerals covered with a collagen membrane in alveolar ridge preservation: a retrospective study.

BACKGROUND: Atelocollagen (AC) is a low-immunogenic collagen derivative with longer degradation time, which can be a suitable material for alveolar ridge preservation (ARP). However, there are few human studies on AC using for ARP. This research aims to radiographically evaluate the efficacy of AC in comparison to deproteinized bovine bone minerals covered with a collagen membrane (DBBM/CM) in ARP. METHODS: Medical records in the Implantology Department of the Hospital of Stomatology of Wuhan University were screened for patients who received flapless ARP using either AC or DBBM/CM. A total of 58 patients were included in this retrospective study. 28 patients were treated with AC, while 30 patients were used DBBM/CM. Cone-beam computed tomography (CBCT) scans were taken before extraction and after 6 months of healing. To assess the dimensional change of the extraction sockets, the scanning data were output and transferred to the digital software to measure horizontal bone width change, vertical bone height change and bone volume change in region of interest. To evaluate the bone quality of healed sockets, the bone density of virtual implants was evaluated. RESULTS: The horizontal bone width changes at all five different levels showed no significant difference between the two groups. The largest horizontal bone width decrement in both groups occurred at the crest of ridge, which decreased 3.71 ± 1.67 mm in AC group and 3.53 ± 1.51 mm in DBBM/CM group (p = 0.68). At the central buccal aspect, the ridge height reduced 0.10 ± 1.30 mm in AC group, while increased 0.77 ± 2.43 mm in DBBM/CM group (p = 0.10). The vertical bone height differences between two groups showed no statistical significance. The percentages of volume absorption in AC group and DBBM/CM group were 12.37%±6.09% and 14.54%±11.21%, respectively. No significant difference in volume absorption was found (p = 0.36). The average bone density around virtual implants in AC group (649.41 ± 184.71 HU) was significantly lower than that in DBBM/CM group (985.23 ± 207.85 HU) (p < 0.001). CONCLUSIONS: ARP with AC had a similar effect on limiting the dimensional alteration of alveolar ridge, when radiographically compared with DBBM/CM.

Image-based robotic-arm assisted unicompartmental knee arthroplasty provides high survival and good-to-excellent clinical outcomes at minimum 10 years follow-up.

PURPOSE: The purpose of the present study was to determine the incidence of revision and report on clinical outcomes at a minimum of 10 years follow-up in patients who had received a medial unicompartmental knee arthroplasty (UKA) with an three-dimensional image-based robotic system. METHODS: A total of 239 patients (247 knees), who underwent medial robotic-arm assisted (RA)-UKA at a single center between April 2011 and June 2013, were assessed. The mean age at surgery was 67.0 years (SD 8.4). Post-operatively, patients were administered the Forgotten Joint Score-12 (FJS-12) and asked about their satisfaction (from 1 to 5). Post-operative complications were recorded. Failure mechanisms, revisions and reoperations were collected. Kaplan-Meier survival curves were calculated, considering revision as the event of interest. RESULTS: A total of 188 patients (196 knees) were assessed at a mean follow-up of 11.1 years (SD 0.5, range 10.0-11.9), resulting in a 79.4% follow-up rate. Seven RA-UKA underwent revision, resulting in a survivorship rate of 96.4% (CI 94.6%-99.2%). Causes of revision included aseptic loosening (2 cases), infection (1 case), post-traumatic (1 case), and unexplained pain (3 cases). The mean FJS-12 and satisfaction were 82.2 (SD 23.9) and 4.4 (SD 0.9), respectively. Majority of cases (174/196, 88.8%) attained the Patient Acceptable Symptoms State (PASS, FJS-12 > 40.63). Male subjects had a higher probability of attaining a "forgotten joint" (p < 0.001) and high satisfaction (equal to 5, p < 0.05), when compared to females. CONCLUSIONS: Three-dimensional image-based RA-UKA demonstrated high implant survivorship and good-to-excellent clinical outcomes at minimum 10 years follow-up. Pain of unknown origin represented the most common reason for RA-UKA revision. LEVEL OF EVIDENCE: III.

Three-Dimensional Volume Rendering in Computed Tomography for Evaluation of the Temporomandibular Joint in Dogs.

Based on computed tomography (CT) images, volume rendering was used to obtain a three-dimensional representation of data (3DVR). The aims of this study included: describing the bone anatomy of the temporomandibular joint (TMJ) of dogs; comparing the TMJs of each dog by skull type and age; comparing 3DVR images with three-standard-plane CTs; assessing soft tissues adjacent to the TMJ and assessing pathological cases. Multidetector computed tomography scans of bilateral TMJs of 410 dogs were observed. From a ventral view, slight displacements in the positions of the skulls were seen, whereas from a caudal view, differences in amplitude of the articular space were observed. Dolichocephalic and mesaticephalic dogs showed more similar TMJ features than brachycephalic dogs. The shape of the TMJ bones were irregular in dogs under 1 year old. The 3DVR images related to the three-standard-plane CT improved the overall comprehension of the changes in the articular space amplitude and condylar process morphology. The fovea pterygoidea, mandibular fossa and retroarticular process were perfectly shown. A better spatial situation of adjacent soft tissues was obtained. The 3DVR represents an ancillary method to the standard-plane CT that could help in the understanding of the anatomy and diagnoses of different pathologies of the TMJ in dogs.

Protocol for capturing 3D facial meshes for rhinoseptoplasty planning

Abstract Objectives: To present and execute a protocol for the capture of 3D facial images using photogrammetry through the open access software Blender and its add-on OrtogOnBlender (OOB) and to evaluate the compatibility of the 3D meshes generated with Computed tomography (CT) of the sinuses. Methods: Individuals > 18 years old, candidates for Rhinoseptoplasty in a tertiary hospital, were submitted to a photographic session to perform the standardized protocol. In the session, divided into 3 phases, sequential photos were taken for processing the photogrammetry in the OOB and producing 3D meshes of the face. The photogrammetry reconstructions were compared with the reference mesh of the soft tissue surface of the Sinus CT scan to assess compatibility between them. Results: 21 patients were included, 67% female. 3 photogrammetry meshes and 1 CT reference mesh were generated, which demonstrated matching compatibility, as most of the mean distances between cloud points were <1.48mm. Phase 3 of the session with the highest number of photos (54.36 ± 15.05) generated the most satisfactory mesh with the best resolution. Conclusions: The proposed protocol is reproducible and feasible in clinical practice, generated satisfactory 3D meshes of the face, being a potential tool for surgical planning and comparison of results. For the implementation of photogrammetry for use in 3D anthropometry, it is necessary to validate this method. Level of evidence: 3. OCEBM Levels of Evidence Working Group.1 The Oxford 2011 Levels of Evidence. Oxford Centre for Evidence-Based Medicine. http://www.cebm.net/index.aspx?o=5653

Three-dimensional CT imaging in extensor tendons using deep learning reconstruction: optimal reconstruction parameters and the influence of dose.

The purpose of this study was to assess the optimal reconstruction parameters and the influence of tube current in extensor tendons three-dimensional computed tomography (3D CT) using deep learning reconstruction, using iterative reconstruction as a reference. In the phantom study, a cylindrical phantom with a 3 mm rod simulated an extensor tendon was used. The phantom images were acquired at tube current of 50, 100, 150, 200, and 250 mA. In the clinical study, CT scans of hand tendons were performed on nine hands from eight patients. All images were reconstructed using advanced intelligent clear-IQ engine (AiCE) parameters (body, body sharp, brain CTA, and brain LCD) and adaptive iterative dose reduction three dimensional (AIDR 3D). The objective image quality for tendon detectability was evaluated by calculating the low-contrast object specific contrast-to-noise ratio (CNRLO) in the phantom study and CNR and coefficient of variation (CV) in the clinical study. In the phantom study, CNRLO (at 200 mA) of AiCE parameters (body, body sharp, brain CTA, and brain LCD) and AIDR 3D were 5.2, 5.3, 5.3, 5.8, and 5.0, respectively. In the clinical study, AiCE brain CTA was higher CNR and lower CV values compared to other reconstruction parameters. AiCE without dose reduction may be an effective strategy for further improving the image quality of extensor tendons 3D CT. Our study suggests that the AiCE brain CTA is more suitable for extensor tendons 3D CT compared to other AiCE parameters.

Coherent Laser Ranging of Deforming Objects in Fires at Sub-Millimeter Precision.

Light Detection and Ranging (LiDAR) is a powerful tool to characterize and track the surface geometry of solid objects. In a fire, however, no method has excelled at measuring three-dimensional shapes at millimeter precision while offering some immunity to the effects of flames. This paper applies coherent Frequency Modulated Continuous Wave Light Detection and Ranging to capture three-dimensional measurements of objects in fire at meters of stand-off distance. We demonstrate that despite the presence of natural gas flame depths up to 1.5 m obscuring the target, measurements with millimeter precision can be obtained. This is a significant improvement over previous work making the technique useful for many fire research applications. An approach to achieve sub-millimeter precision using spatial and temporal averaging during post-processing is presented. The technology is demonstrated in case studies of structural connection and vegetation response in fires.

Three-dimensional visualization and evaluation of hilar cholangiocarcinoma resectability and proposal of a new classification.

BACKGROUND: As digital medicine has exerted profound influences upon diagnosis and treatment of hepatobiliary diseases, our study aims to investigate the accuracy of three-dimensional visualization and evaluation (3DVE) system in assessing the resectability of hilar cholangiocarcinoma (hCCA), and explores its potential clinical value. MATERIALS AND METHODS: The discovery cohort, containing 111 patients from April 2013 to December 2019, was retrospectively included to determine resectability according to revised criteria for unresectability of hCCA. 3D visualization models were reconstructed to evaluate resectability parameters including biliary infiltration, vascular involvement, hepatic atrophy and metastasis. Evaluation accuracy were compared between contrast-enhanced CT and 3DVE. Logistic analysis was performed to identify independent risk factors of R0 resection. A new comprehensive 3DVE classification of hCCA based on factors influencing resectability was proposed to investigate its role in predicting R0 resection and prognosis. The main outcomes were also analyzed in cohort validation, including 34 patients from January 2020 to August 2022. RESULTS: 3DVE showed an accuracy rate of 91% (95%CI 83.6-95.4%) in preoperatively evaluating hCCA resectability, significantly higher than 81% (95%CI 72.8-87.7%) of that of CT (p = 0.03). By multivariable analysis, hepatic artery involvement in 3DVE was identified an independent risk factor for R1 or R2 resection (OR = 3.5, 95%CI 1.4,8.8, P < 0.01). New 3DVE hCCA classification was valuable in predicting patients' R0 resection rate (p < 0.001) and prognosis (p < 0.0001). The main outcomes were internally validated. CONCLUSIONS: 3DVE exhibited a better efficacy in evaluating hCCA resectability, compared with contrast-enhanced CT. Preoperative 3DVE demonstrated hepatic artery involvement was an independent risk factor for the absence of R0 margin. 3DVE classification of hCCA was valuable in clinical practice.