Improving standard volar plate fixation in 3D-guided corrective osteotomy of the distal radius: evaluation of a shim instrument.

Standard volar plates often do not fit the surface of the malunited distal radius after osteotomy, necessitating an offset angle for accurate volar tilt correction. The correction can be achieved if the plate is held at the correct angle when the distal screws are locked. With the advantage of 3D surgical planning and patient-specific instruments, we developed a shim instrument to assist the surgeon in securing the plate at the intended angle when locking the distal screws, and evaluated radiological results. Five female patients aged 63-74 with dorsally angulated extra-articular malunions underwent surgery using 3D-printed guides and the shim instrument. The plate position, drilling guide alignment, screw placements, and distal radius correction on postoperative CTs were compared with the surgical plans. Errors were measured using an anatomical coordinate system, and standard 2D radiographic measures were extracted. Preoperative dorsal tilt ranged from 16° to 35°, and postoperative volar tilt from 1° to 11°. 3D analysis revealed mean absolute correction errors of 6.1° in volar tilt, 1.6° in radial inclination, and 0.6 mm in ulnar variance. The volar tilt error due to the shim instrument, indicated by the mean angle error of the distal screws to the plate, was 2.1° but varied across the five patients. Settling of the distal radius, due to tension during and after reduction, further contributed to a mean loss of 3.5° in volar tilt. The shim instrument helped with securing plates at the intended angle; however, further correction improvements should consider the tension between the fragments of osteoporotic bone.

Accurate object localization facilitates automatic esophagus segmentation in deep learning.

BACKGROUND: Currently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We aimed to improve the performance of esophagus segmentation in deep learning by applying a strategy that involves locating the object first and then performing the segmentation task. METHODS: A total of 100 cases with thoracic computed tomography scans from two publicly available datasets were used in this study. A modified CenterNet, an object location network, was employed to locate the center of the esophagus for each slice. Subsequently, the 3D U-net and 2D U-net_coarse models were trained to segment the esophagus based on the predicted object center. A 2D U-net_fine model was trained based on the updated object center according to the 3D U-net model. The dice similarity coefficient and the 95% Hausdorff distance were used as quantitative evaluation indexes for the delineation performance. The characteristics of the automatically delineated esophageal contours by the 2D U-net and 3D U-net models were summarized. Additionally, the impact of the accuracy of object localization on the delineation performance was analyzed. Finally, the delineation performance in different segments of the esophagus was also summarized. RESULTS: The mean dice coefficient of the 3D U-net, 2D U-net_coarse, and 2D U-net_fine models were 0.77, 0.81, and 0.82, respectively. The 95% Hausdorff distance for the above models was 6.55, 3.57, and 3.76, respectively. Compared with the 2D U-net, the 3D U-net has a lower incidence of delineating wrong objects and a higher incidence of missing objects. After using the fine object center, the average dice coefficient was improved by 5.5% in the cases with a dice coefficient less than 0.75, while that value was only 0.3% in the cases with a dice coefficient greater than 0.75. The dice coefficients were lower for the esophagus between the orifice of the inferior and the pulmonary bifurcation compared with the other regions. CONCLUSION: The 3D U-net model tended to delineate fewer incorrect objects but also miss more objects. Two-stage strategy with accurate object location could enhance the robustness of the segmentation model and significantly improve the esophageal delineation performance, especially for cases with poor delineation results.

Preoperative three-dimensional lung volumetry predicts respiratory complications in patients undergoing major liver resection for colorectal metastases.

Colorectal liver metastases (CRLM) are the predominant factor limiting survival in patients with colorectal cancer and liver resection with complete tumor removal is the best treatment option for these patients. This study examines the predictive ability of three-dimensional lung volumetry (3DLV) based on preoperative computerized tomography (CT), to predict postoperative pulmonary complications in patients undergoing major liver resection for CRLM. Patients undergoing major curative liver resection for CRLM between 2010 and 2021 with a preoperative CT scan of the thorax within 6 weeks of surgery, were included. Total lung volume (TLV) was calculated using volumetry software 3D-Slicer version 4.11.20210226 including Chest Imaging Platform extension ( http://www.slicer.org ). The area under the curve (AUC) of a receiver-operating characteristic analysis was used to define a cut-off value of TLV, for predicting the occurrence of postoperative respiratory complications. Differences between patients with TLV below and above the cut-off were examined with Chi-square or Fisher's exact test and Mann-Whitney U tests and logistic regression was used to determine independent risk factors for the development of respiratory complications. A total of 123 patients were included, of which 35 (29%) developed respiratory complications. A predictive ability of TLV regarding respiratory complications was shown (AUC 0.62, p = 0.036) and a cut-off value of 4500 cm3 was defined. Patients with TLV < 4500 cm3 were shown to suffer from significantly higher rates of respiratory complications (44% vs. 21%, p = 0.007) compared to the rest. Logistic regression analysis identified TLV < 4500 cm3 as an independent predictor for the occurrence of respiratory complications (odds ratio 3.777, 95% confidence intervals 1.488-9.588, p = 0.005). Preoperative 3DLV is a viable technique for prediction of postoperative pulmonary complications in patients undergoing major liver resection for CRLM. More studies in larger cohorts are necessary to further evaluate this technique.

Clinical Application of the 4K-3D Exoscope System in Cochlear Implantation.

PURPOSE: To evaluate a system for otomicrosurgery based on 4K three-dimensional (3D) exoscope technology and apply it to cochlear implantation. METHODS: An open stereoscopic vision-based surgical system, which differs from traditional surgical microscopes, was created by utilizing 4K stereo imaging technology and combining it with low-latency 4K ultra-high-definition 3D display. The system underwent evaluation based on 57 cochlear implantation operations, three designed microscopic manipulations, and a questionnaire survey. RESULTS: The surgical images displayed by the 4K-3D exoscope system (4K-3D-ES) are stereoscopic, clear, and smooth. The use of 4K-3D-ES in cochlear implantation is not inferior to traditional microscopes in terms of intraoperative bleeding and surgical complications, and the surgical duration is not slower or may even be faster than when using traditional microscopes. The results of micromanipulation experiments conducted on 16 students also confirmed this and demonstrated that 4K-3D-ES can be easily adapted. Furthermore, additional advantages of 4K-3D-ES were gathered. Significantly enlarged and high-definition stereoscopic images contribute to the visualization of finer anatomical microstructures such as chordae tympani, ensuring safer surgery. Users feel more comfortable in their necks, shoulders, waists, and backs. Real-time shared stereoscopic view for multiple people, convenient for collaboration and teaching. The ear endoscope and 4K-3D-ES enable seamless switching on the same screen. High-definition 3D images and videos can be saved with just one click, making future publication and communication convenient. CONCLUSION: The feasibility and safety of 4K-3D-ES for cochlear implantation surgery have been demonstrated. The 4K-3D-ES also offers numerous unique advantages and holds clinical application and promotional value.

Chondrosarcoma evaluation using hematein-based x-ray staining and high-resolution 3D micro-CT: a feasibility study.

BACKGROUND: Chondrosarcomas are rare malignant bone tumors diagnosed by analyzing radiological images and histology of tissue biopsies and evaluating features such as matrix calcification, cortical destruction, trabecular penetration, and tumor cell entrapment. METHODS: We retrospectively analyzed 16 cartilaginous tumor tissue samples from three patients (51-, 54-, and 70-year-old) diagnosed with a dedifferentiated chondrosarcoma at the femur, a moderately differentiated chondrosarcoma in the pelvis, and a predominantly moderately differentiated chondrosarcoma at the scapula, respectively. We combined a hematein-based x-ray staining with high-resolution three-dimensional (3D) microscopic x-ray computed tomography (micro-CT) for nondestructive 3D tumor assessment and tumor margin evaluation. RESULTS: We detected trabecular entrapment on 3D micro-CT images and followed bone destruction throughout the volume. In addition to staining cell nuclei, hematein-based staining also improved the visualization of the tumor matrix, allowing for the distinction between the tumor and the bone marrow cavity. The hematein-based staining did not interfere with further conventional histology. There was a 5.97 ± 7.17% difference between the relative tumor area measured using micro-CT and histopathology (p = 0.806) (Pearson correlation coefficient r = 0.92, p = 0.009). Signal intensity in the tumor matrix (4.85 ± 2.94) was significantly higher in the stained samples compared to the unstained counterparts (1.92 ± 0.11, p = 0.002). CONCLUSIONS: Using nondestructive 3D micro-CT, the simultaneous visualization of radiological and histopathological features is feasible. RELEVANCE STATEMENT: 3D micro-CT data supports modern radiological and histopathological investigations of human bone tumor specimens. It has the potential for being an integrative part of clinical preoperative diagnostics. KEY POINTS: • Matrix calcifications are a relevant diagnostic feature of bone tumors. • Micro-CT detects all clinically diagnostic relevant features of x-ray-stained chondrosarcoma. • Micro-CT has the potential to be an integrative part of clinical diagnostics.

Three-dimensional virtual model for robot-assisted partial nephrectomy: a propensity-score matching analysis with a contemporary control group.

PURPOSE: To compare two cohorts of patients submitted to robot-assisted partial nephrectomy (RAPN) with vs without the use of three-dimensional virtual models (3DVMs). METHODS: We screened a prospective consecutive cohort of 152 patients submitted to RAPN with 3DVM and 1264 patients submitted to RAPN without 3DVM between 2019 and 2022. Propensity score matching analysis (PSMA) was applied. Primary endpoint was to evaluate whereas RAPNs with 3DVM were superior in terms of functional outcomes at 12-month. Secondary endopoints were to compare perioperative and oncological outcomes. Multivariable logistic regression analyses (MVA) tested the associations of clinically significant eGFR drop and 3DVMs. Subgroups analysis was performed for PAUDA-risk categories. RESULTS: 100 patients for each group were analyzed after PSMA. RAPN with 3DVM presented a higher rate of selective/no clamping procedure (32% vs 16%, p = 0.03) and a higher enucleation rate (40% vs 29%, p = 0.04). As concern to primary endopoint, 12-month functional preservation performed better within 3DVM group in terms of creatinine serum level (median 1.2 [IQR 1.1-1.4] vs 1.6 [IQR 1.1-1.8], p = 0.03) and eGFR (median 64.6 [IQR 56.2-74.1] vs 52.3 [IQR 49.2-74.1], p = 0.03). However, this result was confirmed only in the PADUA ≥ 10 renal masses. Regarding secondary endpoints, no significative difference emerged between the two cohorts. MVA confirmed 3DVM as a protective factor for clinically significant eGFR drop only in high-risk (PADUA ≥ 10) masses. CONCLUSIONS: RAPN performed with the use of 3DVM assistance resulted in lower incidence of global ischemia and higher rate of enucleations. The positive impact of such technology was found at 12-month only in high-risk renal masses.

The effect of different hybrid rigid internal fixation techniques on the postoperative stability following a mandibular advancement using a bilateral sagittal split ramus osteotomy: A retrospective three-dimensional comparative study.

OBJECTIVE: To three-dimensionally evaluate post-operative mandibular stability following bilateral sagittal split ramus osteotomies between hybrid and non-hybrid rigid internal fixation techniques. MATERIALS AND METHOD: Seventy adults with skeletal class II deformity who underwent bilateral split sagittal osteotomy with mandibular advancement were included. Patients were divided into four groups based on their fixation techniques: hybrid technique (HT) groups I, II, and IV received a 4-hole 2 mm miniplate with either a bicortical screw (BS), additional 2 mm 4-hole miniplate, or two-hole miniplate, while non-HT group III received a 4-hole 2 mm miniplate with four mini-screws (MS). Measurements were taken pre-operatively (T0), immediately postoperatively (T1), and ≥1 year after surgery (T2) using 3D Slicer software. RESULTS: Age, sex, and follow-up period did not correlate significantly with postoperative relapse or stability. Significant differences were observed in the advancement on the right side between groups II, III, and IV and on the left side between groups I, III, and IV. However, the type of surgical intervention showed no significant effect on postoperative relapse and stability. All groups of fixations showed satisfactory stability with irrelevant relapse (< 2 mm or 2°). CONCLUSION: The study demonstrated satisfactory and comparable stability among different fixation groups on patients undergoing mandibular advancement following bilateral split sagittal osteotomy. The results highlighted the importance of considering the degree of advancement when planning orthognathic surgery and managing postoperative outcomes.

[Surgical Replacement of Descending Aorta for Adult Aortic Coarctation by Using Three-dimensional Computer Graphics Reconstruction].

Aortic coarctation is diagnosed in approximately 5% of adult patients with congenital heart disease and is commonly diagnosed through the close examination of hypertension. Various surgical strategies for adult coarctation have been recently reported. Generally, aortic replacement may require blood transfusion in case of injury of the well-developed collateral vessels. Therefore, in order to secure an operative safety, we preoperatively used a medical image viewer to identify the abnormal vessels by three-dimensional computer graphics (3DCG) reconstruction. A 34-year-old male patient was referred to our hospital with hypertension and low ankle-brachial pressure index( ABI). Chest computed tomography( CT) scan showed aortic coarctation and development of abnormal collateral vessels. Descending aorta was replaced via a left third-fourth intercostal thoracotomy under partial extracorporeal circulation. As the image viewer depicted, anatomical abnormality of the collateral vessels was identified precisely, and surgically treated without any injury. The patient was discharged 10 days postoperatively without transfusion and with a normalized ABI.

Assessment of pulmonary vascular anatomy: comparing augmented reality by holograms versus standard CT images/reconstructions using surgical findings as reference standard.

BACKGROUND: We compared computed tomography (CT) images and holograms (HG) to assess the number of arteries of the lung lobes undergoing lobectomy and assessed easiness in interpretation by radiologists and thoracic surgeons with both techniques. METHODS: Patients scheduled for lobectomy for lung cancer were prospectively included and underwent CT for staging. A patient-specific three-dimensional model was generated and visualized in an augmented reality setting. One radiologist and one thoracic surgeon evaluated CT images and holograms to count lobar arteries, having as reference standard the number of arteries recorded at surgery. The easiness of vessel identification was graded according to a Likert scale. Wilcoxon signed-rank test and κ statistics were used. RESULTS: Fifty-two patients were prospectively included. The two doctors detected the same number of arteries in 44/52 images (85%) and in 51/52 holograms (98%). The mean difference between the number of artery branches detected by surgery and CT images was 0.31 ± 0.98, whereas it was 0.09 ± 0.37 between surgery and HGs (p = 0.433). In particular, the mean difference in the number of arteries detected in the upper lobes was 0.67 ± 1.08 between surgery and CT images and 0.17 ± 0.46 between surgery and holograms (p = 0.029). Both radiologist and surgeon showed a higher agreement for holograms (κ = 0.99) than for CT (κ = 0.81) and found holograms easier to evaluate than CTs (p < 0.001). CONCLUSIONS: Augmented reality by holograms is an effective tool for preoperative vascular anatomy assessment of lungs, especially when evaluating the upper lobes, more prone to anatomical variations. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04227444 RELEVANCE STATEMENT: Preoperative evaluation of the lung lobe arteries through augmented reality may help the thoracic surgeons to carefully plan a lobectomy, thus contributing to optimize patients' outcomes. KEY POINTS: • Preoperative assessment of the lung arteries may help surgical planning. • Lung artery detection by augmented reality was more accurate than that by CT images, particularly for the upper lobes. • The assessment of the lung arterial vessels was easier by using holograms than CT images.

A three-dimensional algorithm for precise measurement of human auricle parameters.

Measurement of auricle parameters for planning and post-operative evaluation presents substantial challenges due to the complex 3D structure of the human auricle. Traditional measurement methods rely on manual techniques, resulting in limited precision. This study introduces a novel automated surface-based three-dimensional measurement method for quantifying human auricle parameters. The method was applied to virtual auricles reconstructed from Computed Tomography (CT) scans of a cadaver head and subsequent measurement of important clinically relevant aesthetical auricular parameters (length, width, protrusion, position, auriculocephalic angle, and inclination angle). Reference measurements were done manually (using a caliper and using a 3D landmarking method) and measurement precision was compared to the automated method. The CT scans were performed using both a contemporary high-end and a low-end CT scanner. Scans were conducted at a standard scanning dose, and at half the dose. The automatic method demonstrated significantly higher precision in measuring auricle parameters compared to manual methods. Compared to traditional manual measurements, precision improved for auricle length (9×), width (5×), protrusion (5×), Auriculocephalic Angle (5-54×) and posteroanterior position (23×). Concerning parameters without comparison with a manual method, the precision level of supero-inferior position was 0.489 mm; and the precisions of the inclination angle measurements were 1.365 mm and 0.237 mm for the two automated methods investigated. Improved precision of measuring auricle parameters was associated with using the high-end scanner. A higher dose was only associated with a higher precision for the left auricle length. The findings of this study emphasize the advantage of automated surface-based auricle measurements, showcasing improved precision compared to traditional methods. This novel algorithm has the potential to enhance auricle reconstruction and other applications in plastic surgery, offering a promising avenue for future research and clinical application.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

BACKGROUND: With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT). METHODS: Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE. For CODE images, data were acquired in free breathing and end-expiratory images were reconstructed using retrospective respiratory gating. All images were evaluated through qualitative and quantitative approaches regarding various anatomical structures and lesions (nodule, mediastinal mass, emphysema, reticulation, honeycombing, bronchiectasis, pleural plaque and lymphadenopathy) inside the thorax in terms of diagnostic performance in making specific decisions. RESULTS: Depiction of the lung parenchyma, mediastinal and pleural lesion was not significant different among the three modalities (p > 0.05). Intra-tumoral and peritumoral features of lung nodules were not significant different in the CT, VIBE or CODE images (p > 0.05). However, VIBE and CODE had significantly lower image quality and poorer depiction of airway, great vessels, and emphysema compared to CT (p < 0.05). Image quality of central airways and depiction of bronchi were significantly better in CODE than in VIBE (p < 0.001 and p = 0.005). In contrast, the depiction of the vasculature was better for VIBE than CODE images (p = 0.003). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significant greater in VIBE than CODE except for SNRlung and SNRnodule (p < 0.05). CONCLUSIONS: Our study showed the potential of CODE and VIBE sequences in the evaluation of localized thoracic abnormalities including solid pulmonary nodules.

Automated segmentation and volume prediction in pediatric Wilms' tumor CT using nnu-net.

BACKGROUND: Radiologic volumetric evaluation of Wilms' tumor (WT) is an important indicator to guide treatment decisions. However, due to the heterogeneity of the tumors, radiologists have main-guard differences in diagnosis that can lead to misdiagnosis and poor treatment. The aim of this study was to explore whether CT-based outlining of WT foci can be automated using deep learning. METHODS: We included CT intravenous phase images of 105 patients with WT and double-blind outlining of lesions by two radiologists. Then, we trained an automatic segmentation model using nnUnet. The Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95) were used to assess the performance. Next, we optimized the automatic segmentation results based on the ratio of the three-dimensional diameter of the lesion to improve the performance of volumetric assessment. RESULTS: The DSC and HD95 was 0.83 ± 0.22 and 10.50 ± 8.98 mm. The absolute difference and percentage difference in tumor size was 72.27 ± 134.84 cm3 and 21.08% ± 30.46%. After optimization according to our method, it decreased to 40.22 ± 96.06 cm3 and 10.16% ± 9.70%. CONCLUSION: We introduce a novel method that enhances the accuracy of predicting WT volume by integrating AI automated outlining and 3D tumor diameters. This approach surpasses the accuracy of using AI outcomes alone and has the potential to enhance the clinical evaluation of pediatric patients with WT. By intertwining AI outcomes with clinical data, this method becomes more interpretive and offers promising applications beyond Wilms tumor, extending to other pediatric diseases.

Construction of a nomogram model to predict technical difficulty in performing laparoscopic sphincter-preserving radical resection for rectal cancer.

BACKGROUND: Colorectal surgeons are well aware that performing surgery for rectal cancer becomes more challenging in obese patients with narrow and deep pelvic cavities. Therefore, it is essential for colorectal surgeons to have a comprehensive understanding of pelvic structure prior to surgery and anticipate potential surgical difficulties. AIM: To evaluate predictive parameters for technical challenges encountered during laparoscopic radical sphincter-preserving surgery for rectal cancer. METHODS: We retrospectively gathered data from 162 consecutive patients who underwent laparoscopic radical sphincter-preserving surgery for rectal cancer. Three-dimensional reconstruction of pelvic bone and soft tissue parameters was conducted using computed tomography (CT) scans. Operative difficulty was categorized as either high or low, and multivariate logistic regression analysis was employed to identify predictors of operative difficulty, ultimately creating a nomogram. RESULTS: Out of 162 patients, 21 (13.0%) were classified in the high surgical difficulty group, while 141 (87.0%) were in the low surgical difficulty group. Multivariate logistic regression analysis showed that the surgical approach using laparoscopic intersphincteric dissection, intraoperative preventive ostomy, and the sacrococcygeal distance were independent risk factors for highly difficult laparoscopic radical sphincter-sparing surgery for rectal cancer (P < 0.05). Conversely, the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance was identified as a protective factor (P < 0.05). A nomogram was subsequently constructed, demonstrating good predictive accuracy (C-index = 0.834). CONCLUSION: The surgical approach, intraoperative preventive ostomy, the sacrococcygeal distance, and the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance could help to predict the difficulty of laparoscopic radical sphincter-preserving surgery.

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.

PURPOSE: Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNet-DIR) method using unsupervised learning to establish correspondence between baseline pre-operative and follow-up MRI scans of patients with brain glioma. METHODS: This study involved multi-parametric brain MRI scans (T1, T1-contrast enhanced, T2, FLAIR) acquired at pre-operative and follow-up time for 160 patients diagnosed with glioma, representing the BraTS-Reg 2022 challenge dataset. ConvUNet-DIR, a deep learning-based deformable registration workflow using 3D U-Net style architecture as a core, was developed to establish correspondence between the MRI scans. The workflow consists of three components: (1) the U-Net learns features from pairs of MRI scans and estimates a mapping between them, (2) the grid generator computes the sampling grid based on the derived transformation parameters, and (3) the spatial transformation layer generates a warped image by applying the sampling operation using interpolation. A similarity measure was used as a loss function for the network with a regularization parameter limiting the deformation. The model was trained via unsupervised learning using pairs of MRI scans on a training data set (n = 102) and validated on a validation data set (n = 26) to assess its generalizability. Its performance was evaluated on a test set (n = 32) by computing the Dice score and structural similarity index (SSIM) quantitative metrics. The model's performance also was compared with the baseline state-of-the-art VoxelMorph (VM1 and VM2) learning-based algorithms. RESULTS: The ConvUNet-DIR model showed promising competency in performing accurate 3D deformable registration. It achieved a mean Dice score of 0.975 ± 0.003 and SSIM of 0.908 ± 0.011 on the test set (n = 32). Experimental results also demonstrated that ConvUNet-DIR outperformed the VoxelMorph algorithms concerning Dice (VM1: 0.969 ± 0.006 and VM2: 0.957 ± 0.008) and SSIM (VM1: 0.893 ± 0.012 and VM2: 0.857 ± 0.017) metrics. The time required to perform a registration for a pair of MRI scans is about 1 s on the CPU. CONCLUSIONS: The developed deep learning-based model can perform an end-to-end deformable registration of a pair of 3D MRI scans for glioma patients without human intervention. The model could provide accurate, efficient, and robust deformable registration without needing pre-alignment and labeling. It outperformed the state-of-the-art VoxelMorph learning-based deformable registration algorithms and other supervised/unsupervised deep learning-based methods reported in the literature.

HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images.

BACKGROUND: Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. METHODS: In this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios. RESULTS: Our baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks. CONCLUSIONS: Comprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

[Application of three-dimensional ultrasound technique in repairing dorsal foot wounds with medial sural artery perforator flaps].

Objective: To investigate the accuracy of positioning perforator of medial sural artery with three-dimensional ultrasound technique guided by a wide band linear matrix array volume transducer probe before operation, and the effectiveness of the flap design based on this in repairing the dorsal foot wounds. Methods: Between January 2019 and December 2022, 30 patients with skin and soft tissue defects of the dorsal foot were treated. There were 19 males and 11 females, with an average age of 43.9 years (range, 22-63 years). There were 12 cases of traffic accident injury, 15 cases of heavy crushing injury, and 3 cases of machine injury. The time from injury to hospitalization was 1-8 hours (mean, 3.5 hours). The wounds in size of 5 cm×3 cm to 17 cm×5 cm were thorough debrided and covered with vacuum sealing drainage dressing. Then the wounds were repaired with the medial sural artery perforator flaps after no obvious infection observed. To obtain the complete three-dimensional image, the number and position of the medial sural artery perforator branches and the position of the main blood vessels in the muscle were detected and recorded by wide band linear matrix array volume transducer probe before operation. Suitable perforating branches were selected to design the flap and guide the flap incision on this basis. The size of the perforating flap ranged from 6 cm×4 cm to 18 cm×6 cm. The sensitivity and positive predictive value were calculated by comparing preoperative exploration with intraoperative observation of perforating branches, so as to evaluate the positioning accuracy of three-dimensional ultrasound technique. The donor sites were sutured directly in 25 cases and repaired with free skin grafting in 5 cases. Results: The 60 perforating branches of medial sural artery were found before operation and 58 during operation in 30 patients. Among them, pre- and intra-operative perforations were consistent with 56. The sensitivity was 93.3% and positive predictive value was 96.6%. The intramuscular position and route of the main blood vessels were basically consistent with the pre- and intra-operative observation. All flaps survived and wounds healed by first intention. All incisions at the donor sites healed by first intention, and all skin grafts survived. All patients were follow up 9-24 months (mean, 14.7 months). The appearance, color, and texture of the flaps were good, and no obvious effect on wearing shoes and walking. At last follow-up, the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hind score ranged from 80 to 92, with an average of 87.5. The patient satisfaction was excellent in 29 cases and good in 1 case. Conclusion: The three-dimensional ultrasound technique guided by the wide band linear matrix array volume transducer probe can accurately locate the perforating branch of the medial sural artery, and the three-dimensional imaging is more intuitive, which can be used to guide the design and incision of the medial sural artery perforator flap.

Analysis of 3D pathology samples using weakly supervised AI.

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Three-dimensional evaluation of dental characteristics in patients with Cleidocranial dysplasia.

BACKGROUND: Cleidocranial dysplasia (CCD) is an autosomal dominant hereditary disorder. Besides skeletal abnormalities, CCD is often associated with dental complications, such as multiple supernumerary teeth and permanent teeth impaction or delayed eruption. METHODS: Supernumerary teeth of axial, sagittal and coronal CBCT view was characterized in detail and 3D image reconstruction was performed. Number and location of teeth, morphology of supernumerary teeth, positional relationship between supernumerary and adjacent permanent teeth, direction of supernumerary teeth in CCD patients were analyzed. RESULTS: The mean age of the 3 CCD patients in this study was 16.7 years. Among 36 supernumerary teeth, the majority of them were identified as apical side located and lingual side located. Normal orientation was the most common type in this study, followed by sagittal orientation, and horizontal orientation. Horizontal orientation teeth were all distributed in the mandible. Supernumerary teeth exhibited significantly shorter crown and dental-root lengths, as well as smaller crown mesiodistal and buccolingual diameters (P < 0.01). There was no difference in the number of supernumerary teeth between the maxilla and mandible, and the premolars region had the largest number of supernumerary teeth and the incisor region had the smallest number. CONCLUSIONS: This study compares number and location of teeth, morphology of supernumerary teeth, positional relationship between supernumerary and adjacent permanent teeth and direction of supernumerary teeth, this study also provides a reference for the comprehensive evaluation of CCD patients before surgery.

Building a super-resolution fluorescence cryomicroscope.

Correlated super-resolution fluorescence microscopy and cryo-electron microscopy enables imaging with both high labeling specificity and high resolution. Naturally, combining two sophisticated imaging techniques within one workflow also introduces new requirements on hardware, such as the need for a super-resolution fluorescence capable microscope that can be used to image cryogenic samples. In this chapter, we describe the design and use of the "cryoscope"; a microscope designed for single-molecule localization microscopy (SMLM) of cryoEM samples that fits right into established cryoEM workflows. We demonstrate the results that can be achieved with our microscope by imaging fluorescently labeled vimentin, an intermediate filament, within U2OS cells grown on EM grids, and we provide detailed 3d models that encompass the entire design of the microscope.