3D Computed Tomography Research Articles

Synthesizing human brain CT images from MRI with deep learning

Rapid development of artificial intelligence techniques significantly promotes important medical imaging applications such as disease diagnosis, medical image analysis and cross-modality synthesis. It is valuable to synthesize Computed Tomography (CT) scans of human brains from Magnetic Resonance Imaging (MRI) scans because CT images contain particular information for diseases such as malignant tumors, cerebrovascular malformations and aneurysms. Although there has been many studies trying to apply machine learning methods (e.g., fully convolutional neural networks and generative adversarial networks) to predict CT images based on MRI, there are still opportunities to increase the quality of synthesized CT images using the latest machine learning algorithms. In this study, we aim to synthesize high-credibility human brain CT images from MRI images using machine learning approaches. We build a dataset of both CT and MRI images of 41 patients from The Cancer Imaging Archive. A data pre-processing pipeline is designed to guarantee that the processed images are suitable as inputs to machine learning algorithms. The pipeline includes (1) pairing MRI and CT scans according to a certain time interval between CT and MRI exams of the same patient, (2) registering all MRI images to a standard MRI template, (3) registering all CT images to paired MRI images, (4) intensity normalization and (5) extracting 2D slices from 3D CT and MRI volumes. Three deep neural networks with encoder–decoder structure are selected and implemented including U-Net, U-Net++ and pix2pix to synthesize human brain CT images from MRI images. Experimental results illustrate that U-Net++ shows better performance than U-Net and pix2pix in synthesizing CT images from MRI by achieving a Mean Squared Error of 0.025, a Mean Absolute Error of 0.082 and a Peak Signal-to-Noise Ratio of 67.90, respectively. The trained machine learning models from this work can be applied in future human brain CT image prediction where CT images are absent and MRI images are available for specific patients, thereby supporting disease diagnosis based on CT images.

Distal Clavicle Autograft Versus Traditional and Congruent Arc Latarjet Procedures: A Comparison of Surface Area and Glenoid Apposition With 3-Dimensional Computed Tomography and 3-Dimensional Magnetic Resonance Imaging

Background: Limited studies have compared graft-glenoid apposition and glenoid augmentation area between the Latarjet procedure and distal clavicle graft in glenohumeral stabilization. Additionally, preoperative planning is typically performed using computed tomography (CT), and few studies have used 3-dimensional (3D) magnetic resonance imaging (MRI) reformations to assess graft dimensions. Purpose: The purpose of this study was 2-fold: (1) to compare bony apposition, glenoid augmentation, and graft width among coracoid and distal clavicle bony augmentation techniques and (2) to determine the viability of 3D MRI to assess bone graft dimensions. Study Design: Controlled laboratory study. Methods: A total of 24 patients with recurrent glenohumeral instability and bone loss were included in this study. 3D CT and 3D MRI reformations were utilized to measure pertinent dimensions for 5 orientations of coracoid and distal clavicle autografts: (1) standard Latarjet procedure (SLJ), (2) congruent arc Latarjet procedure (CLJ), (3) distal clavicle attached by its posterior surface (DCP), (4) distal clavicle attached by its inferior surface (DCI), and (5) distal clavicle attached by its resected end (DCR). Glenoid augmentation was defined as the graft surface area contributing to the glenoid. Bone-on-bone apposition was defined as the graft-glenoid contact area for bone healing potential, and graft width was pertinent for fixation technique. Glenoid bone loss ranged from 0% to 34%. Paired t tests were used to compare graft sizes between patients and compare 3D CT versus 3D MRI measurements. Results: The CLJ had the largest graft surface area (mean, 318.41 ± 74.44 mm2), while the SLJ displayed the most bone-on-bone apposition (mean, 318.41 ± 74.44 mm2). The DCI had the largest graft width (mean, 20.62 ± 3.93 mm). Paired t tests revealed no significant differences between the Latarjet techniques, whereas distal clavicle grafts varied significantly with orientation. All 3D CT and 3D MRI measurements were within 1 mm of each other, and only 2 demonstrated a statistically significant difference (coracoid width: 13.03 vs 13.98 mm, respectively [P = .010]; distal clavicle thickness: 9.69 vs 10.77 mm, respectively [P = .002]). 3D CT and 3D MRI measurements demonstrated a strong positive correlation (r > 0.6 and P < .001 for all dimensions). Conclusion: Glenoid augmentation, bony apposition, and graft width varied with coracoid or distal clavicle graft type and orientation. Differences between 3D CT and 3D MRI were small and likely not clinically significant. Clinical Relevance: 3D MRI is a viable method for preoperative planning and graft selection in glenoid bone loss.

Obstetric pelvimetry by three-dimensional computed tomography in non-pregnant Japanese women: a retrospective single-center study

Objective While a basic understanding of pelvic size and typology is still important for obstetricians, pelvic measurement data for Japanese women are very scarce. To our best knowledge, no large-scale pelvimetry studies of Japanese women have been made for the past 50 years. This study aimed to investigate the accurate size, particularly the obstetric conjugate (OC) and transverse diameter of the pelvic inlet (TD), of modern Japanese women, using three-dimensional (3D) computed tomography (CT), and to obtain their reference values. Methods This retrospective, single-center observational study enrolled Japanese non-pregnant women aged between 20 and 40 years, who underwent pelvic CT examination from 2016 to 2021. CT was performed for various reasons, including acute abdomen, search for cancer metastases, and follow-up of existing disease. However, no cases were taken for pelvic measurements. Pelvimetry was performed retrospectively using a 3D workstation. The OC was measured on a strict lateral view and the TD was measured on an axial-oblique view. Other clinical data, such as age, height, and weight, were also extracted from the medical charts and analyzed. Results A total of 1,263 patients were enrolled, with the mean age of 32.7 years (standard deviation [SD] 6.2). The mean height, weight, and body mass index were 158.8 cm (SD 5.8), 54.8 kg (SD 11.7), and 21.7 kg/m2 (SD 4.4), respectively. The mean OC length was 127.0 mm (SD 9.5, 95% confidence interval [CI] 126.5–127.5), while the mean TD length was 126.8 mm (SD 7.5, 95% CI 126.4–127.2). Both values were normally distributed. Height was significantly associated with OC (regression coefficient = 0.75 [95% CI 0.66–0.84], p < .001) and TD (regression coefficient = 0.63 [95% CI 0.56–0.70], p < .001). Age showed a weak but statistically significant positive association with TD (regression coefficient = 0.14 [95% CI 0.07–0.20], p < .001) and OC (regression coefficient = −0.10 [95% CI −0.18 to −0.01], p = .026). Conclusion The 3D CT pelvimetry in 1,263 non-pregnant Japanese women of childbearing age revealed the mean OC and TD of 127.0 mm, and 126.8 mm, which were 11.8 mm and 4.3 mm larger, respectively, than those in the survey in 1972. Our data will be referred to in clinical practice as the standard pelvic measurement values for the Japanese population.

Postoperative femoral component rotation using posterior condylar referencing is difficult to predict preoperatively in total knee arthroplasty

BackgroundMany modern total knee arthroplasty (TKA) systems use posterior condylar axis (PCA) to derive the surgical trans-epicondylar axis (sTEA), which is widely regarded as the gold standard for femoral component rotation. However, the previous imaging studies showed that cartilage remnants can alter component rotation. We therefore conducted this study to determine how the postoperative femoral component rotation deviated from the preoperative plan using three-dimensional (3D) computed tomography (CT) which does not consider cartilage thickness. MethodsA total of 123 knees of 97 consecutive osteoarthritis patients who underwent the same primary TKA system using PCA reference guide were included. External rotation was set at 3°or 5° according to the preoperative 3D CT plan. The number of varus knees (hip–knee–ankle (HKA) angle >5° varus) and valgus knees (HKA >5° valgus) were 100 and 5, respectively. The deviation from the preoperative plan was measured using overlapping pre- and postoperative 3D CT images. ResultsThe mean (standard deviation, range) deviation from the preoperative plan in varus group, external rotation setting of 3°, 5° in varus group and valgus group were 1.3° (1.9°, −2.6° − 7.3°), 1.0° (1.6°, −2.5° − 4.8°), 3.3° (2.3°, −1.2° − 7.3°), and −0.8° (0.8°, −2.0°−0.0°), respectively. No correlation was found between the deviation from the plan and the preoperative HKA angle in varus group (R = 0.15, P = 0.15). ConclusionsThe effect of asymmetric cartilage wear for rotation in the present study was supposed to be approximately 1° as mean value, but it can vary widely from patient to patient.

A Retrospective Study on Profile of Patients with Faciomaxilary Fractures in a Tertiary Care Center.

Maxillofacial injuries in general occur quite commonly following trauma and these injuries if not properly managed can negatively influence both the psychosocial and functional activities of the patient. This is as a result of the centrality of the facial region as a key factor in human identity, aesthetics, and general well-being. Fractures involving the facial skeleton may be isolated or complex. High velocity trauma is usually seen in urban and semi-urban areas while low velocity trauma is the common setting in rural areas. The pattern of faciomaxillary fractures vary with geographical area, socioeconomic condition, enforcements of law and order of a country. Trauma to the faciomaxillary region mandates special attention as important sensory systems are contained within the face (e.g. vision, auditory, somatic sensation, gustatory, olfaction and vestibular), also, vital structures in the head and neck region are intimately associated (airway, blood vessels, nerves and gastrointestinal tracts. It should be noted that the treatment outcome of maxillofacial fractures is mainly dependent among other things on the degree of injury, type of fracture, the expertise of the surgeon, and available technology. The aim of this study is to find out the incidence of faciomaxillary injuries resulting from various etiological factor Classification of facial bone fractures; Diagnosis and different treatment modalities. This is a prospective cross sectional study comprising of 75 patients who were having different faciomaxillary fractures and visited to L.G. hospital from December 2020 to April 2022. Patients were evaluated thoroughly by history taking, proper examination and routine investigations. In general examination consciousness, orientation to time, place and person, neck movements, and general mobility of the patients were checked. In local examination- facial oedema, facial asymmetry, skin lacerations, deep cuts, decreased mouth opening, improper teeth occlusion, teeth loss, nasal bleeding, black eye, eyeball movements and redness of eyes were checked. In specialized radiological investigations x- rays, 2D & 3D Computed Tomography (CT) of Facial bones were done in all cases. CT Brain and CT Cervical spine were done in patients if needed. From our study, it seems reasonable to assume that road traffic accident remains the leading cause of faciomaxillary fractures and is closely followed by fall especially among men in their productive years. It is necessary to diagnose faciomaxillary fracture at the earliest to prevent the complications of fractures such as infection and malocclusion, for that thorough clinical examination and radiological investigations are very important. 3D CT face is the gold standard investigation in case of different faciomaxillary fractures. In isolated fractures nasal bone fractures remains the most affected bone of the facial skeleton followed by mandible. Among the different sites of mandibular fractures body of the mandible is the most common site for mandibular fractures.

Comparison of the accuracy of intraoperative lateral fluoroscopy versus postoperative computed tomography in spinal fusions.

This study compared the accuracy of intraoperative lateral fluoroscopic images versus postoperative computed tomography (CT) 3D studies in the treatment of thoracolumbar spinal fusions. In a tertiary care hospital (study duration 6 months), we compared the use of lateral fluoroscopic images with the postoperative CT scans in 64 patients with thoracic or lumbar fractures undergoing spinal fusions. Out of the 64 patients, 61% were lumbar followed by 39% thoracic fractures. In the lumbar spine, the accuracy of screw placement utilizing lateral fluoroscopy versus postoperative CT 3D was 97.4%, while in thoracic spine, accuracy was reduced to 84.4%. Of the 64 patients, just 4 (6.2%) patients demonstrated lateral pedicle cortex penetration, 1 (1.5%) patient had a medial pedicle cortex breach, while none exhibited anterior vertebral body cortex penetration. This study documented the efficacy of lateral fluoroscopy in intraoperative thoracic and lumbar spinal fixation as confirmed by postoperative CT 3D studies. These findings support the continued use of fluoroscopy rather than CT intraoperatively to lower the risk of radiation exposure to both patients and surgeons.

Preoperative Mixed-Reality Visualization of Complex Tibial Plateau Fractures and Its Benefit Compared to CT and 3D Printing.

Various studies have shown the benefit of three-dimensional (3D) computed tomography (CT) reconstruction and especially 3D printing in the treatment of tibial plateau fractures (TPFs). This study aimed to investigate whether mixed-reality visualization (MRV) using mixed-reality glasses can provide a benefit for CT and/or 3D printing in planning treatment strategies for complex TPFs. Three complex TPFs were selected for the study and processed for 3D imaging. Subsequently, the fractures were presented to specialists in trauma surgery using CT (including 3D CT reconstruction), MRV (hardware: Microsoft HoloLens 2; software: mediCAD MIXED REALITY) and 3D prints. A standardized questionnaire on fracture morphology and treatment strategy was completed after each imaging session. 23 surgeons from 7 hospitals were interviewed. A total of 69.6% (n = 16) of those had treated at least 50 TPFs. A change in fracture classification according to Schatzker was recorded in 7.1% of the cases and in 78.6% an adjustment of the ten-segment classification was observed after MRV. In addition, the intended patient positioning changed in 16.1% of the cases, the surgical approach in 33.9% and osteosynthesis in 39.3%. A total of 82.1% of the participants rated MRV as beneficial compared to CT regarding fracture morphology and treatment planning. An additional benefit of 3D printing was reported in 57.1% of the cases (five-point Likert scale). Preoperative MRV of complex TPFs leads to improved fracture understanding, better treatment strategies and a higher detection rate of fractures in posterior segments, and it thus has the potential to improve patient care and outcomes.

Three Zone Scanning Protocol For Lung Ultrasound: An Anatomical Basis.

Lung ultrasound is rapidly gaining popularity based on point of care ease of use, diagnostic fidelity and lack of ionizing radiation. This was particularly notable at the beginning of the COVID-19 pandemic, where concerns of contamination of the x-ray department led to a reluctance to order frequent chest x-rays. Early COVID-19 lung involvement is of a bronchopneumonia, and patches of consolidation adjacent to the chest wall were easily detectable by ultrasound. A large number of proposed scanning protocols were advocated and are often complex and largely based on traditional stethoscope examination or access points on the chest wall rather than the underlying lung anatomy. A surgical understanding of lung anatomy and related surface anatomy has led us to develop a simplified three zone scanning protocol in 2013. The anterior zone corresponds to the upper lobe, and the posterior zone is divided between upper lobe and lower lobe. The relationship between lung lobes and the surface of the chest wall provides the anatomical basis for a simple three scanning zone lung ultrasound protocol.

Detection &amp; Quantification of Lung Nodules Using 3D CT images

In computer vision image detection and quantification play an important role. Image Detection and quantification is the process of identifying nodule position and the amount of covered area. The dataset which we have used for this research contains 3D CT lung images. In our proposed work we have taken 3D images and those are high-resolution images. We have compared the accuracy of the existing mask and our segmented images. The segmentation method that we have applied to these images is Sparse Field Method localized region-based segmentation and for Nodule detection, I have used ray projection. The ray projection method is efficient for making the point more visible by its x, y, and z components. like a parametric equation where the line crossing through a targeted point by that nodule is more dominated. The Frangi filter was to give a geometric shape to the nodule and we got 90% accurate detection. The high mortality rate associated with lung cancer makes it imperative that it be detected at an early stage. The application of computerized image processing methods has the potential to improve both the efficiency and reliability of lung cancer screening. Computerized tomography (CT) pictures are frequently used in medical image processing because of their excellent resolution and low noise. Computer-aided detection systems, including preprocessing and segmentation methods, as well as data analysis approaches, have been investigated in this research for their potential use in the detection and diagnosis of lung cancer. The primary objective was to research cutting-edge methods for creating computational diagnostic tools to aid in the collection, processing, and interpretation of medical imaging data. Nonetheless, there are still areas that need more work, such as improving sensitivity, decreasing false positives, and optimizing the identification of each type of nodule, even those of varying size and form.

Topologically preserved registration of 3D CT images with deep networks

Objective. Computed Tomography (CT) image registration makes fast and accurate imaging-based disease diagnosis possible. We aim to develop a framework which can perform accurate local registration of organs in 3D CT images while preserving the topology of transformation. Approach. In this framework, the Faster R-CNN method is first used to detect local areas containing organs from fixed and moving images whose results are then registered with a weakly supervised deep neural network. In this network, a novel 3D channel coordinate attention (CA) module is introduced to reduce the loss of position information. The image edge loss and the organ labelling loss are used to weakly supervise the training process of our deep network, which enables the network learning to focus on registering organs and image structures. An intuitive inverse module is also used to reduce the folding of deformation field. More specifically, the folding is suppressed directly by simultaneously maximizing forward and backward registration accuracy in the image domain rather than indirectly by measuring the consistency of forward and inverse deformation fields as usual. Main results. Our method achieves an average dice similarity coefficient (DSC) of 0.954 and an average Similarity (Sim) of 0.914 on publicly available liver datasets (LiTS for training and Sliver07 for testing) and achieves an average DSC of 0.914 and an average Sim of 0.947 on our home-built left ventricular myocardium (LVM) dataset. Significance. Experimental results show that our proposed method can significantly improve the registration accuracy of organs such as the liver and LVM. Moreover, our inverse module can intuitively improve the inherent topological preservation of transformations.

Quantitative analysis of the innominate bone for sex estimation utilising the Phenice method

BackgroundThe Phenice method is a reliable qualitative analysis of the pubis and ischium region of the innominate bone to assess an individual’s sex. Geometric morphometric provides methods of quantitative analysis of the region for identification purposes, which may be affected by environmental changes. This study analysed the Phenice method by utilising 3D (3 dimensional) CT (computed tomography) scans by geometric morphometrics for sex estimation. The CT scans of 231 adult individuals (148 males and 83 females) of the Malaysian population were landmarked by IDAV Landmark software and analysed by MorphoJ and SPSS.ResultsThe first four principal components (PCs) accounted for 41.9% of the total changes when utilising the Phenice method. Widening in pubic symphysis in a U shape with a general widening of the border of the true pelvis, which is typically seen in females, accounted for 21.8% of the eigenvalues.ConclusionsIt was possible to quantify the changes seen in the ventral arc, subpubic concavity and the medial aspect of the ischio-pubic ramus for sex estimation utilising the Phenice method, and most of the changes were seen in PC1 at the pubic region, which accounted for 21.8%.

Fractured morphology of femoral head associated with subsequent femoral neck fracture: Injury analyses of 2D and 3D models of femoral head fractures with computed tomography.

Background: The injury of femoral head varies among femoral head fractures (FHFs). In addition, the injury degree of the femoral head is a significant predictor of femoral neck fracture (FNF) incidence in patients with FHFs. However, the exact measurement methods have yet been clearly defined based on injury models of FHFs. This study aimed to design a new measurement for the injury degree of the femoral head on 2D and 3D models with computed tomography (CT) images and investigate its association with FHFs with FNF. Methods: A consecutive series of 209 patients with FHFs was assessed regarding patient characteristics, CT images, and rate of FNF. New parameters for injury degree of femoral head, including percentage of maximum defect length (PMDL) in the 2D CT model and percentage of fracture area (PFA) in the 3D CT-reconstruction model, were respectively measured. Four 2D parameters included PMDLs in the coronal, cross-sectional and sagittal plane and average PMDL across all three planes. Reliability tests for all parameters were evaluated in 100 randomly selected patients. The PMDL with better reliability and areas under curves (AUCs) was finally defined as the 2D parameter. Factors associated with FNF were determined by binary logistic regression analysis. The sensitivity, specificity, likelihood ratios, and positive and negative predictive values for different cut-off values of the 2D and 3D parameters were employed to test the diagnostic accuracy for FNF prediction. Results: Intra- and inter-class coefficients for all parameters were ≥0.887. AUCs of all parameters ranged from 0.719 to 0.929 (p < 0.05). The average PMDL across all three planes was defined as the 2D parameter. The results of logistic regression analysis showed that average PMDL across all three planes and PFA were the significant predictors of FNF (p < 0.05). The cutoff values of the average PMDL across all three planes and PFA were 91.65% and 29.68%. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, predictive positive value and negative predictive value of 2D (3D) parameters were 91.7% (83.3%), 93.4% (58.4%), 13.8 (2.0), 0.09 (0.29), 45.83% (10.87%), and 99.46% (98.29%). Conclusion: The new measurement on 2D and 3D injury models with CT has been established to assess the fracture risk of femoral neck in patients with FHFs in the clinic practice. 2D and 3D parameters in FHFs were a feasible adjunctive diagnostic tool in identifying FNFs. In addition, this finding might also provide a theoretic basis for the investigation of the convenient digital-model in complex injury analysis.

AI-Driven Robust Kidney and Renal Mass Segmentation and Classification on 3D CT Images.

Early intervention in kidney cancer helps to improve survival rates. Abdominal computed tomography (CT) is often used to diagnose renal masses. In clinical practice, the manual segmentation and quantification of organs and tumors are expensive and time-consuming. Artificial intelligence (AI) has shown a significant advantage in assisting cancer diagnosis. To reduce the workload of manual segmentation and avoid unnecessary biopsies or surgeries, in this paper, we propose a novel end-to-end AI-driven automatic kidney and renal mass diagnosis framework to identify the abnormal areas of the kidney and diagnose the histological subtypes of renal cell carcinoma (RCC). The proposed framework first segments the kidney and renal mass regions by a 3D deep learning architecture (Res-UNet), followed by a dual-path classification network utilizing local and global features for the subtype prediction of the most common RCCs: clear cell, chromophobe, oncocytoma, papillary, and other RCC subtypes. To improve the robustness of the proposed framework on the dataset collected from various institutions, a weakly supervised learning schema is proposed to leverage the domain gap between various vendors via very few CT slice annotations. Our proposed diagnosis system can accurately segment the kidney and renal mass regions and predict tumor subtypes, outperforming existing methods on the KiTs19 dataset. Furthermore, cross-dataset validation results demonstrate the robustness of datasets collected from different institutions trained via the weakly supervised learning schema.

Correlation of suprascapular notch morphology with suprascapular nerve palsy: a 3D-computed tomography study

The morphology of the suprascapular (SS) notch is a very important factor in treatment of suprascapular nerve (SSN) palsy. Several studies have reported SS notch morphology in cadavers or using a three-dimensional computed tomography (3D-CT); however, none has reported the distribution of SS notch morphology according to the age group. In addition, the correlation between SS notch morphology and SSN palsy remains unclear. The purposes of this study were to investigate the morphological distribution of the SS notch by age group in a large population and to assess the relationship between SS notch morphology and SSN palsy. We studied the 3D-CT images of 1063 shoulders in 1009 patients (mean age, 60.8 years; age range, 14-96 years). There were 53 shoulders with SSN palsy and 1010 shoulders without SSN palsy. Morphology of the SS notch was classified by Rengachary's classification (types I-VI). Shoulders with types I-IV were classified into the nonossified superior transverse scapular ligament (STSL) group (group N) and those with types V and VI into the ossified STSL group (group O). The Rengachary's classifications of the 1063 shoulders were as follows: type I: n=113, 10.6%; type II: n=313, 29.4%; type III: n=383, 36.0%; type IV: n=109, 10.3%; type V: n=107, 10.0%; and type VI: n=38, 3.6%. Mean age was significantly older in the ossified STSL group, and the age was <40 years for only two shoulders in this group. The Rengachary's classifications of the SSN palsy cases were as follows: type I: 7.5%, II: 24.5%, III: 34.0%, IV: 15.1%, V: 13.2%, and VI: 5.7%. There was no statistical difference in age and sex, Rengachary type, or ossification between SSN palsy and non-SSN palsy cases. Ossification of the STSL was significantly more common in older patients, which suggests age-related change. In addition, no relation was identified between narrow notch or ossification of the STSL with the onset of SSN palsy.

A Demographic Survey of Pertrochanteric Fractures Based on the Revised Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association (AO/OTA) Classification Using 3D CT Scan Images.

Introduction A demographic survey of femoral pertrochanteric fractures provides several important information for the healthcare system of a country since this fracture is commonly seen in the elderly and has a poor postoperative functional prognosis that is a burden on society. The importance of accurately classifying pertrochanteric fractures as stable or unstable cannot be understated. However, the use of plain radiograph images alone is known to underestimate fracture severity with low inter- or intra-observer agreement. Computedtomography (CT) images offer information for a more accurate classification of pertrochanteric fractures. With this three-dimensional (3D) CT-based study using the revised Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association (AO/OTA) classification, the purpose of this study is to elucidate the epidemiological demography of patients with pertrochanteric fractures. Material and methods We retrospectively collected 808 patients from five hospitals, classified into two groups: stable (A1) or unstable (A2). Age, gender, fracture laterality, and surgerytiming were identified as epidemiological variables. Patients with both preoperative plain radiographs and 3D CT scans were included in the study. The exclusion criteria were AO/OTA A3 type fractures, pathological fractures, previous ipsilateral surgery, 60 years old or younger, and conservatively treated patients. The primary outcome involved detailing the total number of fractures based on classification (A1 or A2) and variables. The secondary outcome involved a comparison between the A1 and A2 groups. Results The mean age of patients at the time of surgery was 85 years (range: 61-103 years). There were 637 female and 171 male patients. There were 463 left-sided fractures and 345 right-sided fractures. Of the 808 patients, 371 (45.9%) were classified to have A1 fractures, and 437 (54.1%) had A2 fractures. The age at surgery, gender, fracture laterality, and surgerytiming between the A1 and A2 groups were compared. The mean and standard deviation of the age at surgery for patients in the A1 and A2 groups were 84.9±7.7 and 86.9±6.8, respectively. The number of patients for each age distribution of 61-69, 70-74, 75-79, 80-84, 85-89, 90-94, and 95 or older for the A1 and A2 groups was 18 and 7, 18 and 12, 43 and 44, 76 and 82, 107 and 132, 79 and 110, and 30 and 50, respectively, showing that the difference in categorial distribution was statistically significant (p=0.002). Overall, 278 females and 93 males were classified to have A1 fractures compared with 359 females and 78 males with A2 fractures (p=0.01). There were 166 right-sided and 205 left-sided stable A1 fractures and 179 right-sidedand 258 left-sided A2 fractures (not significant (NS)). Among the total number of A1 and A2 surgeries by month, the most were in December with 77 surgeries(37 and 40, respectively), and the least was in June with 37 (18 and 19, respectively). The seasonal classification for A1 and A2 surgeries is as follows: spring with 172 (74 and 98, respectively), summer with 150 (70 and 80, respectively), autumn with 193 (90 and 103, respectively), and winter with 208 (97 and 111, respectively) (NS). Conclusion In this demographic study of 808 patients with pertrochanteric fractures classified by 3D CT images, 371 had A1 fractures and 437 had A2 fractures. A2 fractures were significantly more in females with an age peak of 85-89 years.

Application value of computed tomography and magnetic resonance imaging three-dimensional reconstruction and digital subtraction angiography in percutaneous transhepatic cholangial drainage.

This study aims to explore the application value of computed tomography (CT) three-dimensional (3D) reconstruction, magnetic resonance imaging (MRI) 3D reconstruction, and conventional digital subtraction angiography (DSA) fluoroscopy in percutaneous transhepatic cholangial drainage (PTCD). The clinical data of 180 patients with obstructive jaundice requiring PTCD from December 2017 to December 2021 were retrospectively analyzed. Following PTCD, CT 3D reconstruction, MRI 3D reconstruction, and conventional DSA fluoroscopy were conducted, after which the surgical success rates, liver function results, and postsurgical complications were compared. The puncture accuracies under CT 3D reconstruction, MRI 3D reconstruction, and conventional DSA fluoroscopy were 90.0% (54/60), 96.7% (58/60), and 80% (48/60), respectively. The degree of jaundice and epigastric discomfort was relieved in all three groups after surgery, while a significant reduction in the levels of total bilirubin and direct bilirubin was observed relative to the levels before surgery (P < 0.05). The incidences of complications in the CT 3D reconstruction, MRI 3D reconstruction, and conventional DSA fluoroscopy groups were 6.7% (4/60), 3.3% (2/60), and 13.3% (8/60), respectively, and the differences among the three groups were statistically significant (P < 0.05). Conducting conventional enhanced CT and MRI scans in patients before surgery might be more practical than the conventional puncture method. Among the methods under study, MRI 3D reconstruction was found to be safer and more feasible than CT 3D reconstruction and conventional DSA fluoroscopy in PTCD. MRI 3D reconstruction could reduce the degree of jaundice, improve the success rate of surgery, reduce the incidence of complications due to surgery, and improve the patients' tolerance to surgery.

Development of a navigable 3D virtual model of temporal bone anatomy

Background Computed Tomography (CT) scanning offers an accurate structural definition of bones, blood vessels, and soft tissues; however, mental integration of cross-sectional 2D CT images for a 3D understanding of complex anatomical structures becomes difficult when the field of view is confined to the temporal bone. This project tried to provide a feasible solution to this problem by creating a navigable 3D virtual model which may aid in better comprehension of the temporal bone anatomy. Methods A helical-CT scan was used to obtain high-resolution cross-sectional slices of a cadaveric human temporal bone. Using the volume-rendering capabilities of 3D Slicer®, which involves volume data management, cropping of the data set, and threshold painting, detailed anatomical structures were segmented based on the intensity captured from different regions. This volumetric data was converted to an interactive virtual model using Blender®. Results The final product is a web page that allows interaction and navigation with a 3D annotated model of the temporal bone, which can be accessed from any device with a web browser. Conclusion This model can function as a training tool for students, teachers, and practitioners to understand and review the complex anatomy of the temporal bone.

3D CT scan—A valuable adjunct to radiography

Abstract Background: Deformity correction is based on Full-length True Antero-Posterior and Lateral radiographs. However, a 3D computed tomography (CT) Scan provides a more intricate and detailed understanding of the deformities, so as to plan for the correction with utmost precision. Objective: To prove that 3D computed tomography (CT) Scan provides a more intricate and detailed understanding of the deformities. Materials and Methods: A series of 107 cases, studied from 2017, for a period of 5 years, at our institute was done by means of 3D CT scan. Evaluation was done by measuring angles and lines for further deformity correction, especially in the complex rotational deformities; and osteotomies were performed with Ilizarov fixation. 3D printing was done in selected cases. The patient was made to walk in the immediate postoperative period. The Hexapods were tuned as per the calculations made on the SUV software, for gradual correction. Results: The greatest advantage of using 3D CT is a visualization of the minute details. This may alter the number of osteotomies needed. Eventually, this aids in better correction, when compared with a normal X-ray scannogram. Precision of up to 0.001° was achieved with the DICOM images obtained upon doing the 3D CT, in our study. Conclusion: The information on the deformity in sagittal, frontal, and rotational planes is obtained by doing a 3D CT scan, which allows for further precise planning of the correction. And, as a matter of fact, many Orthopedic Surgeons do not attempt deformity correction as they do not have access to proper full-length X-ray scannograms. Our method gives a precise, cheap, and easily available full-length picture of the deformity, with many more advantages.

Interpretable vertebral fracture quantification via anchor-free landmarks localization.

Vertebral body compression fractures are early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by radiologists in clinical settings. Prior research on automatic methods of vertebral fracture classification proves its reliable quality; however, existing methods provide hard-to-interpret outputs and sometimes fail to process cases with severe abnormalities such as highly pathological vertebrae or scoliosis. We propose a new two-step algorithm to localize the vertebral column in 3D CT images and then detect individual vertebrae and quantify fractures in 2D simultaneously. We train neural networks for both steps using a simple 6-keypoints based annotation scheme, which corresponds precisely to the current clinical recommendation. Our algorithm has no exclusion criteria, processes 3D CT in 2 seconds on a single GPU, and provides an interpretable and verifiable output. The method approaches expert-level performance and demonstrates state-of-the-art results in vertebrae 3D localization (the average error is 1mm), vertebrae 2D detection (precision and recall are 0.99), and fracture identification (ROC AUC at the patient level is up to 0.96). Our anchor-free vertebra detection network shows excellent generalizability on a new domain by achieving ROC AUC 0.95, sensitivity 0.85, specificity 0.9 on a challenging VerSe dataset with many unseen vertebra types.

Evaluating three-dimensional lung reconstructions for thoracoscopic lung resections using open-source software: a pilot study.

Preoperative three-dimensional (3D) lung reconstructions can reduce intraoperative blood loss, conversion rate, and operation duration. These 3D reconstructions are predominantly provided by commercial expensive products, hence we aimed to assess the usability and performance of preoperative 3D lung reconstructions created with open-source software. Patients were invited to participate in this prospective pilot study if they were planned for uniportal video-assisted thoracoscopic surgery (VATS) lobectomy or segmentectomy between January and February 2023. Participants were excluded if a two-dimensional (2D) late-arterial-phase computed tomography (CT) scan contained motion artifacts, another surgical procedure was performed, or the surgery was canceled. After informed consent was obtained, 3D lung reconstructions were constructed using open-source 3D Slicer software. The system usability score (SUS) questionnaire assessed the usability of these reconstructions, whilst performance was evaluated based on anatomical validity compared to prior 2D CT assessment as well as operative findings. Descriptive statistics were reported. Thirteen patients were included, of whom one underwent a segmentectomy. Eighty-three percent of the 3D lung reconstructions scored above average (SUS >68). Compared to 2D CT scans, 38% of lung nodule segmental locations were detected more accurately through 3D lung reconstructions. Furthermore, 3D lung reconstructions revealed anatomical variations in 62%, which were not recognized on 2D CT scans, and provided surgeons with insights that would change the procedure and/or transection planes in 62%. One 3D lung reconstruction failed to demonstrate an intraoperative recognized segmental pulmonary artery (A6) branch. Three-dimensional lung reconstructions created with open-source software were usable and effective for uniportal VATS anatomical resections. ClinicalTrials.gov/NCT06132607.