Network-Regularized Diffusion Sampling For 3D Computed Tomography

Complex maxillofacial fractures demand a detailed understanding of the three-dimensional (3D) pattern of injury. Evaluation of the outcome of the facial fracture repair additionally requires optimal demonstration of fracture gap, bony union, fibrous callus or incorporation of fracture ends, presence of incomplete fusion, or pseudoarthrosis. Although 3D computed tomography (CT) is reliably used for the diagnosis of complex facial fractures, its value in facial fracture healing is unknown. An experimental study was conducted to determine the accuracy of 3D spiral CT scans in evaluating facial fracture healing during the early and late postoperative periods. In 10 adult Wistar Albino rats, a standardized bone defect (3 mm) was created within the mid portion of each zygomatic arch (n = 20). At 10 and 20 weeks postfracture, gap distance displayed by 3D CT and plane radiography (posteroanterior) were measured. At 20 weeks postfracture, intraoperative measurement was also performed. A comparison between 3D CT, radiography, and intraoperative findings was performed. At 10 weeks postfracture, the fracture sites displayed larger bone defects in imaging with 3D CT than with plane radiography. The difference between groups was statistically significant (P < 0.05). The mean defect size imaged by 3D CT was 0.91 +/- 0.82 mm (standard deviation) and by plane radiography was 0.42 +/- 0.16 mm. At 20 weeks postfracture, the mean defect size imaged by 3D CT was 0.56 +/- 0.64 mm, and by plane radiography was 0.38 +/- 0.22 mm. The difference between groups was not statistically significant (P > 0.05). The defect size imaged by both plane radiography and 3D CT was significantly less than the measurement obtained from the intraoperative assessment (P < 0.05). It was concluded that 3D CT has limited benefit in the detection of newly formed bone at week 10 and in the detection of fibrous callus, which can eventually give rise to the bony tissue. Plane radiography is more valid during the early postoperative period (week 10), because it can detect the fibrous callus and newly formed bone more precisely. Gap distance between fracture ends could be determined by 3D CT accurately at week 20, although there was a tendency, which was not statistically significant, to overestimate the amount of bone defect measured by 3D CT when compared with that of plane radiography.

Surgical stabilization of flail chest is increasingly recognized as a valid approach to improve pulmonary mechanics in selected trauma patients. The use of two-dimensional (2D) computed tomography (CT) has become almost universal in the assessment of blunt chest trauma and multiple rib fractures. We hypothesized that three-dimensional (3D) CT adds valuable information to the preoperative plan for fixation of rib fractures. Using a retrospective cohort of 35 consecutive adult patients with flail chest requiring surgery, we evaluated the intraobserver and interobserver reliability of plain radiographs, 2D CT and 3D CT, for the identification of rib fractures and identified how often the surgical plan changed with the addition of the information provided by the 3D CT. Two fellowship-trained orthopedic trauma surgeons who regularly operate on rib fractures in their clinical practice and were not involved in the treatment of the study population evaluated the radiographic data. Intraobserver and interobserver reliability was excellent for both 2D CT and 3D CT and was the highest for 2D CT. Overall, 2D CT had the highest diagnostic accuracy for detecting rib fractures as compared with plain radiographs and 3D CT. However, 3D CT changed the surgical tactic in 65.7% of the cases. We conclude that 3D CT is not as accurate as 2D CT for rib fracture diagnostic purposes; it seems to be an important tool for the preoperative planning of rib fracture fixation. Diagnostic study, level II.

Since the balance between the extent of liver resection and liver function is closely associated with postoperative morbidity and mortality, volumetric information is indispensable when deciding on the most appropriate liver resection procedure for hepatic tumors and any indications for portal embolization (PE), and when performing living-donor liver transplantation (LDLT). The extent of liver resection is usually evaluated by computed tomography (CT) volumetry using ­two-dimensional (2D) or three-dimensional (3D) CT images, both of which can calculate liver volume precisely. Furthermore, volumetry with 3D CT yields the total liver volume and automatically calculates the volumes of the territories of individual vessels (both portal vein branches and hepatic venous branches) from their diameters and lengths. Based on this volumetric data and liver function, the feasibility of a planned liver resection procedure can be decided. Any indications for PE in extended hemi-hepatectomy can also be evaluated. The volume of Couinaud’s segment can also be estimated by volumetry using 3D CT. Because ensuring the donor’s safety is of prime importance in LDLT, CT volumetry is routinely employed to assess the necessary graft size and determine whether an adequately sized graft can be procured. Furthermore, 3D CT volumetry can estimate the volume of congestion in the hepatic venous branch of the graft, which gives important information on which to base decisions regarding the reconstruction of the branch. Thus, CT volumetry is indispensable in hepatic surgery.

The intensities (i.e., number of protons in monitor unit [MU]) of deliverable proton spots need to be either zero or meet a minimum-MU (MMU) threshold, which is a nonconvex problem. Since the dose rate is proportionally associated with the MMU threshold, higher-dose-rate proton radiation therapy (RT) (e.g., efficient intensity modulated proton therapy (IMPT) and ARC proton therapy, and high-dose-rate-induced FLASH effect needs to solve the MMU problem with larger MMU threshold, which however makes the nonconvex problem more difficult to solve. This work will develop a more effective optimization method based on orthogonal matching pursuit (OMP) for solving the MMU problem with large MMU thresholds, compared to state-of-the-art methods, such as alternating direction method of multipliers (ADMM), proximal gradient descent method (PGD), or stochastic coordinate descent method (SCD). The new method consists of two essential components. First, the iterative convex relaxation (ICR) method is used to determine the active sets for dose-volume planning constraints and decouple the MMU constraint from the rest. Second, a modified OMP optimization algorithm is used to handle the MMU constraint: the non-zero spots are greedily selected via OMP to form the solution set to be optimized, and then a convex constrained subproblem is formed and can be conveniently solved to optimize the spot weights restricted to this solution set via OMP. During this iterative process, the new non-zero spots localized via OMP will be adaptively added to or removed from the optimization objective. The new method via OMP is validated in comparison with ADMM, PGD and SCD for high-dose-rate IMPT, ARC, and FLASH problems of large MMU thresholds, and the results suggest that OMP substantially improved the plan quality from PGD, ADMM and SCD in terms of both target dose conformality (e.g., quantified by max target dose and conformity index) and normal tissue sparing (e.g., mean and max dose). For example, in the brain case, the max target dose for IMPT/ARC/FLASH was 368.0%/358.3%/283.4% respectively for PGD, 154.4%/179.8%/150.0% for ADMM, 134.5%/130.4%/123.0% for SCD, while it was <120% in all scenarios for OMP; compared to PGD/ADMM/SCD, OMP improved the conformity index from 0.42/0.52/0.33 to 0.65 for IMPT and 0.46/0.60/0.61 to 0.83 for ARC. A new OMP-based optimization algorithm is developed to solve the MMU problems with large MMU thresholds, and validated using examples of IMPT, ARC, and FLASH with substantially improved plan quality from ADMM, PGD, and SCD.

Four-dimensional (4D) computed tomography (CT) ventilation imaging is a novel promising technique for lung functional imaging. The current standard 4D CT technique using phase-based sorting frequently results in artifacts, which may deteriorate the accuracy of ventilation imaging. The purpose of this study was to quantify the variability of 4D CT ventilation imaging due to 4D CT sorting. 4D CT image sets from nine lung cancer patients were each sorted by the phase-based method and anatomic similarity-based method, designed to reduce artifacts, with corresponding ventilation images created for each method. Artifacts in the resulting 4D CT images were quantified with the artifact score which was defined based on the difference between the normalized cross correlation for CT slices within a CT data segment and that for CT slices bordering the interface between adjacent CT data segments. The ventilation variation was quantified using voxel-based Spearman rank correlation coefficients for all lung voxels, and Dice similarity coefficients (DSC) for the spatial overlap of low-functional lung volumes. Furthermore, the correlations with matching single-photon emission CT (SPECT) ventilation images (assumed ground truth) were evaluated for three patients to investigate which sorting method provides higher physiologic accuracy. Anatomic similarity-based sorting reduced 4D CT artifacts compared to phase-based sorting (artifact score, 0.45 ± 0.14 vs 0.58 ± 0.24, p = 0.10 at peak-exhale; 0.63 ± 0.19 vs 0.71 ± 0.31, p = 0.25 at peak-inhale). The voxel-based correlation between the two ventilation images was 0.69 ± 0.26 on average, ranging from 0.03 to 0.85. The DSC was 0.71 ± 0.13 on average. Anatomic similarity-based sorting yielded significantly fewer lung voxels with paradoxical negative ventilation values than phase-based sorting (5.0 ± 2.6% vs 9.7 ± 8.4%, p = 0.05), and improved the correlation with SPECT ventilation regionally. The variability of 4D CT ventilation imaging due to 4D CT sorting was moderate overall and substantial in some cases, suggesting that 4D CT artifacts are an important source of variations in 4D CT ventilation imaging. Reduction of 4D CT artifacts provided more physiologically convincing and accurate ventilation estimates. Further studies are needed to confirm this result.

Purpose:To propose a new parallel‐friendly optimization algorithm, based on alternating direction method of multipliers (ADMM), for solving optimization problems emerging in treatment planning and imagingMethods:ADMM, emerging as a powerful tool for distributed optimization, is employed here for IMRT treatment planning. We modify the existing ADMM by integrating that with two optimization techniques known as Barzilai‐Borwein gradient method and line search. We apply original and integrated ADMM, with various penalty parameter values, on three IMRT treatment planning cases and we compare their performance. Each algorithm terminates once it found a solution within the relative error of 1E‐4 from the optimal solution. We also compare the performance of original and integrated ADMM against the commercial optimization software CPLEX.Results:Our experiments on three different cancer sites (prostate, head and neck, and GYN) indicate that integrated ADMM is much faster than original ADMM (5.8 times faster on average). Moreover, while the performance of original ADMM heavily depends on the selected penalty parameter, integrated ADMM performs very robust against the penalty parameter. Compared to the commercial software CPLEX, integrated ADMM turns out to be around 4–7 times faster.Conclusion:Integrated ADMM is a very efficient optimization algorithm to cope with the large‐scale optimization problems. It is a parallel‐friendly optimization algorithm and provides an idea platform for cloud‐based treatment planning and imaging.

Impact of two- and three-dimensional computed tomography use on intraobserver and interobserver reliabilities of pilon fracture classification and treatment recommendation

Ventral hernias are a surgical challenge, often requiring detailed imaging for surgical planning. Computed tomography (CT) is widely used in preoperative assessment, with three-dimensional (3D) reconstructions increasingly applied in surgical fields. This study aims to assess whether 3D CT reconstructions improve surgical planning compared to conventional two-dimensional (2D) CT. A cross-sectional survey was conducted from October 2024 to January 2025, enrolling 66 surgeons with diverse experience. Participants were randomized into two groups: one assessing a complex ventral hernia using conventional CT and the other using both 2D and 3D reconstructions. Data were collected through questionnaires based on the DECOMP criteria, surgeons' perception of hernia characteristics, surgical planning, and treatment strategies. Statistical analyses, including Fisher's exact test, Chi-square test, and ROC curve analysis, were performed to compare outcomes. No significant differences were found between the groups in the evaluation of the hernia, preoperative planning, or surgical approach. Surgeons predominantly relied on personal interpretation of CT scans rather than radiology reports. Notably, 3D reconstructions decreased the perception of hernia sac omental content (74.2% vs. 97.1%, p = 0.01). Furthermore, 3D visualization did not alter surgical decisions, including mesh selection, component separation, or preoperative techniques for loss of domain. 3D CT reconstructions do not impact the evaluation or surgical planning of complex ventral hernias compared to 2D CT. Although 3D imaging may enhance anatomical visualization, its clinical utility is unclear. Conventional 2D CT, when carefully analyzed, remains sufficient for surgical decision-making. Further research is needed to assess 3D imaging's benefits.

We are investigating image processing and analysis techniques to improve the ability of dual-energy digital radiography (DR) for the detection of cardiac calcification. Computed tomography (CT) is an established tool for the diagnosis of coronary artery diseases. Dual-energy digital radiography could be a cost-effective alternative. In this study, we use three-dimensional (3D) CT images as the "gold standard" to evaluate the DR X-ray images for calcification detection. To this purpose, we developed an automatic registration method for 3D CT volumes and two-dimensional (2D) X-ray images. We call this 3D-to-2D registration. We first use a 3D CT image volume to simulate X-ray projection images and then register them with X-ray images. The registered CT projection images are then used to aid the interpretation dual-energy X-ray images for the detection of cardiac calcification. We acquired both CT and X-ray images from patients with coronary artery diseases. Experimental results show that the 3D-to-2D registration is accurate and useful for this new application.

This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

The 320-slice computed tomography (CT) provides three-dimensional and dynamic imaging resulting in the ability to assess motion analysis between two adjacent structures (the fourth dimension). Differential movements between two adjacent structures would indicate that there is no fixation between the two structures. Eight patients with non-small-cell lung cancers located adjacent to vital structures (e.g. the great vessels) (n = 4), mediastinum (n = 1) or chest wall (n = 3) where conventional CT was unable to exclude local invasion underwent dynamic four-dimensional (4D) CT assessment. In 3 patients, the lung tumour was abutting the chest wall and 1 patient had tumour abutting the mediastinum. The remaining patients included a patient with a large 14-cm left lower lobe cancer abutting the descending thoracic aorta who had previous pleurodesis; a patient with an apical right upper lobe 6-cm cancer with static imaging appearances suggestive of tumour invasion into the apex, the mediastinal surface and superior vena cava (SVC); a patient with a 3.5-cm cancer which had a broad 2.5-cm base abutting the distal aortic arch and a patient with a 14-cm left upper lobe cancer abutting the aortic arch, descending thoracic aorta and chest wall. Differential movements between the tumour and adjacent structure on 4D CT were considered indicative of the absence of frank invasion. Dynamic 4D imaging revealed differential movements between the tumour and the adjacent structures in 7 cases, suggesting the absence of overt malignant invasion. Intraoperative assessments confirmed the findings. In 1 case, a small area of fixation seen on dynamic CT corresponded intraoperatively to superficial invasion of the adventitia of the SVC. Dynamic 4D 320-slice CT is useful in the preoperative assessment of the direct invasion of lung cancer into adjacent structures and hence its resectability.

A comparison of three-dimensional computed tomography scans and stereolithographic models for evaluation of craniofacial anomalies

The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve replacement (TPVR), vary considerably. Three-dimensional (3D) computed tomography (CT) imaging for device size prediction is insufficient to assess the displacement of the right ventricular outflow tract (RVOT) and PA, which could increase the risk of stent misplacement and paravalvular leak. The aim of this study is to provide a dynamic model to visualize and quantify the anatomy of the RVOT to PA over the entire cardiac cycle by four-dimensional (4D) cardiac CT reconstruction to obtain an accurate quantitative evaluation of the required valve size. In this pilot study, cardiac CT from sheep J was chosen to illustrate the procedures. 3D cardiac CT was imported into 3D reconstruction software to build a 4D sequence which was divided into eleven frames over the cardiac cycle to visualize the deformation of the heart. Diameter, cross-sectional area, and circumference of five imaging planes at the main PA, sinotubular junction, sinus, basal plane of the pulmonary valve (BPV), and RVOT were measured at each frame in 4D straightened models prior to valve implantation to predict the valve size. Meanwhile, dynamic changes in the RV volume were also measured to evaluate right ventricular ejection fraction (RVEF). 3D measurements at the end of the diastole were obtained for comparison with the 4D measurements. In sheep J, 4D CT measurements from the straightened model resulted in the same choice of valve size for TPVR (30 mm) as 3D measurements. The RVEF of sheep J from pre-CT was 62.1 %. In contrast with 3D CT, the straightened 4D reconstruction model not only enabled accurate prediction for valve size selection for TPVR but also provided an ideal virtual reality, thus presenting a promising method for TPVR and the innovation of TPVR devices.

Distributed model predictive control (DMPC) is a widely used approach especially for large-scale systems like transportation, traffic control or power distribution systems where solving the MPC problem in a centralized manner is not desirable or even not possible due to the size of the problem, maintenance issues, cabling burden, etc. Distributed optimization methods, which are being employed to solve the DMPC problems, normally suffer from having an enormous number of communications to reach a consensus between the local controllers. Therefore trying to find distributed optimization schemes that can realize an agreement among the local controllers with a lower communication load deserves attention. The alternating direction method of multipliers (ADMM) is a well known method to solve consensus problems. Since the local problems in ADMM can be handled with second-order methods, the convergence will be reached with a lower number of iterations in comparison to first-order methods, e.g. the fast gradient method. In this paper, ADMM is formulated and applied to a DMPC problem first in the primal domain. The main contribution of this paper is, however, the application of ADMM to the dual of the DMPC problem, introducing an augmented connection graph, which shows considerable improvement in convergence speed and therefore requires a lower number of communications in comparison with primal ADMM.

As indications for segmentectomy in small lung cancers expand, accurate preoperative computed tomography (CT) evaluation has become increasingly important. Irregularly shaped tumors require objective measurement techniques. This study assessed new segmentectomy criteria for early-stage non-small-cell lung cancer (NSCLC) using three-dimensional (3D) CT tumor volume. In total, 200 segmentectomies and 691 lobectomies for clinical stage 0/IA NSCLC were retrospectively analyzed. Preoperative 3D-CT was performed to measure total tumor volume and solid component volume. To assess the predictive value of solid component volume and solid component ratio for recurrence and mortality, the receiver operating characteristic (ROC) curves for the segmentectomy and lobectomy groups were plotted individually. Based on the cut-off values derived from the ROC curves in the segmentectomy group, all cases were stratified into four categories ("volume high risk + ratio high risk", "volume high risk + ratio low risk", "volume low risk + ratio high risk", "volume low risk + ratio low risk"). Recurrence-free survival was analyzed using the log-rank test. The cutoff values were 2063.4 mm3 and 28.3% for segmentectomy and 4705.0 mm3 and 73.0% for lobectomy. A significant difference in the 5-year recurrence-free survival between segmentectomy and lobectomy was found only in the volume high-risk + ratio high-risk category (48.1% vs. 66.9%). This exploratory analysis suggests that 3D-CT tumor quantification may aid in refining segmentectomy criteria; however, external validation is necessary before clinical application.