Tomography Research Articles

Trabecular and cortical bone microarchitecture using high-resolution peripheral quantitative computed tomographic imaging in diabetic peripheral neuropathy

ContextType 2 Diabetes Mellitus (T2D) is associated with an increased risk of fragility fracture despite normal areal bone mineral density (BMD). The contribution of diabetic peripheral neuropathy (PN) to volumetric BMD (vBMD) and bone microarchitecture in T2D is not explored. ObjectiveTo assess vBMD and microarchitectural properties of bone using high-resolution peripheral quantitative computed tomography (HR-pQCT) in patients of T2D with or without PN. DesignThis is a cross-sectional study of patients of T2D divided into two groups [patients with T2D without PN (Group A) and T2D with PN (Group B)]. All patients underwent clinical examination, biochemical evaluation, dual-energy X-ray absorptiometry (DXA), and HR-pQCT of the radius and tibia. ResultsA total of 296 patients were included in the study [Group A (n = 98), Group B (n = 198)]. HR-pQCT demonstrated a significant difference in total vBMD[mg/cm3] at tibia (291.6 ± 61.8 vs. 268.2 ± 63.0; p-0.003); cortical vBMD[mg/cm3] at tibia [912.5 (863.3, 962.4) vs. 853.8 (795.3, 913.2) p-0.000], among groups A and B respectively. Among the microarchitecture parameters, there was a significant difference in cortical porosity at the tibia (2.5% ±1.7% vs. 3%±1.7%; p-0.004), trabecular number[mm-1] at the tibia [1.080 (0.896, 1.237) vs. 1.140 (0.983, 1.286), p-0.045] and trabecular thickness[mm] at the radius [0.228 (0.217, 0.247) Vs. 0.238 (0.224, 0.253); p-0.006], among groups A and B respectively. ConclusionDespite comparable areal BMD, T2D patients with PN have diminished vBMD and deteriorated skeletal microarchitecture, compared to those without PN.

Importance of local and systemic factors in preventing implant displacement in the mandibular body: a scoping review of existing literature

BackgroundThe aim of this research was to analyse the current literature on displaced dental implants in the mandibular body, including local and systemic variables related to their cause, and to identify the most frequent location.MethodsThe study conducted a search of three databases (Pubmed, Scopus, and Web of Science) using specific index terms such as ‘dental implant’, ‘displacement’, ‘dislocation’, ‘displaced’, and ‘mandible’. The analysis focused on the direction of displacement and the characteristics of the bone tissue (bone quality, density, and quantity) in cases where dental implants were displaced.ResultsA total of 371 articles were obtained. Thirteen of these articles were selected and read in full. To define bone quality, the Lekholm and Zarb classification, modified by Rosas et al., was used. The type II-B bone, which is characterized by thick cortical bone surrounding cancellous bone with extremely wide medullary spaces, presented the largest number of complications. Twenty-two cases were found in which the displacement direction was horizontal. Of these, four were displaced vestibularly, fourteen lingually, and four remained in the center. Additionally, 24 cases presented vertical displacement, with 12 displaced towards the inferior border of the mandible, 9 towards the middle or adjacent to the inferior dental nerve canal, and 3 above the inferior dental nerve canal.ConclusionThe accidental displacement of implants within the mandibular body is associated with various risk factors, including the characteristics of the bony trabeculum and the size of the medullary spaces. It is reasonable to suggest that only an adequate pre-surgical diagnostic evaluation, with the help of high-resolution tomographic images that allow a previous evaluation of these structures, will help to have better control over the other factors, thus minimizing the risk of displacement.

Three-dimensional replica of the temporal bone in the teaching of human anatomy.

The current study proposes the comparison of the visualization and identification of anatomical details between natural human temporal bone, its respective copy from three-dimensional printing, and the virtual model obtained from CBCT. The sample consisted of undergraduate students in Dentistry (Group UE, n = 22), Postgraduate students in Radiology and Imaging (Group P-RI, n = 20), and Postgraduate students in Forensic Odontology (Group P-FO, n = 24). All participants attended a theoretical class on specialized anatomy of the temporal bone and subsequently performed the markings of 10 determined structures. The number of correct identifications was similar in natural bone and printed three-dimensional models in all groups (p > 0.05). The virtual model showed a significantly lower number of correct structures (p < 0.05) in the 3 groups. In general, there were significantly higher percentages of accurate answers among postgraduate students compared to undergraduate students. Most graduate students believed that the printed three-dimensional model could be used to teach anatomy in place of natural bone, while undergraduate students disagreed or were unsure (p < 0.05). Regarding the virtual tomographic image, in all groups, students disagreed or were not sure that its use would be beneficial in replacing natural bone. Three-dimensional and virtual models can be used as auxiliary tools in teaching anatomy, complementing practical learning with natural bones.

Automatic segmentation of the maxillary sinus on cone beam computed tomographic images with U-Net deep learning model

BackgroundMedical imaging segmentation is the use of image processing techniques to expand specific structures or areas in medical images. This technique is used to separate and display different textures or shapes in an image. The aim of this study is to develop a deep learning-based method to perform maxillary sinus segmentation using cone beam computed tomography (CBCT) images. The proposed segmentation method aims to provide better image guidance to surgeons and specialists by determining the boundaries of the maxillary sinus cavities. In this way, more accurate diagnoses can be made and surgical interventions can be performed more successfully.MethodsIn the study, axial CBCT images of 100 patients (200 maxillary sinuses) were used. These images were marked to identify the maxillary sinus walls. The marked regions are masked for use in the maxillary sinus segmentation model. U-Net, one of the deep learning methods, was used for segmentation. The training process was carried out for 10 epochs and 100 iterations per epoch. The epoch and iteration numbers in which the model showed maximum success were determined using the early stopping method.ResultsAfter the segmentation operations performed with the U-Net model trained using CBCT images, both visual and numerical results were obtained. In order to measure the performance of the U-Net model, IoU (Intersection over Union) and F1 Score metrics were used. As a result of the tests of the model, the IoU value was found to be 0.9275 and the F1 Score value was 0.9784.ConclusionThe U-Net model has shown high success in maxillary sinus segmentation. In this way, fast and highly accurate evaluations are possible, saving time by reducing the workload of clinicians and eliminating subjective errors.

Positron Emission Projection Imaging: A technique for concentration field measurements in opaque industrial systems

A novel Positron Emission Projection Imaging (PEPI) algorithm designed to compute the plane-projected spatial distribution of radiolabelled materials without the need for collimation is introduced. By leveraging improved data efficiency, we have achieved a technique with enhanced spatial resolution and temporal resolution compared to previous PEPI algorithms. Validation of this algorithm was conducted using synthetic data generated from a digital twin of a PET scanner, demonstrating its accuracy for practical applications. The industrial advantage of this novel algorithm was applied in the imaging of laminar flow mixing within a ploughshare mixer, with the experimental results compared against those obtained from validated computational fluid dynamics (CFD) models. This comparison highlights an important use case for PEPI as a robust validation tool for CFD simulations, crucial for enhancing industrial processes. PEPI, which uses deeply penetrating gamma-photons, is now capable of imaging opaque fluids and solids in industrial casing. Future directions for this work include further algorithmic refinements and expanding its application across various industrial systems, establishing PEPI as a robust tool for in-depth industrial process analysis. The advancements presented here allow for optimized mixer design and enhanced process efficiency, extending the frontiers of tomographic imaging in industrial applications.

Sex estimation using post-mortem computed tomographic images of the clavicle in a Malaysian population

Forensic practitioners need contemporary anthropological data for the identification of human remains. The clavicle possesses a high degree of variability in its anatomical, biomechanical, and morphological features that are sex-dependent albeit population specific. The aim of this study was to develop sex estimation models for Malaysian individuals using post-mortem computed tomographic images of the clavicle. Sample comprised scans of 2.0 mm resolution of 405 individuals (209 male; 196 female) aged between 19 to 88 years. These scans were reconstructed and visualized using Infinitt. Six clavicular measurements (i.e. maximum length, C1; midshaft circumference, C2; midshaft maximum diameter, C3; midshaft minimum diameter, C4; maximum breadth of the sternal end, C5; and maximum breadth of the acromial articular surface, C6) were obtained from these images. Data were analyzed using descriptive statistics and discriminant function analysis. Measurements taken from the images were highly precise (ICC = 0.770–0.999). There is a significant difference between all parameters and sex (p < 0.001), however none for age and ethnic group. A multivariate sex estimation model was developed: Sex = (C1*0.86) + (C2*0.236) + (C3*-0.145) + (C5*- 0.074) − 17.618; with an accuracy rate of 89.1 % and sex bias of −3.2 %. Lower accuracy rates were obtained for single variable models (61.5–83.2 %). The resultant sex discriminant models can be used for estimating sex based on the clavicle in our local forensic practice.

Machine Learning Enhanced Tomographic Imaging of Chemical Short-range Order in Fe-based Solid Solutions

Machine Learning Enhanced Tomographic Imaging of Chemical Short-range Order in Fe-based Solid Solutions

Iterative Tomographic Image Reconstruction Algorithm Based on Extended Power Divergence by Dynamic Parameter Tuning.

Computed tomography (CT) imaging plays a crucial role in various medical applications, but noise in projection data can significantly degrade image quality and hinder diagnosis accuracy. Iterative algorithms for tomographic image reconstruction outperform transform methods, especially in scenarios with severe noise in projections. In this paper, we propose a method to dynamically adjust two parameters included in the iterative rules during the reconstruction process. The algorithm, named the parameter-extended expectation-maximization based on power divergence (PXEM), aims to minimize the weighted extended power divergence between the measured and forward projections at each iteration. Our numerical and physical experiments showed that PXEM surpassed conventional methods such as maximum-likelihood expectation-maximization (MLEM), particularly in noisy scenarios. PXEM combines the noise suppression capabilities of power divergence-based expectation-maximization with static parameters at every iteration and the edge preservation properties of MLEM. The experimental results demonstrated significant improvements in image quality in metrics such as the structural similarity index measure and peak signal-to-noise ratio. PXEM improves CT image reconstruction quality under high noise conditions through enhanced optimization techniques.

Overcoming data scarcity in biomedical imaging with a foundational multi-task model.

Foundational models, pretrained on a large scale, have demonstrated substantial success across non-medical domains. However, training these models typically requires large, comprehensive datasets, which contrasts with the smaller and more specialized datasets common in biomedical imaging. Here we propose a multi-task learning strategy that decouples the number of training tasks from memory requirements. We trained a universal biomedical pretrained model (UMedPT) on a multi-task database including tomographic, microscopic and X-ray images, with various labeling strategies such as classification, segmentation and object detection. The UMedPT foundational model outperformed ImageNet pretraining and previous state-of-the-art models. For classification tasks related to the pretraining database, it maintained its performance with only 1% of the original training data and without fine-tuning. For out-of-domain tasks it required only 50% of the original training data. In an external independent validation, imaging features extracted using UMedPT proved to set a new standard for cross-center transferability.

Reconstruction of particle distribution for tomographic particle image velocimetry based on unsupervised learning method

The development of deep learning has inspired some new methods to solve the 3D reconstruction problem for Tomographic Particle Image Velocimetry (Tomo-PIV). However, the supervised learning method requires a large number of data with ground truth as training information, which is very difficult to gather from experiments. Although synthetic datasets can be used as alternatives, they are still not exactly the same with the real-world experimental data. In this paper, an Unsupervised Reconstruction Technique based on U-net (UnRTU) is proposed to reconstruct volume particle distribution explicitly. Instead of using ground truth data, a projection function is used as an unsupervised loss function for network training to reconstruct particle distribution. The UnRTU was compared with some traditional algebraic reconstruction algorithms and supervised learning method using synthetic data under different particle density and noise level. The results indicate that UnRTU outperforms these traditional approaches in both reconstruction quality and noise robustness, and is comparable to the supervised learning methods AI-PR. For experimental tests, particles dispersed in cured epoxy resin are moved by an electric rail with a certain speed to obtain the ground truth data of particle velocity. Compared with other algorithms, the reconstructed particle distribution by UnRTU has the best reconstruction fidelity. And the accuracy of the 3D velocity field estimated by UnRTU is 12.9% higher than that from the traditional MLOS-MART algorithm. It demonstrates significant potential and advantages for UnRTU in 3D reconstruction of particle distribution. Finally, UnRTU was successfully applied to the high-speed planar cascade airflow field, demonstrating its applicability for measuring complex fluid flow fields at higher particle density.

"Unkinking" the "Kink" Normalizes the Doppler Pattern.

Coarctation of the aorta (CoA) comprises 5-7% of congenital heart disease and can present as an isolated narrowing in the aortic arch just distal to the left subclavian artery or can be associated with cardiac abnormalities such as a bicuspid aortic valve, aortopathy, or ventricular septal defects. With the advances in the medical field, intervention on CoA can either be via surgical repair or endovascular stenting. Echocardiography is the mainstay in diagnosing CoA, with tomographic imaging such as magnetic resonance imaging (MRI) or computed tomography providing supplementary assessment of the aorta, valves, and collateral vessels. We present a case of a young hypertensive male who was noted to have a continuous cardiac murmur with diagnostic Doppler pattern of CoA on echocardiography that normalized soon after percutaneous stenting.

GAN-based quantitative oblique back-illumination microscopy enables computationally efficient epi-mode refractive index tomography.

Quantitative oblique back-illumination microscopy (qOBM) is a novel imaging technology that enables epi-mode 3D quantitative phase imaging and refractive index (RI) tomography of thick scattering samples. The technology uses four oblique back illumination images captured at the same focal plane and a fast 2D deconvolution reconstruction algorithm to reconstruct 2D phase cross-sections of thick samples. Alternatively, a through-focus z-stack of oblique back illumination images can be used to recover 3D RI tomograms with improved RI quantitative fidelity at the cost of a more computationally expensive reconstruction algorithm. Here, we report on a generative adversarial network (GAN) assisted approach to reconstruct 3D RI tomograms with qOBM that achieves high fidelity and greatly reduces processing time. The proposed approach achieves high-fidelity 3D RI tomography using differential phase contrast images from three adjacent z-planes. A ∼9-fold improvement in volumetric reconstruction time is achieved. We further show that this technique provides high SNR RI tomograms with high quantitative fidelity, reduces motion artifacts, and generalizes to different tissue types. This work can lead to real-time, high-fidelity RI tomographic imaging for in-vivo pre-clinical and clinical applications.

The Surviving, Not Thriving, Photoreceptors in Patients with ABCA4 Stargardt Disease.

Stargardt disease (STGD1), associated with biallelic variants in the ABCA4 gene, is the most common heritable macular dystrophy and is currently untreatable. To identify potential treatment targets, we characterized surviving STGD1 photoreceptors. We used clinical data to identify macular regions with surviving STGD1 photoreceptors. We compared the hyperreflective bands in the optical coherence tomographic (OCT) images that correspond to structures in the STGD1 photoreceptor inner segments to those in controls. We used adaptive optics scanning light ophthalmoscopy (AO-SLO) to study the distribution of cones and AO-OCT to evaluate the interface of photoreceptors and retinal pigment epithelium (RPE). We found that the profile of the hyperreflective bands differed dramatically between patients with STGD1 and controls. AO-SLOs showed patches in which cone densities were similar to those in healthy retinas and others in which the cone population was sparse. In regions replete with cones, there was no debris at the photoreceptor-RPE interface. In regions with sparse cones, there was abundant debris. Our results raise the possibility that pharmaceutical means may protect surviving photoreceptors and so mitigate vision loss in patients with STGD1.

Structural and Electrochemical Investigation of Anode‐Supported Proton‐Conducting Solid Oxide Fuel Cell Fabricated by the Freeze Casting Process

ABSTRACTHierarchically oriented macroporous NiO–BaZr0.1Ce0.7Y0.2O3−δ (BZCY7) anode‐supporting layer (ASL) was developed using the freeze casting technique. The resulting freeze‐cast structure was analyzed through scanning electron microscopy and X‐ray computed tomography. A thin layer of BZCY7 was utilized as a proton‐conducting electrolyte, whereas La1.9Sr0.1Ni0.7Cu0.3O3−δ –gadolinium‐doped ceria 10% Gd (LSNC–GDC10) was employed and evaluated as cathode layer. The performance of the cell was assessed by means of electrochemical impedance spectroscopy and I–V–P curves at various temperatures. Furthermore, as a point of comparison, a cell with an ASL was prepared using the dry pressing method, incorporating 20 wt.% graphite as a pore‐forming agent. The freeze‐cast anode‐supported cell demonstrated a polarization resistance of 1.45 Ω cm2 at 550°C and 0.29 Ω cm2 at 750°C. Maximum achieved power densities were 0.189 and 0.429 W cm−2 at 550 and 750°C, respectively. For the cell fabricated by the dry pressing method, the maximum power densities were 0.158 and 0.397 W cm−2 at 550 and 750°C, respectively. Additionally, the tortuosity factor of the anode layer and the gas diffusion streamline in the direction of solidification were determined by using 3D X‐ray tomography imaging and subsequent image processing.

Radionuclide therapy of bevacizumab-based PNA-mediated pretargeting.

The radionuclide-labeled bevacizumab (BV) is a potential therapeutic approach for vascular endothelial growth factor overexpressed tumors. Because of its large molecular weight, BV is cleared slowly in vivo, which caused damage to healthy tissues and organs. On account of this situation, using the pretargeting strategy with DNA/RNA analogs, such as peptide nucleic acid (PNA), is an effective way of treating solid tumors. The BV-PNA conjugate (BV-PNA-1) was injected intravenously as the pretargeted probe, which was specifically accumulated in a solid tumor and gradually metabolically cleared. Then the [177Lu]Lu-labeled complementary PNA strand ([177Lu]Lu-PNA-2) as the second probe was injected, and bound with BV-PNA-1 by the base complementary pairing. In this study, the BV-based PNA-mediated pretargeting strategy was systematically studied, including stability of probes, specific binding ability, biodistribution in animal model, evaluation of single photon emission computed tomography/computed tomography imaging, and therapeutic effect. Compared with group A ([177Lu]Lu-BV), the group B (BV-PNA-1 + [177Lu]Lu-PNA-2) showed lower blood radiotoxicity (22.55 ±1.62 vs. 5.18 ± 0.40%, %ID/g, P < 0.05), and similar accumulation of radioactivity in tumor (5.32 ± 0.66 vs. 6.68 ± 0.79%, %ID/g, P > 0.05). Correspondingly, there was no significant difference in therapeutic effect between groups A and B. The PNA-mediated pretargeting strategy could increase the tumor-to-blood ratio, thereby reducing the damage to normal tissues, while having a similar therapeutic effect to solid tumor. All the experiments in this study showed the potential and effectiveness of pretargeting radioimmunotherapy.

High-resolution computed tomographic (HRCT) image series from 413 canid and 18 felid skulls

Computed tomography (CT) is a non-invasive, three-dimensional imaging tool used in medical imaging, forensic science, industry and engineering, anthropology, and archaeology. The current study used high-resolution medical CT scanning of 431 animal skulls, including 399 dog skulls from 152 breeds, 14 cat skulls from 9 breeds, 14 skulls from 8 wild canid species (gray wolf, golden jackal, coyote, maned wolf, bush dog, red fox, Fennec fox, bat-eared fox), and 4 skulls from 4 wild felid species (wildcat, leopard, serval, caracal). This comprehensive and unique collection of CT image series of skulls can provide a solid foundation not only for comparative anatomical and evolutionary studies but also for the advancement of veterinary education, virtual surgery planning, and the facilitation of training in sophisticated machine learning methodologies.

A greedy regularized block Kaczmarz method for accelerating reconstruction in magnetic particle imaging

Objective. Magnetic particle imaging (MPI) is an emerging medical tomographic imaging modality that enables real-time imaging with high sensitivity and high spatial and temporal resolution. For the system matrix reconstruction method, the MPI reconstruction problem is an ill-posed inverse problem that is commonly solved using the Kaczmarz algorithm. However, the high computation time of the Kaczmarz algorithm, which restricts MPI reconstruction speed, has limited the development of potential clinical applications for real-time MPI. In order to achieve fast reconstruction in real-time MPI, we propose a greedy regularized block Kaczmarz method (GRBK) which accelerates MPI reconstruction. Approach. GRBK is composed of a greedy partition strategy for the system matrix, which enables preprocessing of the system matrix into well-conditioned blocks to facilitate the convergence of the block Kaczmarz algorithm, and a regularized block Kaczmarz algorithm, which enables fast and accurate MPI image reconstruction at the same time. Main results. We quantitatively evaluated our GRBK using simulation data from three phantoms at 20 dB, 30 dB, and 40 dB noise levels. The results showed that GRBK can improve reconstruction speed by single orders of magnitude compared to the prevalent regularized Kaczmarz algorithm including Tikhonov regularization, the non-negative Fused Lasso, and wavelet-based sparse model. We also evaluated our method on OpenMPIData, which is real MPI data. The results showed that our GRBK is better suited for real-time MPI reconstruction than current state-of-the-art reconstruction algorithms in terms of reconstruction speed as well as image quality. Significance. Our proposed method is expected to be the preferred choice for potential applications of real-time MPI.

Noninvasive Quantification of Glucose Metabolism in Mice Myocardium Using the Spline Reconstruction Technique.

The spline reconstruction technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The purpose of this study was to compare the SRT, filtered back-projection (FBP), and the Tera-Tomo 3D algorithm for various iteration numbers, using small-animal dynamic PET data obtained from a Mediso nanoScan® PET/CT scanner. For this purpose, Patlak graphical kinetic analysis was employed to noninvasively quantify the myocardial metabolic rate of glucose (MRGlu) in seven male C57BL/6 mice (n=7). All analytic reconstructions were performed via software for tomographic image reconstruction. The analysis of all PET-reconstructed images was conducted with PMOD software (version 3.506, PMOD Technologies LLC, Fällanden, Switzerland) using the inferior vena cava as the image-derived input function. Statistical significance was determined by employing the one-way analysis of variance test. The results revealed that the differences between the values of MRGlu obtained via SRT versus FBP, and the variants of he Tera-Tomo 3D algorithm were not statistically significant (p > 0.05). Overall, the SRT appears to perform similarly to the other algorithms investigated, providing a valid alternative analytic method for preclinical dynamic PET studies.

Head of Zebu cattle (Bos Taurus indicus): sectional anatomy and 3D computed tomography

The research was designed to use computed tomography (CT) with 3D-CT reconstruction imaging techniques and the various anatomical sections—plana transversalia, frontalis, and dorsalia—to describe the anatomical architecture of the Zebu cattle head. Our study used nine mature heads. The CT bone window created detailed images of cranial bones, mandibles, teeth, and hyoid bones. All of the head cavities were evaluated, including the cranial, orbital, oral, auricular, and nasal cavities with their paranasal and conchal sinuses. The septum nasi, attached to the vomer and maxillary bones, did not reach the nasal cavity floor caudally at the level of the second premolar teeth, resulting in a single median channel from the choanae to the nasopharynx. The positions, boundaries, and connections of the paranasal sinuses were clearly identified. There were four nasal conchal sinuses (that were named the dorsal, middle, ethmoidal, and ventral) and five paranasal sinuses that were described as the following: sinus frontalis, maxillaris, palatinorum, and lacrimalis, as defined in the different anatomical sections and computed tomographic images. The complicated sinus frontalis caused the pneumatization of all bones that surrounded the cranial cavity, with the exception of the ethmoidal and body of basisphenoid bones. The sinus maxillaris was connected to the sinus lacrimalis and palatinorum through the maxillolacrimal and palatomaxillary openings, and to the middle nasal meatus through the nasomaxillary opening. Our findings provide a detailed anatomical knowledge for disease diagnosis to internal medicine veterinarians and surgeons by offering a comprehensive atlas of the Zebu cattle anatomy.

Tip, torque and rotation of maxillary molars during distalization using Invisalign: a CBCT study

BackgroundDesirable molar distalization by bodily movement is challenging and can be difficult to achieve. This study investigated changes in molar angulation (mesiodistal tipping), molar inclination (buccolingual torque) and rotation during distalization using clear aligner therapy (CAT).Materials and methodsThis retrospective study included 38 cone beam computed tomographic images (CBCTs) taken for patients treated with molar distalization using CAT. The study evaluated pre- (T0) and post-treatment (T1) CBCTs of 19 adult patients (36.68 ± 13.50 years) who underwent maxillary molar distalization using Invisalign® aligners (Align Technology, Inc., San José, CA, USA) with a minimum of 2 mm distalization. Changes in maxillary molar tip, torque and rotation were measured for 61 molars (183 roots). Paired t-test was used to evaluate the differences between pre- and post-treatment readings. The level of significance was set at p ≤ 0.05. The reproducibility of measurements was assessed by the intraclass correlation coefficient (ICC).ResultsMolar angulation did not show significant change after distalization (p = 0.158) however, there was significant increase in buccal molar inclination (p = 0.034) and mesiobuccal molar rotation (p < 0.001).ConclusionMolar distalization of 2 mm did not cause significant molar tipping. Maxillary molars showed significant buccal inclination (increased torque) and mesiobuccal rotation after distalization.