Maturation of the vertebral ring apophysis is delayed in girls with adolescent idiopathic scoliosis compared to the normal population.

PURPOSE: The ring apophysis is a secondary ossification center on both sides of each vertebral body, to which the annulus of the intervertebral disc inserts. Recently, its pattern of ossification and fusion to the vertebral body was described for the normal growing spine. The aim of the present study was to investigate the ossification and fusion of the ring apophysis in patients with adolescent idiopathic scoliosis (AIS) and compare it to the normal growing population. METHODS: Ring apophysis maturation along the entire thoracic and lumbar spine was analyzed on CT scans of 99 female, pre-operative AIS patients and compared to 134 CT scans of non-scoliotic girls, aged 12 to 20. RESULTS: The ring apophysis maturation in AIS patients was delayed at all spinal levels in AIS patients compared to non-scoliotic controls. Ossification starts at T4-T11 at age 12, followed by T1-T5 and L3-S1 at age 15. The fusion process in AIS patients continues longer in the midthoracic region as compared to the other regions and as compared to non-scoliotic controls, with many incomplete fusions still at age 20. CONCLUSION: The ring apophysis maturation in AIS is delayed compared to that in the normal population and lasts longer in the mid/low thoracic spine. Delayed maturation of the spine's most important stabilizer, while the body's dimensions continue to increase, could be part of the patho-mechanism of AIS.

A multipurpose, adolescent idiopathic scoliosis-specific, short MRI protocol: A feasibility study in volunteers.

INTRODUCTION: Visualization of scoliosis typically requires ionizing radiation (radiography and CT) to visualize bony anatomy. MRI is often additionally performed to screen for neural axis abnormalities. We propose a 14-minutes radiation-free scoliosis-specific MRI protocol, which combines MRI and MRI-based synthetic CT images to visualize soft and osseous structures in one examination. We assess the ability of the protocol to visualize landmarks needed to detect 3D patho-anatomical changes, screen for neural axis abnormalities, and perform surgical planning and navigation. METHODS: 18 adult volunteers were scanned on 1.5 T MR-scanner using 3D T2-weighted and synthetic CT sequences. A predefined checklist of relevant landmarks was used for the parameter assessment by three readers. Parameters included Cobb angles, rotation, torsion, segmental height, area and centroids of Nucleus Pulposus and Intervertebral Disc. Precision, reliability and agreement between the readers measurements were evaluated. RESULTS: 91 % of Likert-based questions scored ≥ 4, indicating moderate to high confidence. Precision of 3D dot positioning was 1.0 mm. Precision of angle measurement was 0.6° (ICC 0.98). Precision of vertebral and IVD height measurements was 0.4 mm (ICC 0.99). Precision of area measurement for NP was 8 mm2 (ICC 0.55) and for IVD 18 mm2 (ICC 0.62) for IVD. Precision of centroid measurement for NP was 1.3 mm (ICC 0.88-0.92) and for IVD 1.1 mm (ICC 0.88-91). CONCLUSIONS: The proposed MRI protocol with synthetic CT reconstructions, has high precision, reliability and agreement between the readers for multiple scoliosis-specific measurements. It can be used to study scoliosis etiopathogenesis and to assess 3D spinal morphology.

Magnetic resonance imaging-based bone imaging of the lower limb: Strategies for generating high-resolution synthetic computed tomography.

This study aims at assessing approaches for generating high-resolution magnetic resonance imaging- (MRI-) based synthetic computed tomography (sCT) images suitable for orthopedic care using a deep learning model trained on low-resolution computed tomography (CT) data. To that end, paired MRI and CT data of three anatomical regions were used: high-resolution knee and ankle data, and low-resolution hip data. Four experiments were conducted to investigate the impact of low-resolution training CT data on sCT generation and to find ways to train models on low-resolution data while providing high-resolution sCT images. Experiments included resampling of the training data or augmentation of the low-resolution data with high-resolution data. Training sCT generation models using low-resolution CT data resulted in blurry sCT images. By resampling the MRI/CT pairs before the training, models generated sharper images, presumably through an increase in the MRI/CT mutual information. Alternatively, augmenting the low-resolution with high-resolution data improved sCT in terms of mean absolute error proportionally to the amount of high-resolution data. Overall, the morphological accuracy was satisfactory as assessed by an average intermodal distance between joint centers ranging from 0.7 to 1.2 mm and by an average intermodal root-mean-squared distances between bone surfaces under 0.7 mm. Average dice scores ranged from 79.8% to 87.3% for bony structures. To conclude, this paper proposed approaches to generate high-resolution sCT suitable for orthopedic care using low-resolution data. This can generalize the use of sCT for imaging the musculoskeletal system, paving the way for an MR-only imaging with simplified logistics and no ionizing radiation.

Automatic generation of subject-specific finite element models of the spine from magnetic resonance images.

The generation of subject-specific finite element models of the spine is generally a time-consuming process based on computed tomography (CT) images, where scanning exposes subjects to harmful radiation. In this study, a method is presented for the automatic generation of spine finite element models using images from a single magnetic resonance (MR) sequence. The thoracic and lumbar spine of eight adult volunteers was imaged using a 3D multi-echo-gradient-echo sagittal MR sequence. A deep-learning method was used to generate synthetic CT images from the MR images. A pre-trained deep-learning network was used for the automatic segmentation of vertebrae from the synthetic CT images. Another deep-learning network was trained for the automatic segmentation of intervertebral discs from the MR images. The automatic segmentations were validated against manual segmentations for two subjects, one with scoliosis, and another with a spine implant. A template mesh of the spine was registered to the segmentations in three steps using a Bayesian coherent point drift algorithm. First, rigid registration was applied on the complete spine. Second, non-rigid registration was used for the individual discs and vertebrae. Third, the complete spine was non-rigidly registered to the individually registered discs and vertebrae. Comparison of the automatic and manual segmentations led to dice-scores of 0.93-0.96 for all vertebrae and discs. The lowest dice-score was in the disc at the height of the implant where artifacts led to under-segmentation. The mean distance between the morphed meshes and the segmentations was below 1 mm. In conclusion, the presented method can be used to automatically generate accurate subject-specific spine models.

Impact of bone and cartilage segmentation from CT and MRI on both bone forearm osteotomy planning.

INTRODUCTION: The use of MRI scans for pre-operative surgical planning of forearm osteotomies provides additional information of joint cartilage and soft tissue structures and reduces radiation exposure in comparison with the use of CT scans. In this study, we investigated whether using 3D information obtained from MRI with and without cartilage information leads to a different outcome of pre-operative planning. METHODS: Bilateral CT and MRI scans of the forearms of 10 adolescent and young adult patients with a unilateral bone deformation were acquired in a prospective study. The bones were segmented from CT and MRI, and cartilage only from MRI. The deformed bones were virtually reconstructed, by registering the joint ends to the healthy contralateral side. An optimal osteotomy plane was determined that minimized the distance between the resulting fragments. This process was performed in threefold: using the CT and MRI bone segmentations, and the MRI cartilage segmentations. RESULTS: Comparison of bone segmentation from MRI and CT scan resulted in a 0.95 ± 0.02 Dice Similarity Coefficient and 0.42 ± 0.07 mm Mean Absolute Surface Distance. All realignment parameters showed excellent reliability across the different segmentations. However, the mean differences in translational realignment between CT and MRI bone segmentations (4.5 ± 2.1 mm) and between MRI bone and MRI bone and cartilage segmentations (2.8 ± 2.1 mm) were shown to be clinically and statistically significant. A significant positive correlation was found between the translational realignment and the relative amount of cartilage. CONCLUSION: This study indicates that although bone realignment remained largely similar when using MRI with and without cartilage information compared to using CT, the small differences in segmentation could induce statistically and clinically significant differences in the osteotomy planning. We also showed that endochondral cartilage might be a non-negligible factor when planning osteotomies for young patients.

Automatic Assessment of Lower-Limb Alignment from Computed Tomography.

BACKGROUND: Preoperative planning of lower-limb realignment surgical procedures necessitates the quantification of alignment parameters by using landmarks placed on medical scans. Conventionally, alignment measurements are performed on 2-dimensional (2D) standing radiographs. To enable fast and accurate 3-dimensional (3D) planning of orthopaedic surgery, automatic calculation of the lower-limb alignment from 3D bone models is required. The goal of this study was to develop, validate, and apply a method that automatically quantifies the parameters defining lower-limb alignment from computed tomographic (CT) scans. METHODS: CT scans of the lower extremities of 50 subjects were both manually and automatically segmented. Thirty-two manual landmarks were positioned twice on the bone segmentations to assess intraobserver reliability in a subset of 20 subjects. The landmarks were also positioned automatically using a shape-fitting algorithm. The landmarks were then used to calculate 25 angles describing the lower-limb alignment for all 50 subjects. RESULTS: The mean absolute difference (and standard deviation) between repeat measurements using the manual method was 2.01 ± 1.64 mm for the landmark positions and 1.05° ± 1.48° for the landmark angles, whereas the mean absolute difference between the manual and fully automatic methods was 2.17 ± 1.37 mm for the landmark positions and 1.10° ± 1.16° for the landmark angles. The manual method required approximately 60 minutes of manual interaction, compared with 12 minutes of computation time for the fully automatic method. The intraclass correlation coefficient showed good to excellent reliability between the manual and automatic assessments for 23 of 25 angles, and the same was true for the intraobserver reliability in the manual method. The mean for the 50 subjects was within the expected range for 18 of the 25 automatically calculated angles. CONCLUSIONS: We developed a method that automatically calculated a comprehensive range of 25 measurements that defined lower-limb alignment in considerably less time, and with differences relative to the manual method that were comparable to the differences between repeated manual assessments. This method could thus be used as an efficient alternative to manual assessment of alignment. LEVEL OF EVIDENCE: Diagnostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Bone visualization of the cervical spine with deep learning-based synthetic CT compared to conventional CT: A single-center noninferiority study on image quality.

PURPOSE: To investigate whether the image quality of a specific deep learning-based synthetic CT (sCT) of the cervical spine is noninferior to conventional CT. METHOD: Paired MRI and CT data were collected from 25 consecutive participants (≥ 50 years) with cervical radiculopathy. The MRI exam included a T1-weighted multiple gradient echo sequence for sCT reconstruction. For qualitative image assessment, four structures at two vertebral levels were evaluated on sCT and compared with CT by three assessors using a four-point scale (range 1-4). The noninferiority margin was set at 0.5 point on this scale. Additionally, acceptable image quality was defined as a score of 3-4 in ≥ 80% of the scans. Quantitative assessment included geometrical analysis and voxelwise comparisons. RESULTS: Qualitative image assessment showed that sCT was noninferior to CT for overall bone image quality, artifacts, imaging of intervertebral joints and neural foramina at levels C3-C4 and C6-C7, and cortical delineation at C6-C7. Noninferiority was weak to absent for cortical delineation at level C3-C4 and trabecular bone at both levels. Acceptable image quality was achieved for all structures in sCT and CT, except for trabecular bone in sCT and level C6-C7 in CT. Geometrical analysis of the sCT showed good to excellent agreement with CT. Voxelwise comparisons showed a mean absolute error of 80.05 (±6.12) HU, dice similarity coefficient (cortical bone) of 0.84 (±0.04) and structural similarity index of 0.86 (±0.02). CONCLUSIONS: This deep learning-based sCT was noninferior to conventional CT for the general visualization of bony structures of the cervical spine, artifacts, and most detailed structure assessments.

Efficient cascaded V-net optimization for lower extremity CT segmentation validated using bone morphology assessment.

Semantic segmentation of bone from lower extremity computerized tomography (CT) scans can improve and accelerate the visualization, diagnosis, and surgical planning in orthopaedics. However, the large field of view of these scans makes automatic segmentation using deep learning based methods challenging, slow and graphical processing unit (GPU) memory intensive. We investigated methods to more efficiently represent anatomical context for accurate and fast segmentation and compared these with state-of-the-art methodology. Six lower extremity bones from patients of two different datasets were manually segmented from CT scans, and used to train and optimize a cascaded deep learning approach. We varied the number of resolution levels, receptive fields, patch sizes, and number of V-net blocks. The best performing network used a multi-stage, cascaded V-net approach with 1283 -643 -323 voxel patches as input. The average Dice coefficient over all bones was 0.98 ± 0.01, the mean surface distance was 0.26 ± 0.12 mm and the 95th percentile Hausdorff distance 0.65 ± 0.28 mm. This was a significant improvement over the results of the state-of-the-art nnU-net, with only approximately 1/12th of training time, 1/3th of inference time and 1/4th of GPU memory required. Comparison of the morphometric measurements performed on automatic and manual segmentations showed good correlation (Intraclass Correlation Coefficient [ICC] >0.8) for the alpha angle and excellent correlation (ICC >0.95) for the hip-knee-ankle angle, femoral inclination, femoral version, acetabular version, Lateral Centre-Edge angle, acetabular coverage. The segmentations were generally of sufficient quality for the tested clinical applications and were performed accurately and quickly compared to state-of-the-art methodology from the literature.

Good long-term outcomes of the hip Chiari osteotomy in adolescents and adults with hip dysplasia: a systematic review.

BACKGROUND AND PURPOSE: The Chiari osteotomy was a regular treatment for developmental hip dysplasia before it became mostly reserved as a salvage therapy. However, the long-term survival of the Chiari osteotomy has not been systematically investigated. We investigated the survival time of the Chiari osteotomy until conversion to total hip arthroplasty (THA) in patients with primary hip dysplasia, and factors which correlated with survival, complications, and the improvement measured in radiographic parameters. PATIENTS AND METHODS: Studies were included when describing patients (> 16 years) with primary hip dysplasia treated with a Chiari osteotomy procedure with 8 years' follow-up. Data on patient characteristics, indications, complications, radiographic parameters, and survival time (endpoint: conversion to THA) were extracted. RESULTS: 8 studies were included. The average postoperative center-edge angle, acetabular head index, and Sharp angle were generally restored within the target range. 3 studies reported Kaplan-Meier survival rates varying from 96% at 10 years to 72% at 20 years' follow-up. Negative survival factors were high age at intervention and pre-existing advanced preoperative osteoarthritis. Moreover, reported complications ranged between 0% and 28.3 %. INTERPRETATION: The Chiari osteotomy has high reported survival rates and is capable of restoring radiographic hip parameters to healthy values. When carefully selected by young age, and a low osteoarthritis score, patients benefit from the Chiari osteotomy with satisfactory survival rates. The position of the Chiari osteotomy in relation to the periacetabular osteotomies should be further (re-)explored.

Patient-specific 3D-printed shelf implant for the treatment of hip dysplasia tested in an experimental animal pilot in canines.

The concept of a novel patient-specific 3D-printed shelf implant should be evaluated in a relevant large animal model with hip dysplasia. Therefore, three dogs with radiographic bilateral hip dysplasia and a positive subluxation test underwent unilateral acetabular augmentation with a 3D-printed dog-specific titanium implant. The contralateral side served as control. The implants were designed on CT-based pelvic bone segmentations and extended the dysplastic acetabular rim to increase the weight bearing surface without impairing the range of motion. Outcome was assessed by clinical observation, manual subluxation testing, radiography, CT, and gait analysis from 6 weeks preoperatively until termination at 26 weeks postoperatively. Thereafter, all hip joints underwent histopathological examination. The implantation and recovery from surgery was uneventful. Clinical subluxation tests at the intervention side became negative. Imaging showed medialization of the femoral head at the intervention side and the mean (range) CE-angle increased from 94° (84°-99°) preoperative to 119° (117°-120°) postoperative. Gait analysis parameters returned to pre-operative levels after an average follow-up of 6 weeks. Histology showed a thickened synovial capsule between the implant and the femoral head without any evidence of additional damage to the articular cartilage compared to the control side. The surgical implantation of the 3D shelf was safe and feasible. The patient-specific 3D-printed shelf implants restored the femoral head coverage and stability of dysplastic hips without complications. The presented approach holds promise to treat residual hip dysplasia justifying future veterinary clinical trials to establish clinical effectiveness in a larger cohort to prepare for translation to human clinic.

Synthetic CT for the planning of MR-HIFU treatment of bone metastases in pelvic and femoral bones: a feasibility study.

OBJECTIVES: Visualization of the bone distribution is an important prerequisite for MRI-guided high-intensity focused ultrasound (MRI-HIFU) treatment planning of bone metastases. In this context, we evaluated MRI-based synthetic CT (sCT) imaging for the visualization of cortical bone. METHODS: MR and CT images of nine patients with pelvic and femoral metastases were retrospectively analyzed in this study. The metastatic lesions were osteolytic, osteoblastic or mixed. sCT were generated from pre-treatment or treatment MR images using a UNet-like neural network. sCT was qualitatively and quantitatively compared to CT in the bone (pelvis or femur) containing the metastasis and in a region of interest placed on the metastasis itself, through mean absolute difference (MAD), mean difference (MD), Dice similarity coefficient (DSC), and root mean square surface distance (RMSD). RESULTS: The dataset consisted of 3 osteolytic, 4 osteoblastic and 2 mixed metastases. For most patients, the general morphology of the bone was well represented in the sCT images and osteolytic, osteoblastic and mixed lesions could be discriminated. Despite an average timespan between MR and CT acquisitions of 61 days, in bone, the average (± standard deviation) MAD was 116 ± 26 HU, MD - 14 ± 66 HU, DSC 0.85 ± 0.05, and RMSD 2.05 ± 0.48 mm and, in the lesion, MAD was 132 ± 62 HU, MD - 31 ± 106 HU, DSC 0.75 ± 0.2, and RMSD 2.73 ± 2.28 mm. CONCLUSIONS: Synthetic CT images adequately depicted the cancellous and cortical bone distribution in the different lesion types, which shows its potential for MRI-HIFU treatment planning. KEY POINTS: • Synthetic computed tomography was able to depict bone distribution in metastatic lesions. • Synthetic computed tomography images intrinsically aligned with treatment MR images may have the potential to facilitate MR-HIFU treatment planning of bone metastases, by combining visualization of soft tissues and cancellous and cortical bone.

Magnetic Resonance Imaging Versus Computed Tomography for Three-Dimensional Bone Imaging of Musculoskeletal Pathologies: A Review.

Magnetic resonance imaging (MRI) is increasingly utilized as a radiation-free alternative to computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal pathologies. MR imaging of hard tissues such as cortical bone remains challenging due to their low proton density and short transverse relaxation times, rendering bone tissues as nonspecific low signal structures on MR images obtained from most sequences. Developments in MR image acquisition and post-processing have opened the path for enhanced MR-based bone visualization aiming to provide a CT-like contrast and, as such, ease clinical interpretation. The purpose of this review is to provide an overview of studies comparing MR and CT imaging for diagnostic and treatment planning purposes in orthopedic care, with a special focus on selective bone visualization, bone segmentation, and three-dimensional (3D) modeling. This review discusses conventional gradient-echo derived techniques as well as dedicated short echo time acquisition techniques and post-processing techniques, including the generation of synthetic CT, in the context of 3D and specific bone visualization. Based on the reviewed literature, it may be concluded that the recent developments in MRI-based bone visualization are promising. MRI alone provides valuable information on both bone and soft tissues for a broad range of applications including diagnostics, 3D modeling, and treatment planning in multiple anatomical regions, including the skull, spine, shoulder, pelvis, and long bones. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

MRI-based synthetic CT shows equivalence to conventional CT for the morphological assessment of the hip joint.

This study evaluated the accuracy of synthetic computed tomography (sCT), as compared to CT, for the 3D assessment of the hip morphology. Thirty male patients with asymptomatic hips, referred for magnetic resonance (MR) imaging and CT, were included in this retrospective study. sCT images were generated from three-dimensional radiofrequency-spoiled T1-weighted multi-echo gradient-echo MR images using a commercially available deep learning-enabled software and were compared with CT images through mean error and surface distance computation and by means of eight clinical morphometric parameters relevant for hip care. Parameters included center-edge angle (CEA), sharp angle, acetabular index, extrusion index, femoral head center-to-midline distance, acetabular version (AV), and anterior and posterior acetabular sector angles. They were measured by two senior orthopedic surgeons and a radiologist in-training on CT and sCT images. The reliability and agreement of CT- and sCT-based measurements were assessed using intraclass correlation coefficients (ICCs) for absolute agreement, Bland-Altman plots, and two one-sided tests for equivalence. The surface distance between CT- and sCT-based bone models were on average submillimeter. CT- and sCT-based measurements showed moderate to excellent interobserver and intraobserver correlation (0.56 < ICC < 0.99). In particular, the inter/intraobserver agreements were good for AV (ICC > 0.75). For CEA, the intraobserver agreement was good (ICC > 0.75) and the interobserver agreement was moderate (ICC > 0.69). Limits of agreements were similar between intraobserver CT and intermodal measurements. All measurements were found statistically equivalent, with average intermodal differences within the intraobserver limits of agreement. In conclusion, sCT and CT were equivalent for the assessment of the hip joint bone morphology.

Multiple-echo steady-state (MESS): Extending DESS for joint T2 mapping and chemical-shift corrected water-fat separation.

PURPOSE: To extend the double echo steady-state (DESS) sequence to enable chemical-shift corrected water-fat separation. METHODS: This study proposes multiple-echo steady-state (MESS), a sequence that modifies the readouts of the DESS sequence to acquire two echoes each with bipolar readout gradients with higher readout bandwidth. This enables water-fat separation and eliminates the need for water-selective excitation that is often used in combination with DESS, without increasing scan time. An iterative fitting approach was used to perform joint chemical-shift corrected water-fat separation and T2 estimation on all four MESS echoes simultaneously. MESS and water-selective DESS images were acquired for five volunteers, and were compared qualitatively as well as quantitatively on cartilage T2 and thickness measurements. Signal-to-noise ratio (SNR) and T2 quantification were evaluated numerically using pseudo-replications of the acquisition. RESULTS: The water-fat separation provided by MESS was robust and with quality comparable to water-selective DESS. MESS T2 estimation was similar to DESS, albeit with slightly higher variability. Noise analysis showed that SNR in MESS was comparable to DESS on average, but did exhibit local variations caused by uncertainty in the water-fat separation. CONCLUSION: In the same acquisition time as DESS, MESS provides water-fat separation with comparable SNR in the reconstructed water and fat images. By providing additional image contrasts in addition to the water-selective DESS images, MESS provides a promising alternative to DESS.

CT to MR registration of complex deformations in the knee joint through dual quaternion interpolation of rigid transforms.

Purpose.To develop a method that enables computed tomography (CT) to magnetic resonance (MR) image registration of complex deformations typically encountered in rotating joints such as the knee joint.Methods.We propose a workflow, denoted quaternion interpolated registration (QIR), consisting of three steps, which makes use of prior knowledge of tissue properties to initialise deformable registration. In the first step, the rigid skeletal components were individually registered. Next, the deformation of soft tissue was estimated using a dual quaternion-based interpolation method. In the final step, the registration was fine-tuned with a rigidity-constrained deformable registration step. The method was applied to paired, unregistered CT and MR images of the knee of 92 patients. It was compared to registration using B-Splines (BS) and B-Splines with a rigidity penalty (BSRP). Registration accuracy was evaluated using mutual information, and by calculating Dice similarity coefficient (DSC), mean absolute surface distance (MASD) and 95th percentile Hausdorff distance (HD95) on bone, and DSC on water and fat dominated tissue. To evaluate the rigidity of bone in the registration, the Jacobian determinant (JD) was calculated.Results.QIR achieved improved results with 0.93, 0.76 mm and 1.88 mm on the DSC, MASD and HD95 metrics on bone, compared to 0.87, 1.40 mm and 4.99 mm for method and 0.87, 1.40 mm and 3.56 mm for the BSRP method. The average DSC of water and fat was 0.77 and 0.86 for the QIR, 0.75 and 0.84 for BS and 0.74 and 0.84 for BSRP. Comparison of the median JD and median interquartile (IQR) ranges of the JD indicated that the QIR (1.00 median, 0.03 IQR) resulted in higher rigidity in the rigid skeletal tissues compared to the BS (0.98 median, 0.19 IQR) and BSRP (1.00 median, 0.05 IQR) methods.Conclusion.This study showed that QIR could improve the outcome of complex registration problems, encountered in joints involving rigid and non-rigid bodies such as occur in the knee, as compared to a conventional registration approach.

3D-printed saw guides for lower arm osteotomy, a comparison between a synthetic CT and CT-based workflow.

BACKGROUND: Three-dimensional (3D)-printed saw guides are frequently used to optimize osteotomy results and are usually designed based on computed tomography (CT), despite the radiation burden, as radiation-less alternatives like magnetic resonance imaging (MRI) have inferior bone visualization capabilities. This study investigated the usability of MR-based synthetic-CT (sCT), a novel radiation-less bone visualization technique for 3D planning and design of patient-specific saw guides. METHODS: Eight human cadaveric lower arms (mean age: 78y) received MRI and CT scans as well as high-resolution micro-CT. From the MRI scans, sCT were generated using a conditional generative adversarial network. Digital 3D bone surface models based on the sCT and general CT were compared to the surface model from the micro-CT that was used as ground truth for image resolution. From both the sCT and CT digital bone models saw guides were designed and 3D-printed in nylon for one proximal and one distal bone position for each radius and ulna. Six blinded observers placed these saw guides as accurately as possible on dissected bones. The position of each guide was assessed by optical 3D-scanning of each bone with positioned saw guide and compared to the preplanning. Eight placement errors were evaluated: three translational errors (along each axis), three rotational errors (around each axis), a total translation (∆T) and a total rotation error (∆R). RESULTS: Surface models derived from micro-CT were on average smaller than sCT and CT-based models with average differences of 0.27 ± 0.30 mm for sCT and 0.24 ± 0.12 mm for CT. No statistically significant positioning differences on the bones were found between sCT- and CT-based saw guides for any axis specific translational or rotational errors nor between the ∆T (p = .284) and ∆R (p = .216). On Bland-Altman plots, the ∆T and ∆R limits of agreement (LoA) were within the inter-observer variability LoA. CONCLUSIONS: This research showed a similar error for sCT and CT digital surface models when comparing to ground truth micro-CT models. Additionally, the saw guide study showed equivalent CT- and sCT-based saw guide placement errors. Therefore, MRI-based synthetic CT is a promising radiation-less alternative to CT for the creation of patient-specific osteotomy surgical saw guides.

Magnetic resonance imaging-based synthetic computed tomography of the lumbar spine for surgical planning: a clinical proof-of-concept.

OBJECTIVE: Computed tomography scanning of the lumbar spine incurs a radiation dose ranging from 3.5 mSv to 19.5 mSv as well as relevant costs and is commonly necessary for spinal neuronavigation. Mitigation of the need for treatment-planning CT scans in the presence of MRI facilitated by MRI-based synthetic CT (sCT) would revolutionize navigated lumbar spine surgery. The authors aim to demonstrate, as a proof of concept, the capability of deep learning-based generation of sCT scans from MRI of the lumbar spine in 3 cases and to evaluate the potential of sCT for surgical planning. METHODS: Synthetic CT reconstructions were made using a prototype version of the "BoneMRI" software. This deep learning-based image synthesis method relies on a convolutional neural network trained on paired MRI-CT data. A specific but generally available 4-minute 3D radiofrequency-spoiled T1-weighted multiple gradient echo MRI sequence was supplemented to a 1.5T lumbar spine MRI acquisition protocol. RESULTS: In the 3 presented cases, the prototype sCT method allowed voxel-wise radiodensity estimation from MRI, resulting in qualitatively adequate CT images of the lumbar spine based on visual inspection. Normal as well as pathological structures were reliably visualized. In the first case, in which a spiral CT scan was available as a control, a volume CT dose index (CTDIvol) of 12.9 mGy could thus have been avoided. Pedicle screw trajectories and screw thickness were estimable based on sCT findings. CONCLUSIONS: The evaluated prototype BoneMRI method enables generation of sCT scans from MRI images with only minor changes in the acquisition protocol, with a potential to reduce workflow complexity, radiation exposure, and costs. The quality of the generated CT scans was adequate based on visual inspection and could potentially be used for surgical planning, intraoperative neuronavigation, or for diagnostic purposes in an adjunctive manner.

Deep learning-enabled MRI-only photon and proton therapy treatment planning for paediatric abdominal tumours.

PURPOSE: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours. MATERIALS AND METHODS: The study was conducted on 66 paediatric patients with Wilms' tumour or neuroblastoma (age 4 ± 2 years) who underwent MR and computed tomography (CT) acquisition on the same day as part of the clinical protocol. MRI intensities were converted to CT Hounsfield units (HU) by means of a UNet-like neural network trained to generate synthetic CT (sCT) from T1- and T2-weighted MR images. The CT-to-sCT image similarity was evaluated by computing the mean error (ME), mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and Dice similarity coefficient (DSC). Synthetic CT dosimetric accuracy was verified against CT-based dose distributions for volumetric-modulated arc therapy (VMAT) and intensity-modulated pencil-beam scanning (PBS). Relative dose differences (Ddiff) in the internal target volume and organs-at-risk were computed and a three-dimensional gamma analysis (2 mm, 2%) was performed. RESULTS: The average ± standard deviation ME was -5 ± 12 HU, MAE was 57 ± 12 HU, PSNR was 30.3 ± 1.6 dB and DSC was 76 ± 8% for bones and 92 ± 9% for lungs. Average Ddiff were <0.5% for both VMAT (range [-2.5; 2.4]%) and PBS (range [-2.7; 3.7]%) dose distributions. The average gamma pass-rates were >99% (range [85; 100]%) for VMAT and >96% (range [87; 100]%) for PBS. CONCLUSION: The deep learning-based model generated accurate sCT from planning T1w- and T2w-MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for paediatric patients with abdominal tumours.

Long-term outcomes of the hip shelf arthroplasty in adolescents and adults with residual hip dysplasia: a systematic review.

Background and purpose - The shelf arthroplasty was the regular treatment for residual hip dysplasia before it was substituted by the peri-acetabular osteotomy. Yet, evidence regarding the survival of shelf arthroplasty surgery has never been systematically documented. Hence, we investigated the survival time of the shelf procedure until revision to THA in patients with primary hip dysplasia. Factors that influenced survival and complications were also examined, along with the accuracy of correcting radiographic parameters to characterize dysplasia.Material and methods - The inclusion criteria were studies of human adolescents and adults (> 16 years) with primary or congenital hip dysplasia who were treated with a shelf arthroplasty procedure. Data were extracted concerning patient characteristics, survival time, complications, operative techniques, and accuracy of correcting radiographic parameters.Results - Our inclusion criteria were applicable to 9 studies. The average postoperative Center-Edge Angle and Acetabular Head Index were mostly within target range, but large variations were common. Kaplan-Meier curves (endpoint: conversion to THA) varied between 37% at 20 years' follow-up and 72% at 35 years' follow-up. Clinical failures were commonly associated with pain and radiographic osteoarthritis. Only minor complications were reported with incidences between 17% and 32%.Interpretation - The shelf arthroplasty is capable of restoring normal radiographic hip parameters and is not associated with major complications. When carefully selected on minimal osteoarthritic changes, hip dysplasia patients with a closed triradiate cartilage may benefit from the shelf procedure with satisfactory survival rates. The importance of the shelf arthroplasty in relation to peri-acetabular osteotomies needs to be further (re)explored.

Deep learning-based MR-to-CT synthesis: The influence of varying gradient echo-based MR images as input channels.

PURPOSE: To study the influence of gradient echo-based contrasts as input channels to a 3D patch-based neural network trained for synthetic CT (sCT) generation in canine and human populations. METHODS: Magnetic resonance images and CT scans of human and canine pelvic regions were acquired and paired using nonrigid registration. Magnitude MR images and Dixon reconstructed water, fat, in-phase and opposed-phase images were obtained from a single T1 -weighted multi-echo gradient-echo acquisition. From this set, 6 input configurations were defined, each containing 1 to 4 MR images regarded as input channels. For each configuration, a UNet-derived deep learning model was trained for synthetic CT generation. Reconstructed Hounsfield unit maps were evaluated with peak SNR, mean absolute error, and mean error. Dice similarity coefficient and surface distance maps assessed the geometric fidelity of bones. Repeatability was estimated by replicating the training up to 10 times. RESULTS: Seventeen canines and 23 human subjects were included in the study. Performance and repeatability of single-channel models were dependent on the TE-related water-fat interference with variations of up to 17% in mean absolute error, and variations of up to 28% specifically in bones. Repeatability, Dice similarity coefficient, and mean absolute error were statistically significantly better in multichannel models with mean absolute error ranging from 33 to 40 Hounsfield units in humans and from 35 to 47 Hounsfield units in canines. CONCLUSION: Significant differences in performance and robustness of deep learning models for synthetic CT generation were observed depending on the input. In-phase images outperformed opposed-phase images, and Dixon reconstructed multichannel inputs outperformed single-channel inputs.