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.

MRI-based synthetic CT in the detection of knee osteoarthritis: Comparison with CT.

Magnetic resonance Imaging is the gold standard for assessment of soft tissues; however, X-ray-based techniques are required for evaluating bone-related pathologies. This study evaluated the performance of synthetic computed tomography (sCT), a novel MRI-based bone visualization technique, compared with CT, for the scoring of knee osteoarthritis. sCT images were generated from the 3T T1-weighted gradient-echo MR images using a trained machine learning algorithm. Two readers scored the severity of osteoarthritis in tibiofemoral and patellofemoral joints according to OACT, which enables the evaluation of osteoarthritis, from its characteristics of joint space narrowing, osteophytes, cysts and sclerosis in CT (and sCT) images. Cohen's κ was used to assess the interreader agreement for each modality, and intermodality agreement of CT- and sCT-based scores for each reader. We also compared the confidence level of readers for grading CT and sCT images using confidence scores collected during grading. Inter-reader agreement for tibiofemoral and patellofemoral joints were almost-perfect for both modalities (κ = 0.83-0.88). The intermodality agreement of osteoarthritis scores between CT and sCT was substantial to almost-perfect for tibiofemoral (κ = 0.63 and 0.84 for the two readers) and patellofemoral joints (κ = 0.78 and 0.81 for the two readers). The analysis of diagnosis confidence scores showed comparable visual quality of the two modalities, where both are showing acceptable confidence levels for scoring OA. In conclusion, in this single-center study, sCT and CT were comparable for the scoring of knee OA.

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.

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.

Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning.

PURPOSE: Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine learning has proven its value in medical image segmentation, including the kidneys. This study presents a fully automatic workflow for renal cortex perfusion quantification by including machine learning-based segmentation. METHODS: Fully automatic workflow was achieved by construction of a cascade of 3 U-nets to replace manual segmentation in ASL quantification. All 1.5T ASL-MRI data, including M0 , T1 , and ASL label-control images, from 10 healthy volunteers was used for training (dataset 1). Trained cascade performance was validated on 4 additional volunteers (dataset 2). Manual segmentations were generated by 2 observers, yielding reference and second observer segmentations. To validate the intended use of the automatic segmentations, manual and automatic RBF values in mL/min/100 g were compared. RESULTS: Good agreement was found between automatic and manual segmentations on dataset 1 (dice score = 0.78 ± 0.04), which was in line with inter-observer variability (dice score = 0.77 ± 0.02). Good agreement was confirmed on dataset 2 (dice score = 0.75 ± 0.03). Moreover, similar cortical RBF was obtained with automatic or manual segmentations, on average and at subject level; with 211 ± 31 mL/min/100 g and 208 ± 31 mL/min/100 g (P < .05), respectively, with narrow limits of agreement at -11 and 4.6 mL/min/100 g. RBF accuracy with automated segmentations was confirmed on dataset 2. CONCLUSION: Our proposed method automates ASL quantification without compromising RBF accuracy. With quick processing and without observer dependence, renal ASL-MRI is more attractive for clinical application as well as for longitudinal and multi-center studies.

Perfusion imaging of neuroblastoma and nephroblastoma in a paediatric population using pseudo-continuous arterial spin-labelling magnetic resonance imaging.

OBJECTIVES: To examine the feasibility of performing ASL-MRI in paediatric patients with solid abdominal tumours. METHODS: Multi-delay ASL data sets were acquired in ten paediatric patients diagnosed with either a neuroblastoma (n = 4) or nephroblastoma (n = 6) during a diagnostic MRI examination at a single visit (n = 4 at initial staging, n = 2 neuroblastoma and n = 2 nephroblastoma patients; n = 6 during follow-up, n = 2 neuroblastoma and n = 4 nephroblastoma patients). Visual evaluation and region-of-interest (ROI) analyses were performed on the processed perfusion-weighted images to assess ASL perfusion signal dynamics in the whole tumour, contralateral kidney, and tumour sub-regions with/without contrast enhancement. RESULTS: The majority of the included abdominal tumours presented with relatively low perfusion-weighted signal (PWS), especially compared with the highly perfused kidneys. Within the tumours, regions with high PWS were observed which, at short PLD, are possibly related to labelled blood inside vessels and at long PLD, reflect labelled blood accumulating inside tumour tissue over time. Conversely, comparison of ASL perfusion-weighted image findings with T1w enhancement after contrast administration showed that regions lacking contrast enhancement also were void of PWS. DISCUSSION: This pilot study demonstrates the feasibility of utilizing ASL-MRI in paediatric patients with solid abdominal tumours and provides a basis for further research on non-invasive perfusion measurements in this study population.

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.

Disc and Vertebral Body Morphology From Birth to Adulthood.

STUDY DESIGN: Cross-sectional. OBJECTIVE: The aim of this study was to describe the morphology of intervertebral discs and vertebral bodies during growth in asymptomatic children and adolescents. SUMMARY OF BACKGROUND DATA: Earlier studies demonstrated that spinal growth occurs predominantly in vertebral bodies. This axiom introduced a vertebral-body-focus for unravelling etiological questions and achieve growth-modulation in young spinal deformity patients. Recent studies show the importance of the intervertebral discs in the early phases and possible etiology of pediatric spinal deformities. There is presently a paucity of 3D morphometric data of spinal elements during growth. METHODS: A database of 298 patients aged 0 to 21 that have received a computed tomography scan for indications not related to the spine was analyzed. Custom made software was used to semi-automatically measure intervertebral disc and vertebral body morphology, corrected for orientation in all 3 planes. RESULTS: Vertebral body height increased from birth up to adulthood, from 4-to-14 mm in the cervical, 6 to 20 mm in the thoracic, and 9 to 28 mm in the lumbar spine. This increase was 0.70 mm/year in males, more pronounced than females with 0.62 mm/year (P = 0.001). Lumbar discs increased throughout growth from 4.4 to 9.0 mm, whereas thoracic discs only increased from 3.5 to 4.9 mm at age 4 and remained stable afterwards, similarly for cervical discs. The disc transverse surface area increased greatly and consistently throughout growth. Disc slenderness was stable in the lumbar spine during growth, but decreased in the thoracic and cervical spine. Overall, discs were more slender in females, especially around early adolescence. CONCLUSION: The spine grows predominantly in the vertebral bodies. Thoracic discs increase in height only during the first years, whereas the transverse surface area continues to increase throughout growth, thus discs slenderness decreases. Relatively, female discs remained slenderer around growth-spurt. These measurements may assist future studies on the role of disc morphology in the etiology and treatment of spinal deformity.Level of Evidence: 4.

Prospective Evaluation of Local Sustained Release of Celecoxib in Dogs with Low Back Pain.

Back pain affects millions globally and in 40% of the cases is attributed to intervertebral disc degeneration. Oral analgesics are associated with adverse systemic side-effects and insufficient pain relief. Local drug delivery mitigates systemic effects and accomplishes higher local dosing. Clinical efficacy of intradiscally injected celecoxib (CXB)-loaded polyesteramide microspheres (PEAMs) was studied in a randomized prospective double-blinded placebo controlled veterinary study. Client-owned dog patients suffering from back pain were treated with CXB-loaded (n = 20) or unloaded PEAMs ("placebo") (n = 10) and evaluated by clinical examination, gait analysis, owners' questionnaires, and MRI at 6 and 12 weeks follow-up. At 6 and 12 weeks, CXB-treated dogs experienced significantly less pain interference with their daily life activities compared to placebo. The risk ratio for treatment success was 1.90 (95% C.I. 1.24-2.91, p = 0.023) at week 6 and 1.95 (95% C.I. 1.10-3.45, p = 0.036) at week 12. The beneficial effects of CXB-PEAMs were more pronounced for the subpopulation of male dogs and those with no Modic changes in MRI at inclusion in the study; disc protrusion did not affect the outcome. It remains to be determined whether intradiscal injection of CXB-PEAMs, in addition to analgesic properties, has the ability to halt the degenerative process in the long term or restore the disc.

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.

Feasibility of Velocity-Selective Arterial Spin Labeling in Breast Cancer Patients for Noncontrast-Enhanced Perfusion Imaging.

BACKGROUND: Dynamic contrast-enhanced (DCE) MRI is the most sensitive method for detection of breast cancer. However, due to high costs and retention of intravenously injected gadolinium-based contrast agent, screening with DCE-MRI is only recommended for patients who are at high risk for developing breast cancer. Thus, a noncontrast-enhanced alternative to DCE is desirable. PURPOSE: To investigate whether velocity selective arterial spin labeling (VS-ASL) can be used to identify increased perfusion and vascularity within breast lesions compared to surrounding tissue. STUDY TYPE: Prospective. POPULATION: Eight breast cancer patients. FIELD STRENGTH/SEQUENCE: A 3 T; VS-ASL with multislice single-shot gradient-echo echo-planar-imaging readout. ASSESSMENT: VS-ASL scans were independently assessed by three radiologists, with 3-25 years of experience in breast radiology. Scans were scored on lesion visibility and artifacts, based on a 3-point Likert scale. A score of 1 corresponded to "lesions being distinguishable from background" (lesion visibility), and "no or few artifacts visible, artifacts can be distinguished from blood signal" (artifact score). A distinction was made between mass and nonmass lesions (based on BI-RADS lexicon), as assessed in the standard clinical exam. STATISTICAL TESTS: Intra-class correlation coefficient (ICC) for interobserver agreement. RESULTS: The ICC was 0.77 for lesion visibility and 0.84 for the artifact score. Overall, mass lesions had a mean score of 1.27 on lesion visibility and 1.53 on the artifact score. Nonmass lesions had a mean score of 2.11 on lesion visibility and 2.11 on the artifact score. DATA CONCLUSION: We have demonstrated the technical feasibility of bilateral whole-breast perfusion imaging using VS-ASL in breast cancer patients. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

What a stranded whale with scoliosis can teach us about human idiopathic scoliosis.

Scoliosis is a deformation of the spine that may have several known causes, but humans are the only mammal known to develop scoliosis without any obvious underlying cause. This is called 'idiopathic' scoliosis and is the most common type. Recent observations showed that human scoliosis, regardless of its cause, has a relatively uniform three-dimensional anatomy. We hypothesize that scoliosis is a universal compensatory mechanism of the spine, independent of cause and/or species. We had the opportunity to study the rare occurrence of scoliosis in a whale (Balaenoptera acutorostrata) that stranded in July 2019 in the Netherlands. A multidisciplinary team of biologists, pathologists, veterinarians, taxidermists, radiologists and orthopaedic surgeons conducted necropsy and imaging analysis. Blunt traumatic injury to two vertebrae caused an acute lateral deviation of the spine, which had initiated the development of compensatory curves in regions of the spine without anatomical abnormalities. Three-dimensional analysis of these compensatory curves showed strong resemblance with different types of human scoliosis, amongst which idiopathic. This suggests that any decompensation of spinal equilibrium can lead to a rather uniform response. The unique biomechanics of the upright human spine, with significantly decreased rotational stability, may explain why only in humans this mechanism can be induced relatively easily, without an obvious cause, and is therefore still called 'idiopathic'.

Exploring label dynamics of velocity-selective arterial spin labeling in the kidney.

PURPOSE: Velocity-selective arterial spin labeling (VSASL) has been proposed for renal perfusion imaging to mitigate planning challenges and effects of arterial transit time (ATT) uncertainties. In VSASL, label generation may shift in the vascular tree as a function of cutoff velocity. Here, we investigate label dynamics and especially the ATT of renal VSASL and compared it with a spatially selective pulsed arterial spin labeling technique, flow alternating inversion recovery (FAIR). METHODS: Arterial spin labeling data were acquired in 7 subjects, using free-breathing dual VSASL and FAIR with five postlabeling delays: 400, 800, 1200, 2000, and 2600 ms. The VSASL measurements were acquired with cutoff velocities of 5, 10, and 15 cm/s, with anterior-posterior velocity-encoding direction. Cortical perfusion-weighted signal, temporal SNR, quantified renal blood flow, and arterial transit time were reported. RESULTS: In contrast to FAIR, renal VSASL already showed fairly high signal at the earliest postlabeling delays, for all cutoff velocities. The highest VSASL signal and temporal SNR was obtained with a cutoff velocity of 10 cm/s at postlabeling delay = 800 ms, which was earlier than for FAIR at 1200 ms. Fitted ATT on VSASL was ≤ 0 ms, indicating ATT insensitivity, which was shorter than for FAIR (189 ± 79 ms, P < .05). Finally, the average cortical renal blood flow measured with cutoff velocities of 5 cm/s (398 ± 84 mL/min/100 g) and 10 cm/s (472 ± 160 mL/min/100 g) were similar to renal blood flow measured with FAIR (441 ± 84 mL/min/100 g) (P > .05) with good correlations on subject level. CONCLUSION: Velocity-selective arterial spin labeling in the kidney reduces ATT sensitivity compared with the recommended pulsed arterial spin labeling method, as well as if cutoff velocity is increased to reduce spurious labeling due to motion. Thus, VSASL has potential as a method for time-efficient, single-time-point, free-breathing renal perfusion measurements, despite lower tSNR than FAIR.

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.

Multi-organ comparison of flow-based arterial spin labeling techniques: Spatially non-selective labeling for cerebral and renal perfusion imaging.

PURPOSE: Flow-based arterial spin labeling (ASL) techniques provide a transit-time insensitive alternative to the more conventional spatially selective ASL techniques. However, it is not clear which flow-based ASL technique performs best and also, how these techniques perform outside the brain (taking into account eg, flow-dynamics, field-inhomogeneity, and organ motion). In the current study we aimed to compare 4 flow-based ASL techniques (ie, velocity selective ASL, acceleration selective ASL, multiple velocity selective saturation ASL, and velocity selective inversion prepared ASL [VSI-ASL]) to the current spatially selective reference techniques in brain (ie, pseudo-continuous ASL [pCASL]) and kidney (ie, pCASL and flow alternating inversion recovery [FAIR]). METHODS: Brain (n = 5) and kidney (n = 6) scans were performed in healthy subjects at 3T. Perfusion-weighted signal (PWS) maps were generated and ASL techniques were compared based on temporal SNR (tSNR), sensitivity to perfusion changes using a visual stimulus (brain) and robustness to respiratory motion by comparing scans acquired in paced-breathing and free-breathing (kidney). RESULTS: In brain, all flow-based ASL techniques showed similar tSNR as pCASL, but only VSI-ASL showed similar sensitivity to perfusion changes. In kidney, all flow-based ASL techniques had comparable tSNR, although all lower than FAIR. In addition, VSI-ASL showed a sensitivity to B1 -inhomogeneity. All ASL techniques were relatively robust to respiratory motion. CONCLUSION: In both brain and kidney, flow-based ASL techniques provide a planning-free and transit-time insensitive alternative to spatially selective ASL techniques. VSI-ASL shows the most potential overall, showing similar performance as the golden standard pCASL in brain. However, in kidney, a reduction of B1 -sensitivity of VSI-ASL is necessary to match the performance of FAIR.

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.

Influence of labeling parameters and respiratory motion on velocity-selective arterial spin labeling for renal perfusion imaging.

PURPOSE: Arterial transit time uncertainties and challenges during planning are potential issues for renal perfusion measurement using spatially selective arterial spin labeling techniques. To mitigate these potential issues, a spatially non-selective technique, such as velocity-selective arterial spin labeling (VSASL), could be an alternative. This article explores the influence of VSASL sequence parameters and respiratory induced motion on VS-label generation. METHODS: VSASL data were acquired in human subjects (n = 15), with both single and dual labeling, during paced-breathing, while essential sequence parameters were systematically varied; (1) cutoff velocity, (2) labeling gradient orientation and (3) post-labeling delay (PLD). Pseudo-continuous ASL was acquired as a spatially selective reference. In an additional free-breathing single VSASL experiment (n = 9) we investigated respiratory motion influence on VS-labeling. Absolute renal blood flow (RBF), perfusion weighted signal (PWS), and temporal signal-to-noise ratio (tSNR) were determined. RESULTS: (1) With decreasing cutoff velocity, tSNR and PWS increased. However, undesired tissue labeling occurred at low cutoff velocities (≤ 5.4 cm/s). (2) Labeling gradient orientation had little effect on tSNR and PWS. (3) For single VSASL high signal appeared in the kidney pedicle at PLD < 800 ms, and tSNR and PWS decreased with increasing PLD. For dual VSASL, maximum tSNR occurred at PLD = 1200 ms. Average cortical RBF measured with dual VSASL (264 ± 34 mL/min/100 g) at a cutoff velocity of 5.4 cm/s, and feet-head labeling was slightly lower than with pseudo-continuous ASL (283 ± 55 mL/min/100 g). CONCLUSION: With well-chosen sequence parameters, tissue labeling induced by respiratory motion can be minimized, allowing to obtain good quality RBF maps using planning-free labeling with dual VSASL.