CT-like MRI: a qualitative assessment of ZTE sequences for knee osseous abnormalities

Deep learning reconstruction for optimized bone assessment in zero echo time MR imaging of the knee

PURPOSE

To evaluate the impact of deep learning-based reconstruction (DLRecon) on bone assessment in zero echo-time (ZTE) MRI of the knee at 1.5 Tesla.

METHODS

This retrospective study included 48 consecutive exams of 46 patients (23 females) who underwent clinically indicated knee MRI at 1.5 Tesla. Standard imaging protocol comprised a sagittal prescribed, isotropic ZTE sequence. ZTE image reconstruction was performed with a standard-of-care (non-DL) and prototype DLRecon method. Exams were divided into subsets with and without osseous pathology based on the radiology report. Using a 4-point scale, two blinded readers qualitatively graded features of bone depiction including artifacts and conspicuity of pathology including diagnostic certainty in the respective subsets. Quantitatively, one reader measured signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone. Comparative analyses were conducted to assess the differences between the reconstruction methods. In addition, interreader agreement was calculated for the qualitative gradings.

RESULTS

DLRecon significantly improved gradings for bone depiction relative to non-DL reconstruction (all, p < 0.05), while there was no significant difference with regards to artifacts (both, median score of 0; p = 0.058). In the subset with pathologies, conspicuity of pathology and diagnostic confidence were also scored significantly higher in DLRecon compared to non-DL (median 3 vs 2; p ≤ 0.03). Interreader agreement ranged from moderate to almost-perfect (κ = 0.54-0.88). Quantitatively, DLRecon demonstrated significantly enhanced CNR and SNR of bone compared to non-DL (p < 0.001).

CONCLUSION

ZTE MRI with DLRecon improved bone depiction in the knee, compared to non-DL. Additionally, DLRecon increased conspicuity of osseous findings together with diagnostic certainty.

CT-like images based on T1-weighted gradient echo MRI sequences for the assessment of fractures of the hand and wrist compared to CT

OBJECTIVE

To evaluate the performance of a 3D T1-weighted gradient-echo (3D T1GRE) computed tomography (CT)-like magnetic resonance imaging (MRI) sequence for detecting and assessing wrist and hand fractures compared to conventional CT.

METHODS

Subjects with acute wrist or hand fracture in CT underwent additional 3 T MRI including a CT-like 3D T1GRE sequence and were compared to patients without fractures. Two radiologists assessed fracture morphology on both modalities according to the Arbeitsgemeinschaft Osteosynthese (AO) and graded image quality and diagnostic confidence on a 5-point Likert scale. Besides diagnostic test evaluation, differences in image quality and diagnostic confidence between CT-like MRI and CT were calculated using the Wilcoxon test. Agreement of AO classification between modalities and readers was assessed using Cohen's Kappa.

RESULTS

Twenty-eight patients with 43 fractures and 43 controls were included. Image quality (3D T1GRE 1.19 ± 0.37 vs. CT 1.22 ± 0.42; p = 0.65) and diagnostic confidence (3D T1GRE 1.28 ± 0.53 vs. CT 1.28 ± 0.55; p = 1.00) were rated excellent for both modalities. Regarding the AO classification, intra- (rater 1 and rater 2, κ = 0.89; 95% CI 0.80-0.97) and interrater agreement were excellent (3D T1GRE, κ = 0.82; 95% CI, 0.70-0.93; CT, κ = 0.85; 95% CI, 0.75-0.94). CT-like MRI showed excellent sensitivity, specificity and accuracy for fracture detection (reader 1: 1.00, 0.92, 0.96; reader 2: 0.98, 0.94, 0.96).

CONCLUSION

CT-like MRI is a comparable alternative to CT for assessing hand and wrist fractures, offering the advantage of avoiding radiation exposure.

Enhanced bone assessment of the shoulder using zero-echo time MRI with deep-learning image reconstruction

OBJECTIVES

To assess a deep learning-based reconstruction algorithm (DLRecon) in zero echo-time (ZTE) MRI of the shoulder at 1.5 Tesla for improved delineation of osseous findings.

METHODS

In this retrospective study, 63 consecutive exams of 52 patients (28 female) undergoing shoulder MRI at 1.5 Tesla in clinical routine were included. Coronal 3D isotropic radial ZTE pulse sequences were acquired in the standard MR shoulder protocol. In addition to standard-of-care (SOC) image reconstruction, the same raw data was reconstructed with a vendor-supplied prototype DLRecon algorithm. Exams were classified into three subgroups: no pathological findings, degenerative changes, and posttraumatic changes, respectively. Two blinded readers performed bone assessment on a 4-point scale (0-poor, 3-perfect) by qualitatively grading image quality features and delineation of osseous pathologies including diagnostic confidence in the respective subgroups. Quantitatively, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were measured. Qualitative variables were compared using the Wilcoxon signed-rank test for ordinal data and the McNemar test for dichotomous variables; quantitative measures were compared with Student's t-testing.

RESULTS

DLRecon scored significantly higher than SOC in all visual metrics of image quality (all, p < 0.03), except in the artifact category (p = 0.37). DLRecon also received superior qualitative scores for delineation of osseous pathologies and diagnostic confidence (p ≤ 0.03). Quantitatively, DLRecon achieved superior CNR (95 CI [1.4-3.1]) and SNR (95 CI [15.3-21.5]) of bone than SOC (p < 0.001).

CONCLUSION

DLRecon enhanced image quality in ZTE MRI and improved delineation of osseous pathologies, allowing for increased diagnostic confidence in bone assessment.

Robot-Assisted Lumbar Pedicle Screw Placement Based on 3D Magnetic Resonance Imaging

STUDY DESIGN

Human Cadaveric Study.

OBJECTIVE

This study aims to explore the feasibility of using preoperative magnetic resonance imaging (MRI), zero-time-echo (ZTE) and spoiled gradient echo (SPGR), as source data for robotic-assisted spine surgery and assess the accuracy of pedicle screws.

METHODS

Zero-time-echo and SPGR MRI scans were conducted on a human cadaver. These images were manually post-processed, producing a computed tomography (CT)-like contrast. The Mazor X robot was used for lumbar pedicle screw-place navigating of MRI. The cadaver underwent a postoperative CT scan to determine the actual position of the navigated screws.

RESULTS

Ten lumbar pedicle screws were robotically navigated of MRI (4 ZTE; 6 SPGR). All MR-navigated screws were graded A on the Gertzbein-Robbins scale. Comparing preoperative robotic planning to postoperative CT scan trajectories: The screws showed a median deviation of overall 0.25 mm (0.0; 1.3), in the axial plane 0.27 mm (0.0; 1.3), and in the sagittal plane 0.24 mm (0.0; 0.7).

CONCLUSION

This study demonstrates the first successful registration of MRI sequences, ZTE and SPGR, in robotic spine surgery here used for intraoperative navigation of lumbar pedicle screws achieving sufficient accuracy, showcasing potential progress toward radiation-free spine surgery.

Quantitative Skeletal Imaging and Image-Based Modeling in Pediatric Orthopaedics

PURPOSE OF REVIEW

Musculoskeletal imaging serves a critical role in clinical care and orthopaedic research. Image-based modeling is also gaining traction as a useful tool in understanding skeletal morphology and mechanics. However, there are fewer studies on advanced imaging and modeling in pediatric populations. The purpose of this review is to provide an overview of recent literature on skeletal imaging modalities and modeling techniques with a special emphasis on current and future uses in pediatric research and clinical care.

RECENT FINDINGS

While many principles of imaging and 3D modeling are relevant across the lifespan, there are special considerations for pediatric musculoskeletal imaging and fewer studies of 3D skeletal modeling in pediatric populations. Improved understanding of bone morphology and growth during childhood in healthy and pathologic patients may provide new insight into the pathophysiology of pediatric-onset skeletal diseases and the biomechanics of bone development. Clinical translation of 3D modeling tools developed in orthopaedic research is limited by the requirement for manual image segmentation and the resources needed for segmentation, modeling, and analysis. This paper highlights the current and future uses of common musculoskeletal imaging modalities and 3D modeling techniques in pediatric orthopaedic clinical care and research.

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.

Deep-Learning-Aided Evaluation of Spondylolysis Imaged with Ultrashort Echo Time Magnetic Resonance Imaging

Isthmic spondylolysis results in fracture of pars interarticularis of the lumbar spine, found in as many as half of adolescent athletes with persistent low back pain. While computed tomography (CT) is the gold standard for the diagnosis of spondylolysis, the use of ionizing radiation near reproductive organs in young subjects is undesirable. While magnetic resonance imaging (MRI) is preferable, it has lowered sensitivity for detecting the condition. Recently, it has been shown that ultrashort echo time (UTE) MRI can provide markedly improved bone contrast compared to conventional MRI. To take UTE MRI further, we developed supervised deep learning tools to generate (1) CT-like images and (2) saliency maps of fracture probability from UTE MRI, using ex vivo preparation of cadaveric spines. We further compared quantitative metrics of the contrast-to-noise ratio (CNR), mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) between UTE MRI (inverted to make the appearance similar to CT) and CT and between CT-like images and CT. Qualitative results demonstrated the feasibility of successfully generating CT-like images from UTE MRI to provide easier interpretability for bone fractures thanks to improved image contrast and CNR. Quantitatively, the mean CNR of bone against defect-filled tissue was 35, 97, and 146 for UTE MRI, CT-like, and CT images, respectively, being significantly higher for CT-like than UTE MRI images. For the image similarity metrics using the CT image as the reference, CT-like images provided a significantly lower mean MSE (0.038 vs. 0.0528), higher mean PSNR (28.6 vs. 16.5), and higher SSIM (0.73 vs. 0.68) compared to UTE MRI images. Additionally, the saliency maps enabled quick detection of the location with probable pars fracture by providing visual cues to the reader. This proof-of-concept study is limited to the data from ex vivo samples, and additional work in human subjects with spondylolysis would be necessary to refine the models for clinical use. Nonetheless, this study shows that the utilization of UTE MRI and deep learning tools could be highly useful for the evaluation of isthmic spondylolysis.

Bone Tissue in Magnetic Resonance Imaging: Contribution of New Zero Echo Time Sequences

The introduction of new ultrashort and zero echo time (ZTE) sequences is revolutionizing magnetic resonance imaging (MRI) and optimizing patient management. These sequences acquire signals in tissues with very short T2: mineralized bone, cortical bone, and calcium deposits. They can be added to a classic MRI protocol. ZTE MRI provides computed tomography-like contrast for bone.

MR Imaging of Acute Knee Injuries: Systematic Evaluation and Reporting

Acute knee injury ranges among the most common joint injuries in professional and recreational athletes. Radiographs can detect joint effusion, fractures, deformities, and malalignment; however, MR imaging is most accurate for radiographically occult fractures, chondral injury, and soft tissue injuries. Using a structured checklist approach for systematic MR imaging evaluation and reporting, this article reviews the MR imaging appearances of the spectrum of traumatic knee injuries, including osteochondral injuries, cruciate ligament tears, meniscus tears and ramp lesions, anterolateral complex and collateral ligament injuries, patellofemoral translation, extensor mechanism tears, and nerve and vascular injuries.

Synthetic CT in Musculoskeletal Disorders: A Systematic Review

ABSTRACT

Repeated computed tomography (CT) examinations increase patients' ionizing radiation exposure and health costs, making an alternative method desirable. Cortical and trabecular bone, however, have short T2 relaxation times, causing low signal intensity on conventional magnetic resonance (MR) sequences. Different techniques are available to create a "CT-like" contrast of bone, such as ultrashort echo time, zero echo time, gradient-echo, and susceptibility-weighted image MR sequences, and artificial intelligence. This systematic review summarizes the essential technical background and developments of ultrashort echo time, zero echo time, gradient-echo, susceptibility-weighted image MR imaging sequences and artificial intelligence; presents studies on research and clinical applications of "CT-like" MR imaging; and describes their main advantages and limitations. We also discuss future opportunities in research, which patients would benefit the most, the most appropriate situations for using the technique, and the potential to replace CT in the clinical workflow.

Detailed bone assessment of the sacroiliac joint in a prospective imaging study: comparison between computed tomography, zero echo time, and black bone magnetic resonance imaging

OBJECTIVES

To compare the value of zero echo time (ZTE) and gradient echo "black bone" (BB) MRI sequences for bone assessment of the sacroiliac joint (SI) using computed tomography (CT) as the reference standard.

MATERIALS AND METHODS

Between May 2019 and January 2021, 79 patients prospectively underwent clinically indicated 3-T MRI including ZTE and BB imaging. Additionally, all patients underwent a CT scan covering the SI joints within 12 months of the MRI examination. Two blinded readers performed bone assessment by grading each side of each SI joint qualitatively in terms of seven features (osteophytes, subchondral sclerosis, erosions, ankylosis, joint irregularity, joint widening, and gas in the SI joint) using a 4-point Likert scale (0 = no changes-3 = marked changes). Scores were compared between all three imaging modalities.

RESULTS

Interreader agreement was largely good (k values: 0.5-0.83). Except for the feature "gas in SI joint" where ZTE exhibited significantly lower scores than CT (p < 0.001), ZTE and BB showed similar performance relative to CT for all other features (p > 0.52) with inter-modality agreement being substantial to almost perfect (Krippendorff's alpha coefficients: 0.724-0.983). When combining the data from all features except for gas in the SI joint and when binarizing grading scores, combined sensitivity/specificity was 76.7%/98.6% for ZTE and 80.8%/99.1% for BB, respectively, compared to CT.

CONCLUSIONS

The performance of ZTE and BB sequences was comparable to CT for bone assessment of the SI joint. These sequences may potentially serve as an alternative to CT yet without involving exposure to ionizing radiation.