127 research outputs found
AI MSK clinical applications: spine imaging
Recent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions
Deep Learning Convolutional Neural Network Reconstruction and Radial k-Space Acquisition MR Technique for Enhanced Detection of Retropatellar Cartilage Lesions of the Knee Joint
OBJECTIVES
To assess diagnostic performance of standard radial k-space (PROPELLER) MRI sequences and compare with accelerated acquisitions combined with a deep learning-based convolutional neural network (DL-CNN) reconstruction for evaluation of the knee joint.
METHODS
Thirty-five patients undergoing MR imaging of the knee at 1.5 T were prospectively included. Two readers evaluated image quality and diagnostic confidence of standard and DL-CNN accelerated PROPELLER MR sequences using a four-point Likert scale. Pathological findings of bone, cartilage, cruciate and collateral ligaments, menisci, and joint space were analyzed. Inter-reader agreement (IRA) for image quality and diagnostic confidence was assessed using intraclass coefficients (ICC). Cohen's Kappa method was used for evaluation of IRA and consensus between sequences in assessing different structures. In addition, image quality was quantitatively evaluated by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements.
RESULTS
Mean acquisition time of standard vs. DL-CNN sequences was 10 min 3 s vs. 4 min 45 s. DL-CNN sequences showed significantly superior image quality and diagnostic confidence compared to standard MR sequences. There was moderate and good IRA for assessment of image quality in standard and DL-CNN sequences with ICC of 0.524 and 0.830, respectively. Pathological findings of the knee joint could be equally well detected in both sequences (Îş-value of 0.8). Retropatellar cartilage could be significantly better assessed on DL-CNN sequences. SNR and CNR was significantly higher for DL-CNN sequences (both p < 0.05).
CONCLUSIONS
In MR imaging of the knee, DL-CNN sequences showed significantly higher image quality and diagnostic confidence compared to standard PROPELLER sequences, while reducing acquisition time substantially. Both sequences perform comparably in the detection of knee-joint pathologies, while DL-CNN sequences are superior for evaluation of retropatellar cartilage lesions
Is hypnosis a valid alternative to spontaneous breathing general anesthesia for claustrophobic patients undergoing MR exams? A preliminary retrospective study
Abstract Background The purpose of our retrospective study was to assess the termination rate and the image quality of MR exams performed in claustrophobic patients under medical hypnosis, as compared to patients undergoing MR under spontaneous breathing general anesthesia. Methods Our study was approved by the ethics committee. The “hypnosis group” included consecutive patients that had previously interrupted an MR exam because of claustrophobia. The “control group” included patients undergoing MR under pharmacologic sedation. Two experienced radiologists assessed, randomly, independently and blinded the image quality of the two groups using a symmetrical Likert scale: 0 = non-diagnostic images; 1 = bad image quality; 2 = fair image quality; 3 = good image quality; 4 = very good image quality. Descriptive statistics was performed. Results Eighty patients were included, equally distributed between the two groups. Every patient was able to complete the MR exam. Ratings 3 and 4 represented the majority of ratings. Both readers rated the MR exams with score 3 or 4 in 66.25% (53/80) of MR exams. Only 5% (4/80) of MR exams were rated below score 2. The majority of the MR exams showed good or very good image quality. No significant difference was found in image quality between the two (p = 0.06) groups. The agreement between the two readers according to the k score was 0.105. Conclusions Medical hypnosis is a valid alternative to spontaneous breathing general anesthesia in patients unable to undergo MR due to claustrophobia, allowing good quality images
C-arm flat-panel CT arthrography of the wrist and elbow: first experiences in human cadavers
Objective: To determine the optimal intra-articular iodine concentration for C-arm flat-panel computed tomography (FPCT) arthrography using advanced joint phantoms and to evaluate its application in human cadaveric wrists and elbows. Multi-detector (MD) CT served as the standard of reference. Materials and methods: Joint phantoms and 10 human cadaveric wrist and elbow joints were scanned with C-arm FPCT (5-s, 8-s, and 20-s runs) and standard MDCT using different and optimal concentrations of iodinated contrast material. CT numbers of contrast material, tissue, and noise were measured and contrast-to-noise ratios (CNR) calculated for quantitative analysis. Image and depiction of cartilage, bone, and soft tissues were rated. Radiation doses were compared. Results: In FPCT, iodine concentrations positively correlated with CT numbers and noise of contrast material and with radiation dose (r = 0.713-0.996, p < 0.05 each). At an iodine concentration of 45mg/ml, CNR of cartilage and soft tissues were highest for all FPCT acquisitions and higher than in MDCT. The 20-s FPCT run performed best for image quality and depiction of anatomical structures and was rated overall equal to MDCT (p = 0.857). Conclusion: The optimal iodine concentration for C-arm FPCT arthrography in this study is 45mg/ml, leading to superior CNR and image quality for an optimal FPCT protocol compared with standard MDCT arthrography in human cadaveric joint
Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography
OBJECTIVE
The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.
MATERIALS AND METHODS
Thirty-five exams (18 brachial and 17 lumbosacral plexus) of 34 patients undergoing routine clinical MR neurography at 1.5 T were retrospectively included (mean age: 49 ± 12 years, 15 female). Coronal 3D T2-weighted short tau inversion recovery fast spin echo with variable flip angle sequences covering plexial nerves on both sides were obtained as part of the standard protocol. In addition to standard-of-care (SOC) reconstruction, k-space was reconstructed with a 3D DLRecon algorithm. Two blinded readers evaluated images for image quality and diagnostic confidence in assessing nerves, muscles, and pathology using a 4-point scale. Additionally, signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR) between nerve, muscle, and fat were measured. For comparison of visual scoring result non-parametric paired sample Wilcoxon signed-rank testing and for quantitative analysis paired sample Student's t-testing was performed.
RESULTS
DLRecon scored significantly higher than SOC in all categories of image quality (p < 0.05) and diagnostic confidence (p < 0.05), including conspicuity of nerve branches and pathology. With regard to artifacts there was no significant difference between the reconstruction methods. Quantitatively, DLRecon achieved significantly higher CNR and SNR than SOC (p < 0.05).
CONCLUSION
DLRecon enhanced overall image quality, leading to improved conspicuity of nerve branches and pathology, and allowing for increased diagnostic confidence in evaluation of the brachial and lumbosacral plexus
Diffusion tensor imaging of the median nerve: intra-, inter-reader agreement, and agreement between two software packages
Objective: To assess intra-, inter-reader agreement, and the agreement between two software packages for magnetic resonance diffusion tensor imaging (DTI) measurements of the median nerve. Materials and methods: Fifteen healthy volunteers (seven men, eight women; mean age, 31.2years) underwent DTI of both wrists at 1.5T. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of the median nerve were measured by three readers using two commonly used software packages. Measurements were repeated by two readers after 6weeks. Intraclass correlation coefficients (ICC) and Bland-Altman analysis were used for statistical analysis. Results: ICCs for intra-reader agreement ranged from 0.87 to 0.99, for inter-reader agreement from 0.62 to 0.83, and between the two software packages from 0.63 to 0.82. Bland-Altman analysis showed no differences for intra- and inter-reader agreement and agreement between software packages. Conclusion: The intra-, inter-reader, and agreement between software packages for DTI measurements of the median nerve were moderate to substantial suggesting that user- and software-dependent factors contribute little to variance in DTI measurement
Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time
OBJECTIVES
To compare the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences with post-processed PROPELLER MRI sequences using deep learning-based (DL) reconstructions.
METHODS
In this prospective study of 30 patients, conventional (19 min 18 s) and accelerated MRI sequences (7 min 16 s) using the PROPELLER technique were acquired. Accelerated sequences were post-processed using DL. The image quality and diagnostic confidence were qualitatively assessed by 2 readers using a 5-point Likert scale. Analysis of the pathological findings of cartilage, rotator cuff tendons and muscles, glenoid labrum and subacromial bursa was performed. Inter-reader agreement was calculated using Cohen's kappa statistic. Quantitative evaluation of image quality was measured using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).
RESULTS
Mean image quality and diagnostic confidence in evaluation of all shoulder structures were higher in DL sequences (p value = 0.01). Inter-reader agreement ranged between kappa values of 0.155 (assessment of the bursa) and 0.947 (assessment of the rotator cuff muscles). In 17 cases, thickening of the subacromial bursa of more than 2 mm was only visible in DL sequences. The pathologies of the other structures could be properly evaluated by conventional and DL sequences. Mean SNR (p value = 0.01) and CNR (p value = 0.02) were significantly higher for DL sequences.
CONCLUSIONS
The accelerated PROPELLER sequences with DL post-processing showed superior image quality and higher diagnostic confidence compared to the conventional PROPELLER sequences. Subacromial bursa can be thoroughly assessed in DL sequences, while the other structures of the shoulder joint can be assessed in conventional and DL sequences with a good agreement between sequences.
KEY POINTS
• MRI of the shoulder requires long scan times and can be hampered by motion artifacts. • Deep learning-based convolutional neural networks are used to reduce image noise and scan time while maintaining optimal image quality. The radial k-space acquisition technique (PROPELLER) can reduce the scan time and has potential to reduce motion artifacts. • DL sequences show a higher diagnostic confidence than conventional sequences and therefore are preferred for assessment of the subacromial bursa, while conventional and DL sequences show comparable performance in the evaluation of the shoulder joint
Comparison of different CT metal artifact reduction strategies for standard titanium and carbon-fiber reinforced polymer implants in sheep cadavers
BACKGROUND
CT artifacts induced by orthopedic implants can limit image quality and diagnostic yield. As a number of different strategies to reduce artifact extent exist, the aim of this study was to systematically compare ex vivo the impact of different CT metal artifact reduction (MAR) strategies on spine implants made of either standard titanium or carbon-fiber-reinforced-polyetheretherketone (CFR-PEEK).
METHODS
Spine surgeons fluoroscopically-guided prepared six sheep spine cadavers with pedicle screws and rods of either titanium or CFR-PEEK. Samples were subjected to single- and dual-energy (DE) CT-imaging. Different tube voltages (80, DE mixed, 120 and tin-filtered 150 kVp) at comparable radiation dose and iterative reconstruction versus monoenergetic extrapolation (ME) techniques were compared. Also, the influence of image reconstruction kernels (soft vs. bone tissue) was investigated. Qualitative (Likert scores) and quantitative parameters (attenuation changes induced by implant artifact, implant diameter and image noise) were evaluated by two independent radiologists. Artifact degree of different MAR-strategies and implant materials were compared by multiple ANOVA analysis.
RESULTS
CFR-PEEK implants induced markedly less artifacts than standard titanium implants (p < .001). This effect was substantially larger than any other tested MAR technique. Reconstruction algorithms had small impact in CFR-PEEK implants and differed significantly in MAR efficiency (p < .001) with best MAR performance for DECT ME 130 keV (bone kernel). Significant differences in image noise between reconstruction kernels were seen (p < .001) with minor impact on artifact degree.
CONCLUSIONS
CFR-PEEK spine implants induce significantly less artifacts than standard titanium compositions with higher MAR efficiency than any alternate scanning or image reconstruction strategy. DECT ME 130Â keV image reconstructions showed least metal artifacts. Reconstruction kernels primarily modulate image noise with minor impact on artifact degree
Metal-induced artifacts in computed tomography and magnetic resonance imaging: comparison of a biodegradable magnesium alloy versus titanium and stainless steel controls
OBJECTIVE: To evaluate metal artifacts induced by biodegradable magnesium-a new class of degradable biomaterial that is beginning to enter the orthopedic routine-on CT and MRI compared to standard titanium and steel controls.
METHODS: Different pins made of titanium, stainless steel, and biodegradable magnesium alloys were scanned using a second-generation dual-energy multidetector CT and a 1.5-T MR scanner. In CT, quantitative assessment of artifacts was performed by two independent readers by measuring the noise in standardized regions of interest close to the pins. In MRI, the artifact diameter was measured. Interobserver agreement was evaluated using intraclass correlation coefficients. Artifacts were compared using Mann Whitney U tests.
RESULTS: In comparison to stainless steel, biodegradable magnesium alloys induced significantly fewer artifacts in both 1.5-T MRI (p = 0.019-0.021) and CT (p = 0.003-0.006). Compared to titanium, magnesium induced significantly less artifact-related noise in CT (p = 0.003-0.008). Although artifacts were less on MRI for biodegradable magnesium compared to titanium, this result was not statistically significant.
CONCLUSION: Biodegradable magnesium alloys induce substantially fewer artifacts in CT compared to standard titanium and stainless steel, and fewer artifacts in MRI for the comparison with stainless steel
Correlation of dynamic contrast-enhanced bone perfusion with morphologic ultra-short echo time MR imaging in medication-related osteonecrosis of the jaw
OBJECTIVES: To investigate whether dynamic contrast-enhanced (DCE)-MR bone perfusion could serve as surrogate for morphologic ultra-short echo time (UTE) bone images and to correlate perfusion with morphologic hallmarks in histologically proven foci of medication-related osteonecrosis of the jaw (MRONJ).
METHODS: Retrospective study including 20 patients with established diagnosis of MRONJ. Qualitative consensus assessment of predefined jaw regions by two radiologists was used as reference standard using Likert scale (0-3) for standard imaging hallmarks in MRONJ (osteolysis, sclerosis, periosteal thickening). DCE-MRI measurements performed in corresponding regions of the mandible were then correlated with qualitative scores. Regions were grouped into "non-affected" and "pathologic" based on binarized Likert scores of different imaging hallmarks (0-1 vs 2-3). DCE-MRI measurements among hallmarks were compared using Mann-Whitney-U-testing. ROC (receiver-operating-characteristic) analysis was performed for each of the perfusion parameters to assess diagnostic performance for identification of MRONJ using morphologic ratings as reference standard.
RESULTS: Median perfusion measurements of "pathologic" regions in wash-in, peak enhancement intensity and integrated area under the curve are significantly higher than those of "non-affected" regions, irrespective of reference imaging hallmark (p < 0.05). No significant perfusion differences were found between "pathologic" regions with and without osteolysis (p = 0.180). ROC analysis showed fair diagnostic performance of DCE-MRI parameters for identification of MRONJ (AUC 0.626-0.727).
CONCLUSIONS: DCE bone perfusion parameters are significantly increased in MRONJ compared to non-affected regions, irrespective of osteolysis. Due to certain overlap DCE-MRI bone perfusion cannot serve as full surrogate for UTE bone imaging but may enhance reader confidence
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