1
|
Gassert FT, Kufner A, Renz M, Gassert FG, Bollwein C, Kronthaler S, Feuerriegel GC, Kirschke JS, Ganter C, Makowski MR, Braun C, Schwaiger BJ, Woertler K, Karampinos DC, Gersing AS. Comparing CT-Like Images Based on Ultra-Short Echo Time and Gradient Echo T1-Weighted MRI Sequences for the Assessment of Vertebral Disorders Using Histology and True CT as the Reference Standard. J Magn Reson Imaging 2024; 59:1542-1552. [PMID: 37501387 DOI: 10.1002/jmri.28927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND Several magnetic resonance (MR) techniques have been suggested for radiation-free imaging of osseous structures. PURPOSE To compare the diagnostic value of ultra-short echo time and gradient echo T1-weighted MRI for the assessment of vertebral pathologies using histology and computed tomography (CT) as the reference standard. STUDY TYPE Prospective. SUBJECTS Fifty-nine lumbar vertebral bodies harvested from 20 human cadavers (donor age 73 ± 13 years; 9 male). FIELD STRENGTH/SEQUENCE Ultra-short echo time sequence optimized for both bone (UTEb) and cartilage (UTEc) imaging and 3D T1-weighted gradient-echo sequence (T1GRE) at 3 T; susceptibility-weighted imaging (SWI) gradient echo sequence at 1.5 T. CT was performed on a dual-layer dual-energy CT scanner using a routine clinical protocol. ASSESSMENT Histopathology and conventional CT were acquired as standard of reference. Semi-quantitative and quantitative morphological features of degenerative changes of the spines were evaluated by four radiologists independently on CT and MR images independently and blinded to all other information. Features assessed were osteophytes, endplate sclerosis, visualization of cartilaginous endplate, facet joint degeneration, presence of Schmorl's nodes, and vertebral dimensions. Vertebral disorders were assessed by a pathologist on histology. STATISTICAL TESTS Agreement between T1GRE, SWI, UTEc, and UTEb sequences and CT imaging and histology as standard of reference were assessed using Fleiss' κ and intra-class correlation coefficients, respectively. RESULTS For the morphological assessment of osteophytes and endplate sclerosis, the overall agreement between SWI, T1GRE, UTEb, and UTEc with the reference standard (histology combined with CT) was moderate to almost perfect for all readers (osteophytes: SWI, κ range: 0.68-0.76; T1GRE: 0.92-1.00; UTEb: 0.92-1.00; UTEc: 0.77-0.85; sclerosis: SWI, κ range: 0.60-0.70; T1GRE: 0.77-0.82; UTEb: 0.81-0.92; UTEc: 0.61-0.71). For the visualization of the cartilaginous endplate, UTEc showed the overall best agreement with the reference standard (histology) for all readers (κ range: 0.85-0.93). DATA CONCLUSIONS Morphological assessment of vertebral pathologies was feasible and accurate using the MR-based bone imaging sequences compared to CT and histopathology. T1GRE showed the overall best performance for osseous changes and UTEc for the visualization of the cartilaginous endplate. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Florian T Gassert
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexander Kufner
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Martin Renz
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Felix G Gassert
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christine Bollwein
- Department of Pathology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Georg C Feuerriegel
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Carl Ganter
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Braun
- Institute of Forensic Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Neuroradiology, University Hospital of Munich, LMU Munich, Munich, Germany
| |
Collapse
|
2
|
Feuerriegel GC, Kronthaler S, Weiss K, Haller B, Leonhardt Y, Neumann J, Pfeiffer D, Hesse N, Erber B, Schwaiger BJ, Makowski MR, Woertler K, Karampinos DC, Wurm M, Gersing AS. Assessment of glenoid bone loss and other osseous shoulder pathologies comparing MR-based CT-like images with conventional CT. Eur Radiol 2023; 33:8617-8626. [PMID: 37453986 PMCID: PMC10667374 DOI: 10.1007/s00330-023-09939-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/24/2023] [Accepted: 05/16/2023] [Indexed: 07/18/2023]
Abstract
OBJECTIVES To evaluate and compare the diagnostic performance of CT-like images based on a 3D T1-weighted spoiled gradient-echo sequence (T1 GRE), an ultra-short echo time sequence (UTE), and a 3D T1-weighted spoiled multi-echo gradient-echo sequence (FRACTURE) with conventional CT in patients with suspected osseous shoulder pathologies. MATERIALS AND METHODS Patients with suspected traumatic dislocation of the shoulder (n = 46, mean age 40 ± 14.5 years, 19 women) were prospectively recruited and received 3-T MR imaging including 3D T1 GRE, UTE, and 3D FRACTURE sequences. CT was performed in patients with acute fractures and served as standard of reference (n = 25). Agreement of morphological features between the modalities was analyzed including the glenoid bone loss, Hill-Sachs interval, glenoid track, and the anterior straight-line length. Agreement between the modalities was assessed using Bland-Altman plots, Student's t-test, and Pearson's correlation coefficient. Inter- and intrareader assessment was evaluated with weighted Cohen's κ and intraclass correlation coefficient. RESULTS All osseous pathologies were detected accurately on all three CT-like sequences (n = 25, κ = 1.00). No significant difference in the percentage of glenoid bone loss was found between CT (mean ± standard deviation, 20.3% ± 8.0) and CT-like MR images (FRACTURE 20.6% ± 7.9, T1 GRE 20.4% ± 7.6, UTE 20.3% ± 7.7, p > 0.05). When comparing the different measurements on CT-like images, measurements performed using the UTE images correlated best with CT. CONCLUSION Assessment of bony Bankart lesions and other osseous pathologies was feasible and accurate using CT-like images based on 3-T MRI compared with conventional CT. Compared to the T1 GRE and FRACTURE sequence, the UTE measurements correlated best with CT. CLINICAL RELEVANCE STATEMENT In an acute trauma setting, CT-like images based on a T1 GRE, UTE, or FRACTURE sequence might be a useful alternative to conventional CT scan sparing associated costs as well as radiation exposure. KEY POINTS • No significant differences were found for the assessment of the glenoid bone loss when comparing measurements of CT-like MR images with measurements of conventional CT images. • Compared to the T1 GRE and FRACTURE sequence, the UTE measurements correlated best with CT whereas the FRACTURE sequence appeared to be the most robust regarding motion artifacts. • The T1 GRE sequence had the highest resolution with high bone contrast and detailed delineation of even small fractures but was more susceptible to motion artifacts.
Collapse
Affiliation(s)
- Georg C Feuerriegel
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany.
| | - Sophia Kronthaler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | | | - Bernhard Haller
- Institute of Medical Informatics, Statistics and Epidemiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Yannik Leonhardt
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Jan Neumann
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Daniela Pfeiffer
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Nina Hesse
- Department of Radiology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Bernd Erber
- Department of Radiology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Markus Wurm
- Department of Trauma Surgery, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Department of Neuroradiology, University Hospital of Munich, LMU Munich, Munich, Germany
| |
Collapse
|
3
|
Feuerriegel GC, Weiss K, Kronthaler S, Leonhardt Y, Neumann J, Wurm M, Lenhart NS, Makowski MR, Schwaiger BJ, Woertler K, Karampinos DC, Gersing AS. Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain. Eur Radiol 2023; 33:4875-4884. [PMID: 36806569 PMCID: PMC10289918 DOI: 10.1007/s00330-023-09472-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/07/2023] [Accepted: 01/22/2023] [Indexed: 02/21/2023]
Abstract
OBJECTIVES To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR images in patients with shoulder pain. METHODS Prospectively, thirty-eight patients (14 women, mean age 40.0 ± 15.2 years) with shoulder pain underwent morphological MRI using a pseudo-random, density-weighted k-space scheme with an acceleration factor of 2.5 using CS only. An automated DL-based algorithm (CS DL) was used to create reconstructions of the same k-space data as used for CS reconstructions. Images were analyzed by two radiologists and assessed for pathologies, image quality, and visibility of anatomical landmarks using a 4-point Likert scale. RESULTS Overall agreement for the detection of pathologies between the CS DL reconstructions and CS images was substantial to almost perfect (κ 0.95 (95% confidence interval 0.82-1.00)). Image quality and the visibility of the rotator cuff, articular cartilage, and axillary recess were overall rated significantly higher for CS DL images compared to CS (p < 0.03). Contrast-to-noise ratios were significantly higher for cartilage/fluid (CS DL 198 ± 24.3, CS 130 ± 32.2, p = 0.02) and ligament/fluid (CS DL 184 ± 17.3, CS 141 ± 23.5, p = 0.03) and SNR values were significantly higher for ligaments and muscle of the CS DL reconstructions (p < 0.04). CONCLUSION Evaluation of shoulder pathologies was feasible using a DL-based algorithm for MRI reconstruction and denoising. In clinical routine, CS DL may be beneficial in particular for reducing image noise and may be useful for the detection and better discrimination of discrete pathologies. Assessment of shoulder pathologies was feasible with improved image quality as well as higher SNR using a compressed sensing deep learning-based framework for image reconstructions and denoising. KEY POINTS • Automated deep learning-based reconstructions showed a significant increase in signal-to-noise ratio and contrast-to-noise ratio (p < 0.04) with only a slight increase of reconstruction time of 40 s compared to CS. • All pathologies were accurately detected with no loss of diagnostic information or prolongation of the scan time. • Significant improvements of the image quality as well as the visibility of the rotator cuff, articular cartilage, and axillary recess were detected.
Collapse
Affiliation(s)
- Georg C Feuerriegel
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany.
| | | | - Sophia Kronthaler
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Yannik Leonhardt
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Jan Neumann
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Markus Wurm
- Department of Trauma Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Nicolas S Lenhart
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Alexandra S Gersing
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Department of Neuroradiology, University Hospital of Munich, LMU Munich, Munich, Germany
| |
Collapse
|
4
|
Sollmann N, Kirschke JS, Kronthaler S, Boehm C, Dieckmeyer M, Vogele D, Kloth C, Lisson CG, Carballido-Gamio J, Link TM, Karampinos DC, Karupppasamy S, Beer M, Krug R, Baum T. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. ROFO-FORTSCHR RONTG 2022; 194:1088-1099. [PMID: 35545103 DOI: 10.1055/a-1770-4626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Osteoporosis is a highly prevalent systemic skeletal disease that is characterized by low bone mass and microarchitectural bone deterioration. It predisposes to fragility fractures that can occur at various sites of the skeleton, but vertebral fractures (VFs) have been shown to be particularly common. Prevention strategies and timely intervention depend on reliable diagnosis and prediction of the individual fracture risk, and dual-energy X-ray absorptiometry (DXA) has been the reference standard for decades. Yet, DXA has its inherent limitations, and other techniques have shown potential as viable add-on or even stand-alone options. Specifically, three-dimensional (3 D) imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), are playing an increasing role. For CT, recent advances in medical image analysis now allow automatic vertebral segmentation and value extraction from single vertebral bodies using a deep-learning-based architecture that can be implemented in clinical practice. Regarding MRI, a variety of methods have been developed over recent years, including magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) that enable the extraction of a vertebral body's proton density fat fraction (PDFF) as a promising surrogate biomarker of bone health. Yet, imaging data from CT or MRI may be more efficiently used when combined with advanced analysis techniques such as texture analysis (TA; to provide spatially resolved assessments of vertebral body composition) or finite element analysis (FEA; to provide estimates of bone strength) to further improve fracture prediction. However, distinct and experimentally validated diagnostic criteria for osteoporosis based on CT- and MRI-derived measures have not yet been achieved, limiting broad transfer to clinical practice for these novel approaches. KEY POINTS:: · DXA is the reference standard for diagnosis and fracture prediction in osteoporosis, but it has important limitations.. · CT- and MRI-based methods are increasingly used as (opportunistic) approaches.. · For CT, particularly deep-learning-based automatic vertebral segmentation and value extraction seem promising.. · For MRI, multiple techniques including spectroscopy and chemical shift imaging are available to extract fat fractions.. · Texture and finite element analyses can provide additional measures for vertebral body composition and bone strength.. CITATION FORMAT: · Sollmann N, Kirschke JS, Kronthaler S et al. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1770-4626.
Collapse
Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.,Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan Stefan Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christof Boehm
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Daniel Vogele
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | | | - Julio Carballido-Gamio
- Department of Radiology, University of Colorado - Anschutz Medical Campus, Aurora, CO, United States
| | - Thomas Marc Link
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Dimitrios Charalampos Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Subburaj Karupppasamy
- Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore.,Sobey School of Business, Saint Mary's University, Halifax, NS, Canada
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Roland Krug
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| |
Collapse
|
5
|
Kronthaler S, Diefenbach MN, Boehm C, Zamskiy M, Makowski MR, Baum T, Sollmann N, Karampinos DC. On quantification errors of R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction mapping in trabecularized bone marrow in the static dephasing regime. Magn Reson Med 2022; 88:1126-1139. [PMID: 35481686 DOI: 10.1002/mrm.29279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 04/04/2022] [Accepted: 04/05/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE To study the effect of field inhomogeneity distributions in trabecularized bone regions on the gradient echo (GRE) signal with short TEs and to characterize quantification errors on R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction (PDFF) maps when using a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model at short TEs. METHODS Field distortions were simulated based on a trabecular bone micro CT dataset. Simulations were performed for different bone volume fractions (BV/TV) and for different bone-fat composition values. A multi-TE UTE acquisition was developed to acquire multiple UTEs with random order to minimize eddy currents. The acquisition was validated in phantoms and applied in vivo in a volunteer's ankle and knee. Chemical shift encoded MRI (CSE-MRI) based on a Cartesian multi-TE GRE scan was acquired in the spine of patients with metastatic bone disease. RESULTS Simulations showed that signal deviations from the exponential signal decay at short TEs were more prominent for a higher BV/TV. UTE multi-TE measurements reproduced in vivo the simulation-based predicted behavior. In regions with high BV/TV, the presence of field inhomogeneities induced an R 2 * $$ {R}_2^{\ast } $$ underestimation in trabecularized bone marrow when using CSE-MRI at 3T with a short TE. CONCLUSION R 2 * $$ {R}_2^{\ast } $$ can be underestimated when using short TEs (<2 ms at 3 T) and a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model in multi-echo GRE acquisitions of trabecularized bone marrow.
Collapse
Affiliation(s)
- Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian N Diefenbach
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christof Boehm
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Mark Zamskiy
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| |
Collapse
|
6
|
Feuerriegel GC, Kopp FK, Pfeiffer D, Pogorzelski J, Wurm M, Leonhardt Y, Boehm C, Kronthaler S, Karampinos DC, Neumann J, Schwaiger BJ, Makowski MR, Woertler K, Gersing AS. Evaluation of MR-derived simulated CT-like images and simulated radiographs compared to conventional radiography in patients with shoulder pain: a proof-of-concept study. BMC Musculoskelet Disord 2022; 23:122. [PMID: 35123466 PMCID: PMC8818249 DOI: 10.1186/s12891-022-05076-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 01/28/2022] [Indexed: 11/24/2022] Open
Abstract
Background To evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with suspected shoulder pathology. Methods 3 T MRI of the shoulder including a 3D T1-weighted gradient echo sequence was performed in 25 patients (mean age 52.4 ± 18 years, 13 women) with suspected shoulder pathology. Subsequently a cone-beam forward projection algorithm was used to obtain intensity-inverted CT-like images and simulated radiographs. Two radiologists evaluated the simulated images separately and independently using the conventional radiographs as the standard of reference, including measurements of the image quality, acromiohumeral distance, critical shoulder angle, degenerative joint changes and the acromial type. Additionally, the CT-like MR images were evaluated for glenoid defects, subcortical cysts and calcifications. Agreement between the MR-derived simulated radiographs and conventional radiographs was calculated using Cohen’s Kappa. Results Measurements on simulated radiographs and conventional radiographs overall showed a substantial to almost perfect inter- and intra-rater agreement (κ = 0.69–1.00 and κ = 0.65–0.85, respectively). Image quality of the simulated radiographs was rated good to excellent (1.6 ± 0.7 and 1.8 ± 0.6, respectively) by the radiologists. A substantial agreement was found regarding diagnostically relevant features, assessed on Y- and anteroposterior projections (κ = 0.84 and κ = 0.69 for the measurement of the CSA; κ = 0.95 and κ = 0.60 for the measurement of the AHD; κ = 0.77 and κ = 0.77 for grading of the Samilson-Prieto classification; κ = 0.83 and κ = 0.67 for the grading of the Bigliani classification, respectively). Conclusion In this proof-of-concept study, clinically relevant features of the shoulder joint were assessed reliably using MR-derived CT-like images and simulated radiographs with an image quality equivalent to conventional radiographs. MR-derived CT-like images and simulated radiographs may provide useful diagnostic information while reducing the amount of radiation exposure.
Collapse
|
7
|
Gassert FT, Kufner A, Gassert FG, Leonhardt Y, Kronthaler S, Schwaiger BJ, Boehm C, Makowski MR, Kirschke JS, Baum T, Karampinos DC, Gersing AS. MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures. Osteoporos Int 2022; 33:487-496. [PMID: 34537863 PMCID: PMC8813693 DOI: 10.1007/s00198-021-06147-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 09/03/2021] [Indexed: 12/20/2022]
Abstract
UNLABELLED The bone marrow proton density fat fraction (PDFF) assessed with MRI enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures. Therefore, PDFF may be a potentially useful biomarker for bone fragility assessment. INTRODUCTION To evaluate whether magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) of vertebral bone marrow can differentiate between osteoporotic/osteopenic patients with and without vertebral fractures. METHODS Of the 52 study patients, 32 presented with vertebral fractures of the lumbar spine (66.4 ± 14.4 years, 62.5% women; acute low-energy osteoporotic/osteopenic vertebral fractures, N = 25; acute high-energy traumatic vertebral fractures, N = 7). These patients were frequency matched for age and sex to patients without vertebral fractures (N = 20, 69.3 ± 10.1 years, 70.0% women). Trabecular bone mineral density (BMD) values were derived from quantitative computed tomography. Chemical shift encoding-based water-fat MRI of the lumbar spine was performed, and PDFF maps were calculated. Associations between fracture status and PDFF were assessed using multivariable linear regression models. RESULTS Over all patients, mean PDFF and trabecular BMD correlated significantly (r = - 0.51, P < 0.001). In the osteoporotic/osteopenic group, those patients with osteoporotic/osteopenic fractures had a significantly higher PDFF than those without osteoporotic fractures after adjusting for age, sex, weight, height, and trabecular BMD (adjusted mean difference [95% confidence interval], 20.8% [10.4%, 30.7%]; P < 0.001), although trabecular BMD values showed no significant difference between the subgroups (P = 0.63). For the differentiation of patients with and without vertebral fractures in the osteoporotic/osteopenic subgroup using mean PDFF, an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88 (P = 0.006) was assessed. When evaluating all patients with vertebral fractures, those with high-energy traumatic fractures had a significantly lower PDFF than those with low-energy osteoporotic/osteopenic vertebral fractures (P < 0.001). CONCLUSION MR-based PDFF enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures, suggesting the use of PDFF as a potential biomarker for bone fragility.
Collapse
Affiliation(s)
- F T Gassert
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany.
| | - A Kufner
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - F G Gassert
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - Y Leonhardt
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - S Kronthaler
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - B J Schwaiger
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
- Department of Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - C Boehm
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - M R Makowski
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - J S Kirschke
- Department of Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - T Baum
- Department of Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - D C Karampinos
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| | - A S Gersing
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany
| |
Collapse
|
8
|
Kronthaler S, Boehm C, Feuerriegel G, Börnert P, Katscher U, Weiss K, Makowski MR, Schwaiger BJ, Gersing AS, Karampinos DC. Assessment of vertebral fractures and edema of the thoracolumbar spine based on water-fat and susceptibility-weighted images derived from a single ultra-short echo time scan. Magn Reson Med 2021; 87:1771-1783. [PMID: 34752650 DOI: 10.1002/mrm.29078] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/19/2021] [Accepted: 10/22/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a methodology to simultaneously perform single echo Dixon water-fat imaging and susceptibility-weighted imaging (SWI) based on a single echo time (TE) ultra-short echo time (UTE) (sUTE) scan to assess vertebral fractures and degenerative bone changes in the thoracolumbar spine. METHODS A methodology was developed to solve the smoothness-constrained inverse water-fat problem to separate water and fat while removing unwanted low-frequency phase terms. Additionally, the corrected UTE phase was used for SWI. UTE imaging (TE: 0.14 ms, 3T MRI) was performed in the lumbar spine of nine patients with vertebral fractures and bone marrow edema (BME). All images were reviewed by two radiologists. Water- and fat-separated images were analyzed in comparison with short-tau inversion recovery (STIR) and with respect to BME visibility. The visibility of fracture lines and cortical outlining of the UTE magnitude images were analyzed in comparison with computed tomography. RESULTS Unwanted phase components, dominated by the B1 phase, were removed from the UTE phase images. The rating of the diagnostic quality of BME visualization showed a high preference for the sUTE-Dixon water- and fat-separated images in comparison with STIR. The UTE magnitude images enabled better visualizing fracture lines compared with STIR and slightly better visibility of cortical outlining. With increasing SWI weighting osseous structures and fatty tissues were enhanced. CONCLUSION The proposed sUTE-Dixon-SWI methodology allows the removal of unwanted low-frequency phases and enables water-fat separation and SWI processing from a single complex UTE image. The methodology can be used for the simultaneous assessment of vertebral fractures and BME of the thoracolumbar spine.
Collapse
Affiliation(s)
- Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Christof Boehm
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Georg Feuerriegel
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | | | | | | | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| |
Collapse
|
9
|
Leonhardt Y, Gassert FT, Feuerriegel G, Gassert FG, Kronthaler S, Boehm C, Kufner A, Ruschke S, Baum T, Schwaiger BJ, Makowski MR, Karampinos DC, Gersing AS. Vertebral bone marrow T2* mapping using chemical shift encoding-based water-fat separation in the quantitative analysis of lumbar osteoporosis and osteoporotic fractures. Quant Imaging Med Surg 2021; 11:3715-3725. [PMID: 34341744 PMCID: PMC8245952 DOI: 10.21037/qims-20-1373] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 04/07/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Chemical shift encoding-based water-fat separation techniques have been used for fat quantification [proton density fat fraction (PDFF)], but they also enable the assessment of bone marrow T2*, which has previously been reported to be a potential biomarker for osteoporosis and may give insight into the cause of vertebral fractures (i.e., osteoporotic vs. traumatic) and the microstructure of the bone when applied to vertebral bone marrow. METHODS The 32 patients (78.1% with low-energy osteopenic/osteoporotic fractures, mean age 72.3±9.8 years, 76% women; 21.9% with high-energy traumatic fractures, 47.3±12.8 years, no women) were frequency-matched for age and sex to subjects without vertebral fractures (n=20). All study patients underwent 3T-MRI of the lumbar spine including sagittally acquired spoiled gradient echo sequences for chemical shift encoding-based water-fat separation, from which T2* values were obtained. Volumetric trabecular bone mineral density (BMD) and trabecular bone parameters describing the three-dimensional structural integrity of trabecular bone were derived from quantitative CT. Associations between T2* measurements, fracture status and trabecular bone parameters were assessed using multivariable linear regression models. RESULTS Mean T2* values of non fractured vertebrae in all patients showed a significant correlation with BMD (r=-0.65, P<0.001), trabecular number (TbN) (r=-0.56, P<0.001) and trabecular spacing (TbSp) (r=0.61, P<0.001); patients with low-energy osteoporotic vertebral fractures showed significantly higher mean T2* values than those with traumatic fractures (13.6±4.3 vs. 8.4±2.2 ms, P=0.01) as well as a significantly lower TbN (0.69±0.08 vs. 0.93±0.03 mm-1, P<0.01) and a significantly larger trabecular spacing (1.06±0.16 vs. 0.56±0.08 mm, P<0.01). Mean T2* values of osteoporotic patients with and without vertebral fracture showed no significant difference (13.5±3.4 vs. 15.6±3.5 ms, P=0.40). When comparing the mean T2* of the fractured vertebrae, no significant difference could be detected between low-energy osteoporotic fractures and high-energy traumatic fractures (12.6±5.4 vs. 8.1±2.4 ms, P=0.10). CONCLUSIONS T2* mapping of vertebral bone marrow using using chemical shift encoding-based water-fat separation allows for assessing osteoporosis as well as the trabecular microstructure and enables a radiation-free differentiation between patients with low-energy osteoporotic and high-energy traumatic vertebral fractures, suggesting its potential as a biomarker for bone fragility.
Collapse
Affiliation(s)
- Yannik Leonhardt
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Florian T. Gassert
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Georg Feuerriegel
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Felix G. Gassert
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christof Boehm
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexander Kufner
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Stefan Ruschke
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt J. Schwaiger
- Department of Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcus R. Makowski
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C. Karampinos
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexandra S. Gersing
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Neuroradiology, University Hospital of Munich (LMU), Munich, Germany
| |
Collapse
|
10
|
Probst FA, Burian E, Malenova Y, Lyutskanova P, Stumbaum MJ, Ritschl LM, Kronthaler S, Karampinos D, Probst M. Geometric accuracy of magnetic resonance imaging-derived virtual 3-dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study. Clin Implant Dent Relat Res 2021; 23:779-788. [PMID: 34318580 DOI: 10.1111/cid.13033] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 04/29/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Providing accurate 3-dimensional virtual bone surface models is a prerequisite for virtual surgical planning and additive manufacturing in craniomaxillofacial surgery. For this purpose, magnetic resonance imaging (MRI) may be a radiation-free alternative to computed tomography (CT) and cone beam computed tomography (CBCT). PURPOSE The aim of this study was to assess the geometric accuracy of 3-dimensional T1-weighted MRI-derived virtual bone surface models of the mandible in comparison to CT and CBCT. MATERIALS AND METHODS Specimens of the mandible from porcine cadavers were scanned with (1) a 3-dimensional T1-weighted MRI sequence (0.6 mm isotropic voxel) optimized for bone imaging, (2) CT, and (3) CBCT. Cortical mandibular structures (n = 10) were segmented using semiautomated and manual techniques. Imaging-based virtual 3-dimensional models were aligned with a high-resolution optical 3-dimensional surface scan of the dissected bone (=ground truth) and global geometric deviations were calculated (mean surface distance [MSD]/root-mean-square distance [RMSD]). Agreement between the imaging modalities was assessed by equivalence testing and Bland-Altman analysis. RESULTS Intra- and inter-rater agreement was on a high level for all modalities. Global geometric deviations (MSD/RMSD) between optical scans and imaging modalities were 0.225 ± 0.020 mm/0.345 ± 0.074 mm for CT, 0.280 ± 0.067 mm/0.371 ± 0.074 mm for MRI, and 0.352 ± 0.076 mm/0.454 ± 0.071 mm for CBCT. All imaging modalities were statistically equivalent within an equivalence margin of ±0.3 mm, and Bland-Altman analysis indicated high agreement as well. CONCLUSIONS The results of this study indicate that the accuracy and reliability of MRI-derived virtual 3-dimensional bone surface models is equal to CT and CBCT. MRI may be considered as a reliable alternative to CT and CBCT in computer-assisted craniomaxillofacial surgery.
Collapse
Affiliation(s)
- Florian Andreas Probst
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Yoana Malenova
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | - Plamena Lyutskanova
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | | | - Lucas Maximilian Ritschl
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| |
Collapse
|
11
|
Schwaiger BJ, Schneider C, Kronthaler S, Gassert FT, Böhm C, Pfeiffer D, Baum T, Kirschke JS, Karampinos DC, Makowski MR, Woertler K, Wurm M, Gersing AS. CT-like images based on T1 spoiled gradient-echo and ultra-short echo time MRI sequences for the assessment of vertebral fractures and degenerative bone changes of the spine. Eur Radiol 2021; 31:4680-4689. [PMID: 33443599 PMCID: PMC8213670 DOI: 10.1007/s00330-020-07597-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 10/28/2020] [Accepted: 12/03/2020] [Indexed: 12/24/2022]
Abstract
Objectives To evaluate the performance of 3D T1w spoiled gradient-echo (T1SGRE) and ultra-short echo time (UTE) MRI sequences for the detection and assessment of vertebral fractures and degenerative bone changes compared with conventional CT. Methods Fractures (n = 44) and degenerative changes (n = 60 spinal segments) were evaluated in 30 patients (65 ± 14 years, 18 women) on CT and 3-T MRI, including CT-like images derived from T1SGRE and UTE. Two radiologists evaluated morphological features on both modalities: Genant and AO/Magerl classifications, anterior/posterior vertebral height, fracture age; disc height, neuroforaminal diameter, grades of spondylolisthesis, osteophytes, sclerosis, and facet joint degeneration. Diagnostic accuracy and agreement between MRI and CT and between radiologists were assessed using crosstabs, weighted κ, and intraclass correlation coefficients. Image quality was graded on a Likert scale. Results For fracture detection, sensitivity, specificity, and accuracy were 0.95, 0.98, and 0.97 for T1SGRE and 0.91, 0.96, and 0.95 for UTE. Agreement between T1SGRE and CT was substantial to excellent (e.g., Genant: κ, 0.92 [95% confidence interval, 0.83–1.00]; AO/Magerl: κ, 0.90 [0.76–1.00]; osteophytes: κ, 0.91 [0.82–1.00]; sclerosis: κ, 0.68 [0.48–0.88]; spondylolisthesis: ICCs, 0.99 [0.99–1.00]). Agreement between UTE and CT was lower, ranging from moderate (e.g., sclerosis: κ, 0.43 [0.26–0.60]) to excellent (spondylolisthesis: ICC, 0.99 [0.99–1.00]). Inter-reader agreement was substantial to excellent (0.52–1.00), respectively, for all parameters. Median image quality of T1SGRE was rated significantly higher than that of UTE (p < 0.001). Conclusions Morphologic assessment of bone pathologies of the spine using MRI was feasible and comparable to CT, with T1SGRE being more robust than UTE. Key Points • Vertebral fractures and degenerative bone changes can be assessed on CT-like MR images, with 3D T1w spoiled gradient-echo–based images showing a high diagnostic accuracy and agreement with CT. • This could enable MRI to precisely assess bone morphology, and 3D T1SGRE MRI sequences may substitute additional spinal CT examinations in the future. • Image quality and robustness of T1SGRE sequences are higher than those of UTE MRI for the assessment of bone structures.
Collapse
Affiliation(s)
- Benedikt J Schwaiger
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany. .,Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Charlotte Schneider
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Florian T Gassert
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christof Böhm
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Daniela Pfeiffer
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus Woertler
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Markus Wurm
- Department of Trauma Surgery, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| |
Collapse
|
12
|
Kronthaler S, Rahmer J, Börnert P, Makowski MR, Schwaiger BJ, Gersing AS, Karampinos DC. Trajectory correction based on the gradient impulse response function improves high-resolution UTE imaging of the musculoskeletal system. Magn Reson Med 2020; 85:2001-2015. [PMID: 33251655 DOI: 10.1002/mrm.28566] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/30/2020] [Accepted: 10/02/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE UTE sequences typically acquire data during the ramping up of the gradient fields, which makes UTE imaging prone to eddy current and system delay effects. The purpose of this work was to use a simple gradient impulse response function (GIRF) measurement to estimate the real readout gradient waveform and to demonstrate that precise knowledge of the gradient waveform is important in the context of high-resolution UTE musculoskeletal imaging. METHODS The GIRF was measured using the standard hardware of a 3 Tesla scanner and applied on 3D radial UTE data (TE: 0.14 ms). Experiments were performed on a phantom, in vivo on a healthy knee, and in vivo on patients with spine fractures. UTE images were reconstructed twice, first using the GIRF-corrected gradient waveforms and second using nominal-corrected waveforms, correcting for the low-pass filter characteristic of the gradient chain. RESULTS Images reconstructed with the nominal-corrected gradient waveforms exhibited blurring and showed edge artifacts. The blurring and the edge artifacts were reduced when the GIRF-corrected gradient waveforms were used, as shown in single-UTE phantom scans and in vivo dual-UTE gradient-echo scans in the knee. Further, the importance of the GIRF-based correction was indicated in UTE images of the lumbar spine, where thin bone structures disappeared when the nominal correction was employed. CONCLUSION The presented GIRF-based trajectory correction method using standard scanner hardware can improve the quality of high-resolution UTE musculoskeletal imaging.
Collapse
Affiliation(s)
- Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | | | | | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| |
Collapse
|
13
|
Sollmann N, Löffler MT, Kronthaler S, Böhm C, Dieckmeyer M, Ruschke S, Kirschke JS, Carballido-Gamio J, Karampinos DC, Krug R, Baum T. MRI-Based Quantitative Osteoporosis Imaging at the Spine and Femur. J Magn Reson Imaging 2020; 54:12-35. [PMID: 32584496 DOI: 10.1002/jmri.27260] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 05/31/2020] [Accepted: 06/01/2020] [Indexed: 12/27/2022] Open
Abstract
Osteoporosis is a systemic skeletal disease with a high prevalence worldwide, characterized by low bone mass and microarchitectural deterioration, predisposing an individual to fragility fractures. Dual-energy X-ray absorptiometry (DXA) has been the clinical reference standard for diagnosing osteoporosis and for assessing fracture risk for decades. However, other imaging modalities are of increasing importance to investigate the etiology, treatment, and fracture risk. The purpose of this work is to review the available literature on quantitative magnetic resonance imaging (MRI) methods and related findings in osteoporosis at the spine and proximal femur as the clinically most important fracture sites. Trabecular bone microstructure analysis at the proximal femur based on high-resolution MRI allows for a better prediction of osteoporotic fracture risk than DXA-based bone mineral density (BMD) alone. In the 1990s, T2 * mapping was shown to correlate with the density and orientation of the trabecular bone. Recently, quantitative susceptibility mapping (QSM), which overcomes some of the limitations of T2 * mapping, has been applied for trabecular bone quantifications at the spine, whereas ultrashort echo time (UTE) imaging provides valuable surrogate markers of cortical bone quantity and quality. Magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) enable the quantitative assessment of the nonmineralized bone compartment through extraction of the bone marrow fat fraction (BMFF). Furthermore, CSE-MRI allows for the differentiation of osteoporotic vs. pathologic fractures, which is of high clinical relevance. Lastly, advanced postprocessing and image analysis tools, particularly considering statistical parametric mapping and region-specific BMFF distributions, have high potential to further improve MRI-based fracture risk assessments at the spine and hip. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2.
Collapse
Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Maximilian T Löffler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christof Böhm
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Stefan Ruschke
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Julio Carballido-Gamio
- Department of Radiology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Roland Krug
- Department of Radiology and Biomedical Imaging, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| |
Collapse
|
14
|
Gersing AS, Bodden J, Neumann J, Diefenbach MN, Kronthaler S, Pfeiffer D, Knebel C, Baum T, Schwaiger BJ, Hock A, Rummeny EJ, Woertler K, Karampinos DC. Accelerating anatomical 2D turbo spin echo imaging of the ankle using compressed sensing. Eur J Radiol 2019; 118:277-284. [DOI: 10.1016/j.ejrad.2019.06.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/11/2019] [Accepted: 06/10/2019] [Indexed: 11/27/2022]
|