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Chung CB, Pathria MN, Resnick D. MRI in MSK: is it the ultimate examination? Skeletal Radiol 2024; 53:1727-1735. [PMID: 38277028 DOI: 10.1007/s00256-024-04601-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 01/17/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024]
Affiliation(s)
- Christine B Chung
- Department of Radiology, University of California, San Diego, CA, USA.
- Department of Radiology, Veterans Affairs Medical Center, San Diego, CA, USA.
| | - Mini N Pathria
- Department of Radiology, University of California, San Diego, CA, USA
| | - Donald Resnick
- Department of Radiology, University of California, San Diego, CA, USA
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Vosshenrich J, Koerzdoerfer G, Fritz J. Modern acceleration in musculoskeletal MRI: applications, implications, and challenges. Skeletal Radiol 2024; 53:1799-1813. [PMID: 38441617 DOI: 10.1007/s00256-024-04634-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 08/09/2024]
Abstract
Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6 min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.
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Affiliation(s)
- Jan Vosshenrich
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | | | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
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Chaika M, Brendel JM, Ursprung S, Herrmann J, Gassenmaier S, Brendlin A, Werner S, Nickel MD, Nikolaou K, Afat S, Almansour H. Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression. Invest Radiol 2024:00004424-990000000-00235. [PMID: 39043213 DOI: 10.1097/rli.0000000000001110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024]
Abstract
OBJECTIVE Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerated MRI of the upper abdomen in the context of pancreatic pathologies are lacking. In a clinical setting, the purpose of this study is to investigate the performance of a novel DL-based reconstruction algorithm in T1-weighted volumetric interpolated breath-hold examinations with partial Fourier sampling and Dixon fat suppression (hereafter, VIBE-DixonDL). The objective is to analyze its impact on acquisition time, image sharpness and quality, diagnostic confidence, pancreatic lesion conspicuity, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). METHODS This prospective single-center study included participants with various pancreatic pathologies who gave written consent from January 2023 to September 2023. During the same session, each participant underwent 2 MRI acquisitions using a 1.5 T scanner: conventional precontrast and postcontrast T1-weighted VIBE acquisitions with Dixon fat suppression (VIBE-Dixon, reference standard) using 4-fold parallel imaging acceleration and 6-fold accelerated VIBE-Dixon acquisitions with partial Fourier sampling utilizing a novel DL reconstruction tailored to the acquisition. A qualitative image analysis was performed by 4 readers. Acquisition time, image sharpness, overall image quality, image noise and artifacts, diagnostic confidence, as well as pancreatic lesion conspicuity and size were compared. Furthermore, a quantitative analysis of SNR and CNR was performed. RESULTS Thirty-two participants were evaluated (mean age ± SD, 62 ± 19 years; 20 men). The VIBE-DixonDL method enabled up to 52% reduction in average breath-hold time (7 seconds for VIBE-DixonDL vs 15 seconds for VIBE-Dixon, P < 0.001). A significant improvement of image sharpness, overall image quality, diagnostic confidence, and pancreatic lesion conspicuity was observed in the images recorded using VIBE-DixonDL (P < 0.001). Furthermore, a significant reduction of image noise and motion artifacts was noted in the images recorded using the VIBE-DixonDL technique (P < 0.001). In addition, for all readers, there was no evidence of a difference in lesion size measurement between VIBE-Dixon and VIBE-DixonDL. Interreader agreement between VIBE-Dixon and VIBE-DixonDL regarding lesion size was excellent (intraclass correlation coefficient, >90). Finally, a statistically significant increase of pancreatic SNR in VIBE-DIXONDL was observed in both the precontrast (P = 0.025) and postcontrast images (P < 0.001). Also, an increase of splenic SNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.34 and P = 0.003, respectively). Similarly, an increase of pancreas CNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.557 and P = 0.026, respectively). CONCLUSIONS The prospectively accelerated, DL-enhanced VIBE with Dixon fat suppression was clinically feasible. It enabled a 52% reduction in breath-hold time and provided superior image quality, diagnostic confidence, and pancreatic lesion conspicuity. This technique might be especially useful for patients with limited breath-hold capacity.
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Affiliation(s)
- Marianna Chaika
- From the Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tübingen University Hospital, Tübingen, Germany (M.C., J.M.B., S.U., J.H., S.G., A.B., S.W., K.N., S.A., H.A.); MR Application Predevelopment, Siemens Healthineers AG, Forchheim, Germany (M.D.N.); and Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor, Therapies," University of Tübingen, Tübingen, Germany (K.N.)
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Ghotra SS, Cottier Y, Bruguier C, Dominguez A, Monnin P, Sá Dos Reis C. A pilot study to identify suitable MRI protocols for preoperative planning of total hip arthroplasty. Eur J Radiol 2024; 178:111620. [PMID: 39029238 DOI: 10.1016/j.ejrad.2024.111620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 06/15/2024] [Accepted: 07/11/2024] [Indexed: 07/21/2024]
Abstract
PURPOSE The purpose of this study is to identify suitable MRI sequences and evaluate the feasibility and performance of MRI for total hip arthroplasty (THA) preoperative planning. METHOD A multicentric pilot study was conducted to evaluate DP TSE and T1 GRE 3D sequences. High-resolution pelvis, hip, knee and ankle images were acquired. Protocols were optimised to enhance image quality (IQ) and reduce acquisition time to fit clinical practice. The final protocol was validated with 19 healthy volunteers with variable BMIs at 1.5 and 3 Tesla. Visual assessment was performed by five radiographers and radiologists using the ViewDEX software. Visual Grading Analysis (VGA), Intraclass Correlation Coefficient (ICC), Prevalence-adjusted and bias-adjusted kappa (PABAK) and Visual Grading Characteristics (VGC) were performed to analyse data. RESULTS VGA scores indicated that the optimised 3D DP TSE and 3D T1 GRE sequences at 3 T, as well as 3D DP TSE sequence at 1.5 T offer adequate IQ and allow a correct visualisation of the anatomy. Overall ICC analysis was moderate to good reliability at 0.749 (95 % CI 0.69-0.79) and increased from good to excellent at 0.846 (95 % CI 0.72-0.91) for DP at 3 T. PABAK shows fair agreement at 0.25 (95 % CI 0.227-0.273). VGC analysis showed that 3D DP TSE sequences performed statistically better than 3D T1 GRE at 1.5 and 3 T (p-value ≤ 0.05). Furthermore, 3 T sequences showed a statistically better performance compared to 1.5 T (p-value ≤ 0.05). CONCLUSIONS According to the results, 3D DP and T1 MRI sequences can be considered for preoperative planning for THA. Further research is required to emphasize the clinical validation of the results.
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Affiliation(s)
- Switinder Singh Ghotra
- School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne 1011, Switzerland; Department of Radiology, Hospital of Yverdon-les-Bains (eHnv), 1400 Yverdon-les-Bains, Switzerland.
| | - Yann Cottier
- Centre d'Imagerie Diagnostique de Lausanne, Lausanne 1011, Switzerland
| | - Christine Bruguier
- Department of Diagnostic & Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland; University Center of Legal Medicine Lausanne - Geneva, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland.
| | - Alejandro Dominguez
- School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne 1011, Switzerland; University Center of Legal Medicine Lausanne - Geneva, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland.
| | - Pascal Monnin
- School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne 1011, Switzerland.
| | - Cláudia Sá Dos Reis
- School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne 1011, Switzerland.
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5
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Lin DJ, Doshi AM, Fritz J, Recht MP. Designing Clinical MRI for Enhanced Workflow and Value. J Magn Reson Imaging 2024; 60:29-39. [PMID: 37795927 DOI: 10.1002/jmri.29038] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/18/2023] [Accepted: 09/18/2023] [Indexed: 10/06/2023] Open
Abstract
MRI is an expensive and traditionally time-intensive modality in imaging. With the paradigm shift toward value-based healthcare, radiology departments must examine the entire MRI process cycle to identify opportunities to optimize efficiency and enhance value for patients. Digital tools such as "frictionless scheduling" prioritize patient preference and convenience, thereby delivering patient-centered care. Recent advances in conventional and deep learning-based accelerated image reconstruction methods have reduced image acquisition time to such a degree that so-called nongradient time now constitutes a major percentage of total room time. For this reason, architectural design strategies that reconfigure patient preparation processes and decrease the turnaround time between scans can substantially impact overall throughput while also improving patient comfort and privacy. Real-time informatics tools that provide an enterprise-wide overview of MRI workflow and Picture Archiving and Communication System (PACS)-integrated instant messaging can complement these efforts by offering transparent, situational data and facilitating communication between radiology team members. Finally, long-term investment in training, recruiting, and retaining a highly skilled technologist workforce is essential for building a pipeline and team of technologists committed to excellence. Here, we highlight various opportunities for optimizing MRI workflow and enhancing value by offering many of our own on-the-ground experiences and conclude by anticipating some of the future directions for process improvement and innovation in clinical MR imaging. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Dana J Lin
- Department of Radiology, NYU Grossman School of Medicine/NYU Langone Health, New York, New York, USA
| | - Ankur M Doshi
- Department of Radiology, NYU Grossman School of Medicine/NYU Langone Health, New York, New York, USA
| | - Jan Fritz
- Department of Radiology, NYU Grossman School of Medicine/NYU Langone Health, New York, New York, USA
| | - Michael P Recht
- Department of Radiology, NYU Grossman School of Medicine/NYU Langone Health, New York, New York, USA
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Ashikyan O, Xia S, Faridi O, Porembka JH, Chhabra A. Positive Effect of a Financial Incentive on Radiologist Compliance With Quality Metric Placement in Knee Radiography Reports. J Am Coll Radiol 2024; 21:1033-1039. [PMID: 38302038 DOI: 10.1016/j.jacr.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/13/2024] [Accepted: 01/22/2024] [Indexed: 02/03/2024]
Abstract
PURPOSE Ongoing quality improvement (QI) processes in the authors' department include the insertion of a Kellgren-Lawrence (KL) osteoarthritis grading template in knee radiography reports to decrease unnecessary MRI. However, uniform adoption of this grading system is lacking. Department-wide financial incentives were instituted to improve compliance with QI metrics. The purpose of this study was to evaluate the effect of a financial incentive on KL grading system use and to compare compliance rates of musculoskeletal (MSK) radiologists with those of general radiologists who were not financially incentivized to use KL grading. METHODS Percentages of all knee radiography reports containing KL grading with standardized follow-up recommendations were determined by querying the departmental radiology database before and after the introduction of the new quality-based financial incentive. Preincentive compliance rates for MSK and general radiologists were compared with an adoption period and two separate 6-month postincentive periods. RESULTS In total, 52,673 reports were retrospectively analyzed for KL grading use (41,670 reports interpreted by MSK radiologists and 11,003 interpreted by general radiologists). Increase in compliance was greatest among MSK radiologists' reports during the incentivized adoption period (from 36.1% to 53.2%). This improvement was sustained among MSK radiologists and averaged 62.7% during the most recently studied postimplementation period. A lesser degree of improvement in compliance was observed in nonincentivized general radiologists' reports (from 19.3% to 27.5%); during the postimplementation follow-up period, their compliance decreased to 26.5%. CONCLUSIONS The introduction of a financial incentive resulted in significantly increased adoption of QI practices with sustained improvement among incentivized MSK radiologists compared with nonincentivized general radiologists.
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Affiliation(s)
- Oganes Ashikyan
- University of Texas Southwestern Medical Center, Dallas, Texas.
| | - Shuda Xia
- University of Texas Southwestern Medical Center, Dallas, Texas
| | - Osama Faridi
- University of Texas Southwestern Medical Center, Dallas, Texas
| | | | - Avneesh Chhabra
- University of Texas Southwestern Medical Center, Dallas, Texas
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7
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Brendel JM, Jacoby J, Dehdab R, Ursprung S, Fritz V, Werner S, Herrmann J, Brendlin AS, Gassenmaier S, Schick F, Nickel D, Nikolaou K, Afat S, Almansour H. Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI. Acad Radiol 2024:S1076-6332(24)00356-8. [PMID: 38955591 DOI: 10.1016/j.acra.2024.05.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 05/24/2024] [Accepted: 05/26/2024] [Indexed: 07/04/2024]
Abstract
RATIONALE AND OBJECTIVES To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPAIR fat saturation achieving a 50 % reduction in breath-hold duration (hereafter, VIBE-SPAIRDL) in terms of image quality and diagnostic confidence. MATERIALS AND METHODS This prospective study enrolled consecutive patients referred for upper abdominal MRI from November 2023 to December 2023 at a single tertiary center. Patients underwent upper abdominal MRI with acquisition of non-contrast and gadobutrol-enhanced conventional VIBE-SPAIR (fourfold acceleration, acquisition time 16 s) and VIBE-SPAIRDL (sixfold acceleration, acquisition time 8 s) on a 1.5 T scanner. Image analysis was performed by four readers, evaluating homogeneity of fat suppression, perceived signal-to-noise ratio (SNR), edge sharpness, artifact level, lesion detectability and diagnostic confidence. A statistical power analysis for patient sample size estimation was performed. Image quality parameters were compared by a repeated measures analysis of variance, and interreader agreement was assessed using Fleiss' κ. RESULTS Among 450 consecutive patients, 45 patients were evaluated (mean age, 60 years ± 15 [SD]; 27 men, 18 women). VIBE-SPAIRDL acquisition demonstrated superior SNR (P < 0.001), edge sharpness (P < 0.001), and reduced artifacts (P < 0.001) with substantial to almost perfect interreader agreement for non-contrast (κ: 0.70-0.91) and gadobutrol-enhanced MRI (κ: 0.68-0.87). No evidence of a difference was found between conventional VIBE-SPAIR and VIBE-SPAIRDL regarding homogeneity of fat suppression, lesion detectability, or diagnostic confidence (all P > 0.05). CONCLUSION Deep learning reconstruction of VIBE-SPAIR facilitated a reduction of breath-hold duration by half, while reducing artifacts and improving image quality. SUMMARY Deep learning reconstruction of prospectively accelerated T1 volumetric interpolated breath-hold examination for upper abdominal MRI enabled a 50 % reduction in breath-hold time with superior image quality. KEY RESULTS 1) In a prospective analysis of 45 patients referred for upper abdominal MRI, accelerated deep learning (DL)-reconstructed VIBE images with spectral fat saturation (SPAIR) showed better overall image quality, with better perceived signal-to-noise ratio and less artifacts (all P < 0.001), despite a 50 % reduction in acquisition time compared to conventional VIBE. 2) No evidence of a difference was found between conventional VIBE-SPAIR and accelerated VIBE-SPAIRDL regarding lesion detectability or diagnostic confidence.
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Affiliation(s)
- Jan M Brendel
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Johann Jacoby
- Institute of Clinical Epidemiology and Applied Biometry, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Reza Dehdab
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Stephan Ursprung
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Victor Fritz
- Department of Radiology, Section for Experimental Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Sebastian Werner
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Judith Herrmann
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Andreas S Brendlin
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Sebastian Gassenmaier
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Fritz Schick
- Department of Radiology, Section for Experimental Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Dominik Nickel
- Department of MR Application Predevelopment, Siemens Healthineers, Forchheim, Germany
| | - Konstantin Nikolaou
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany
| | - Saif Afat
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany
| | - Haidara Almansour
- Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany.
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Kakigi T, Sakamoto R, Arai R, Yamamoto A, Kuriyama S, Sano Y, Imai R, Numamoto H, Miyake KK, Saga T, Matsuda S, Nakamoto Y. Thin-slice 2D MR Imaging of the Shoulder Joint Using Denoising Deep Learning Reconstruction Provides Higher Image Quality Than 3D MR Imaging. Magn Reson Med Sci 2024:mp.2023-0115. [PMID: 38777762 DOI: 10.2463/mrms.mp.2023-0115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
PURPOSE This study was conducted to evaluate whether thin-slice 2D fat-saturated proton density-weighted images of the shoulder joint in three imaging planes combined with parallel imaging, partial Fourier technique, and denoising approach with deep learning-based reconstruction (dDLR) are more useful than 3D fat-saturated proton density multi-planar voxel images. METHODS Eighteen patients who underwent MRI of the shoulder joint at 3T were enrolled. The denoising effect of dDLR in 2D was evaluated using coefficient of variation (CV). Qualitative evaluation of anatomical structures, noise, and artifacts in 2D after dDLR and 3D was performed by two radiologists using a five-point Likert scale. All were analyzed statistically. Gwet's agreement coefficients were also calculated. RESULTS The CV of 2D after dDLR was significantly lower than that before dDLR (P < 0.05). Both radiologists rated 2D higher than 3D for all anatomical structures and noise (P < 0.05), except for artifacts. Both Gwet's agreement coefficients of anatomical structures, noise, and artifacts in 2D and 3D produced nearly perfect agreement between the two radiologists. The evaluation of 2D tended to be more reproducible than 3D. CONCLUSION 2D with parallel imaging, partial Fourier technique, and dDLR was proved to be superior to 3D for depicting shoulder joint structures with lower noise.
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Affiliation(s)
- Takahide Kakigi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Ryo Sakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Department of Real World Data Research and Development, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Ryuzo Arai
- Department of Orthopaedic Surgery, Kyoto Katsura Hospital, Kyoto, Kyoto, Japan
| | - Akira Yamamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Center for Medical Education, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Shinichi Kuriyama
- Department of Orthopaedic Surgery, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Yuichiro Sano
- MRI Systems Division, Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Rimika Imai
- MRI Systems Division, Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Hitomi Numamoto
- Division of Clinical Radiology Service, Kyoto University Hospital, Kyoto, Kyoto, Japan
- Department of Advanced Medical Imaging Research, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Kanae Kawai Miyake
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Department of Advanced Medical Imaging Research, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Tsuneo Saga
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Department of Advanced Medical Imaging Research, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Shuichi Matsuda
- Department of Orthopaedic Surgery, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
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Marth AA, Feuerriegel GC, Marcus RP, Sutter R. How accurate is MRI for diagnosing tarsal coalitions? A retrospective diagnostic accuracy study. Eur Radiol 2024; 34:3493-3502. [PMID: 37855854 PMCID: PMC11126476 DOI: 10.1007/s00330-023-10304-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/22/2023] [Accepted: 09/04/2023] [Indexed: 10/20/2023]
Abstract
OBJECTIVES This study aimed to evaluate the diagnostic accuracy, inter-reader agreement, and associated pathologies on MR images of patients with confirmed TC. METHODS AND MATERIALS In this retrospective study, 168 ankle MRI exams were included, consisting of 56 patients with clinically or surgically confirmed TC and 112 controls without TC, matched for age and sex. Images were analyzed independently by three radiologists blinded to clinical information. The evaluation criteria included the presence, type, and location of TC, as well as associated pathologies. After calculating diagnostic accuracy and the odds ratio of demographic data and anatomic coalition type for associated pathologies, inter-reader agreement was assessed using kappa statistics. RESULTS The majority of TCs were non-osseous (91.1%) and located at the calcaneonavicular (33.9%) or talocalcaneal joint (66.1%). Associated pathologies included adjacent and distant bone marrow edema (57.1% and 25.0%), osteochondral defect of the talar dome (OCD, 19.6%), and joint effusion (10.7%) and accessory anterolateral talar facet (17.9%). Talar OCD was associated with increased patient age (p = 0.03). MRI exhibited a cumulative sensitivity and specificity of 95.8% and 94.3% with almost perfect inter-reader agreement (κ = 0.895). CONCLUSION MRI is a reliable method for detecting tarsal coalition and identifying commonly associated pathologies. Therefore, we recommend the routine use of MRI in the diagnostic workup of patients with foot pain and suspected tarsal coalition. CLINICAL RELEVANCE STATEMENT MRI is an accurate and reliable modality for diagnosing tarsal coalitions and detecting associated pathologies, while improving patient safety compared to computed tomography by avoiding radiation exposure. KEY POINTS • Despite the technological progress in magnetic resonance imaging (MRI), computed tomography (CT) is still regarded as the gold standard for diagnosing tarsal coalition (TC). • MRI had a cumulative sensitivity of 95.8% and specificity of 94.3% for detecting tarsal coalition with an almost perfect inter-reader agreement. • MRI demonstrates high accuracy and reliability in diagnosing tarsal coalitions and is useful for identifying associated pathologies, while also improving patient safety by avoiding radiation exposure.
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Affiliation(s)
- Adrian A Marth
- Department of Radiology, Balgrist University Hospital, Faculty of Medicine, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
- Swiss Center for Musculoskeletal Imaging, Balgrist Campus AG, Zurich, Switzerland.
| | - Georg C Feuerriegel
- Department of Radiology, Balgrist University Hospital, Faculty of Medicine, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Roy P Marcus
- Department of Radiology, Balgrist University Hospital, Faculty of Medicine, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Reto Sutter
- Department of Radiology, Balgrist University Hospital, Faculty of Medicine, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland
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Chang EY, Bencardino JT, French CN, Fritz J, Hanrahan CJ, Jibri Z, Kassarjian A, Motamedi K, Ringler MD, Strickland CD, Tiegs-Heiden CA, Walker REA. SSR white paper: guidelines for utilization and performance of direct MR arthrography. Skeletal Radiol 2024; 53:209-244. [PMID: 37566148 PMCID: PMC10730654 DOI: 10.1007/s00256-023-04420-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 07/23/2023] [Accepted: 07/29/2023] [Indexed: 08/12/2023]
Abstract
OBJECTIVE Direct magnetic resonance arthrography (dMRA) is often considered the most accurate imaging modality for the evaluation of intra-articular structures, but utilization and performance vary widely without consensus. The purpose of this white paper is to develop consensus recommendations on behalf of the Society of Skeletal Radiology (SSR) based on published literature and expert opinion. MATERIALS AND METHODS The Standards and Guidelines Committee of the SSR identified guidelines for utilization and performance of dMRA as an important topic for study and invited all SSR members with expertise and interest to volunteer for the white paper panel. This panel was tasked with determining an outline, reviewing the relevant literature, preparing a written document summarizing the issues and controversies, and providing recommendations. RESULTS Twelve SSR members with expertise in dMRA formed the ad hoc white paper authorship committee. The published literature on dMRA was reviewed and summarized, focusing on clinical indications, technical considerations, safety, imaging protocols, complications, controversies, and gaps in knowledge. Recommendations for the utilization and performance of dMRA in the shoulder, elbow, wrist, hip, knee, and ankle/foot regions were developed in group consensus. CONCLUSION Although direct MR arthrography has been previously used for a wide variety of clinical indications, the authorship panel recommends more selective application of this minimally invasive procedure. At present, direct MR arthrography remains an important procedure in the armamentarium of the musculoskeletal radiologist and is especially valuable when conventional MRI is indeterminant or results are discrepant with clinical evaluation.
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Affiliation(s)
- Eric Y Chang
- Radiology Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego Medical Center, San Diego, CA, USA
| | - Jenny T Bencardino
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Cristy N French
- Department of Radiology, Penn State Hershey Medical Center, Hummelstown, PA, USA
| | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | | | - Zaid Jibri
- GNMI in Mississauga, Greater Toronto Area, Toronto, ON, Canada
| | - Ara Kassarjian
- Department of Radiology, Division of Musculoskeletal Imaging, Olympia Medical Center, Elite Sports Imaging, Madrid, Spain
| | - Kambiz Motamedi
- Department of Radiology, University of California, Los Angeles Medical Center, Los Angeles, CA, USA
| | | | - Colin D Strickland
- Department of Radiology, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Richard E A Walker
- McCaig Institute for Bone and Joint Health, Calgary, Canada.
- Cumming School of Medicine, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada.
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11
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Wang Q, Zhao W, Xing X, Wang Y, Xin P, Chen Y, Zhu Y, Xu J, Zhao Q, Yuan H, Lang N. Feasibility of AI-assisted compressed sensing protocols in knee MR imaging: a prospective multi-reader study. Eur Radiol 2023; 33:8585-8596. [PMID: 37382615 PMCID: PMC10667384 DOI: 10.1007/s00330-023-09823-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/02/2023] [Accepted: 03/22/2023] [Indexed: 06/30/2023]
Abstract
OBJECTIVES To evaluate the image quality and diagnostic performance of AI-assisted compressed sensing (ACS) accelerated two-dimensional fast spin-echo MRI compared with standard parallel imaging (PI) in clinical 3.0T rapid knee scans. METHODS This prospective study enrolled 130 consecutive participants between March and September 2022. The MRI scan procedure included one 8.0-min PI protocol and two ACS protocols (3.5 min and 2.0 min). Quantitative image quality assessments were performed by evaluating edge rise distance (ERD) and signal-to-noise ratio (SNR). Shapiro-Wilk tests were performed and investigated by the Friedman test and post hoc analyses. Three radiologists independently evaluated structural disorders for each participant. Fleiss κ analysis was used to compare inter-reader and inter-protocol agreements. The diagnostic performance of each protocol was investigated and compared by DeLong's test. The threshold for statistical significance was set at p < 0.05. RESULTS A total of 150 knee MRI examinations constituted the study cohort. For the quantitative assessment of four conventional sequences with ACS protocols, SNR improved significantly (p < 0.001), and ERD was significantly reduced or equivalent to the PI protocol. For the abnormality evaluated, the intraclass correlation coefficient ranged from moderate to substantial between readers (κ = 0.75-0.98) and between protocols (κ = 0.73-0.98). For meniscal tears, cruciate ligament tears, and cartilage defects, the diagnostic performance of ACS protocols was considered equivalent to PI protocol (Delong test, p > 0.05). CONCLUSIONS Compared with the conventional PI acquisition, the novel ACS protocol demonstrated superior image quality and was feasible for achieving equivalent detection of structural abnormalities while reducing acquisition time by half. CLINICAL RELEVANCE STATEMENT Artificial intelligence-assisted compressed sensing (ACS) providing excellent quality and a 75% reduction in scanning time presents significant clinical advantages in improving the efficiency and accessibility of knee MRI for more patients. KEY POINTS • The prospective multi-reader study showed no difference in diagnostic performance between parallel imaging and AI-assisted compression sensing (ACS) was found. • Reduced scan time, sharper delineation, and less noise with ACS reconstruction. • Improved efficiency of the clinical knee MRI examination by the ACS acceleration.
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Affiliation(s)
- Qizheng Wang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Weili Zhao
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Xiaoying Xing
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Ying Wang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Peijin Xin
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Yongye Chen
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Yupeng Zhu
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Jiajia Xu
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Qiang Zhao
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Ning Lang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China.
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12
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Manson EN, Inkoom S, Mumuni AN, Shirazu I, Awua AK. Assessment of the Impact of Turbo Factor on Image Quality and Tissue Volumetrics in Brain Magnetic Resonance Imaging Using the Three-Dimensional T1-Weighted (3D T1W) Sequence. Int J Biomed Imaging 2023; 2023:6304219. [PMID: 38025965 PMCID: PMC10665095 DOI: 10.1155/2023/6304219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/13/2023] [Accepted: 11/01/2023] [Indexed: 12/01/2023] Open
Abstract
Background The 3D T1W turbo field echo sequence is a standard imaging method for acquiring high-contrast images of the brain. However, the contrast-to-noise ratio (CNR) can be affected by the turbo factor, which could affect the delineation and segmentation of various structures in the brain and may consequently lead to misdiagnosis. This study is aimed at evaluating the effect of the turbo factor on image quality and volumetric measurement reproducibility in brain magnetic resonance imaging (MRI). Methods Brain images of five healthy volunteers with no history of neurological diseases were acquired on a 1.5 T MRI scanner with varying turbo factors of 50, 100, 150, 200, and 225. The images were processed and analyzed with FreeSurfer. The influence of the TFE factor on image quality and reproducibility of brain volume measurements was investigated. Image quality metrics assessed included the signal-to-noise ratio (SNR) of white matter (WM), CNR between gray matter/white matter (GM/WM) and gray matter/cerebrospinal fluid (GM/CSF), and Euler number (EN). Moreover, structural brain volume measurements of WM, GM, and CSF were conducted. Results Turbo factor 200 produced the best SNR (median = 17.01) and GM/WM CNR (median = 2.29), but turbo factor 100 offered the most reproducible SNR (IQR = 2.72) and GM/WM CNR (IQR = 0.14). Turbo factor 50 had the worst and the least reproducible SNR, whereas turbo factor 225 had the worst and the least reproducible GM/WM CNR. Turbo factor 200 again had the best GM/CSF CNR but offered the least reproducible GM/CSF CNR. Turbo factor 225 had the best performance on EN (-21), while turbo factor 200 was next to the most reproducible turbo factor on EN (11). The results showed that turbo factor 200 had the least data acquisition time, in addition to superior performance on SNR, GM/WM CNR, GM/CSF CNR, and good reproducibility characteristics on EN. Both image quality metrics and volumetric measurements did not vary significantly (p > 0.05) with the range of turbo factors used in the study by one-way ANOVA analysis. Conclusion Since no significant differences were observed in the performance of the turbo factors in terms of image quality and volume of brain structure, turbo factor 200 with a 74% acquisition time reduction was found to be optimal for brain MR imaging at 1.5 T.
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Affiliation(s)
- Eric Naab Manson
- Department of Medical Imaging, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
- Department of Medical Physics, School of Nuclear and Allied Sciences, University of Ghana, Accra, Ghana
| | - Stephen Inkoom
- Radiation Protection Institute (RPI), Ghana Atomic Energy Commission, Accra, Ghana
| | - Abdul Nashirudeen Mumuni
- Department of Medical Imaging, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
| | - Issahaku Shirazu
- Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Accra, Ghana
| | - Adolf Kofi Awua
- Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Accra, Ghana
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Khodarahmi I, Khanuja HS, Stern SE, Carrino JA, Fritz J. Compressed Sensing SEMAC MRI of Hip, Knee, and Ankle Arthroplasty Implants: A 1.5-T and 3-T Intrapatient Performance Comparison for Diagnosing Periprosthetic Abnormalities. AJR Am J Roentgenol 2023; 221:661-672. [PMID: 37255041 DOI: 10.2214/ajr.23.29380] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
BACKGROUND. The utility of 3-T MRI for diagnosing joint disorders is established, but its performance for diagnosing abnormalities around arthroplasty implants is unclear. OBJECTIVE. The purpose of this study was to compare 1.5-T and 3-T compressed sensing slice encoding for metal artifact correction (SEMAC) MRI for diagnosing peri-prosthetic abnormalities around hip, knee, and ankle arthroplasty implants. METHODS. Forty-five participants (26 women, 19 men; mean age ± SD, 71 ± 14 years) with symptomatic lower extremity arthroplasty (hip, knee, and ankle, 15 each) prospectively underwent consecutive 1.5- and 3-T MRI examinations with intermediate-weighted (IW) and STIR compressed sensing SEMAC sequences. Using a Likert scale, three radiologists evaluated the presence or absence of periprosthetic abnormalities, including bone marrow edema-like signal, osteolysis, stress reaction/fracture, synovitis, and tendon abnormalities and collections; image quality; and visibility of anatomic structures. Statistical analysis included nonparametric comparison and interchangeability testing. RESULTS. For diagnosing periprosthetic abnormalities, 1.5-T and 3-T compressed sensing SEMAC MRI were interchangeable. Across all three joints, 3-T MRI had lower noise than 1.5-T MRI (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [range, 2-5 and 3-5] vs 3 and 3 [range, 2-5 and 2-4]; p < .01 for both), sharper edges (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [both ranges, 2-5] vs 3 and 3 [range, 2-4 and 2-5]; p < .02 and p < .05), and more effective metal artifact reduction (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [range, 3-5 and 2-5] vs 4 and 4 [both ranges, 3-5]; p < .02 and p = .72). Agreement was moderate to substantial for image contrast (IW and STIR, 0.66 and 0.54 [95% CI, 0.41-0.91 and 0.29-0.80]; p = .58 and p = .16) and joint capsule visualization (IW and STIR, 0.57 and 0.70 [range, 0.32-0.81 and 0.51-0.89]; p = .16 and p = .19). The bone-implant interface was more visible at 1.5 T (median IW and STIR scores, 4 and 4 [both ranges, 2-5] at 1.5 T vs 3 and 3 [both ranges, 2-5] at 3 T; p = .08 and p = .58), but periprosthetic tissues had superior visibility at 3 T (IW and STIR, 4 and 4 [both ranges, 3-5] at 3 T vs 4 and 4 [ranges, 2-5 and 3-5] at 1.5 T; p = .07 and p = .19). CONCLUSION. Optimized 1.5-T and 3-T compressed sensing SEMAC MRI are interchangeable for diagnosing periprosthetic abnormalities, although metallic artifacts are larger at 3 T. CLINICAL IMPACT. With compressed sensing SEMAC MRI, lower extremity arthroplasty implants can be imaged at 3 T rather than 1.5 T.
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Affiliation(s)
- Iman Khodarahmi
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016
| | - Harpal S Khanuja
- Department of Orthopaedic Surgery, Johns Hopkins School of Medicine, Baltimore, MD
| | - Steven E Stern
- Centre for Data Analytics, Bond University, Gold Coast, Australia
| | - John A Carrino
- Department of Radiology, Hospital for Special Surgery, New York, NY
| | - Jan Fritz
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016
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14
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Herrmann J, Afat S, Gassenmaier S, Koerzdoerfer G, Lingg A, Almansour H, Nickel D, Werner S. Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network. Diagnostics (Basel) 2023; 13:3241. [PMID: 37892062 PMCID: PMC10606422 DOI: 10.3390/diagnostics13203241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/10/2023] [Accepted: 10/14/2023] [Indexed: 10/29/2023] Open
Abstract
OBJECTIVES Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D TSE sequences with deep learning (DL) reconstruction (TSEDL) for routine clinical hip MRI at 1.5 and 3 T in terms of feasibility, image quality, and diagnostic performance. MATERIAL AND METHODS In this prospective, monocentric study, TSEDL was implemented clinically and evaluated in 14 prospectively enrolled patients undergoing a clinically indicated hip MRI at 1.5 and 3T between October 2020 and May 2021. Each patient underwent two examinations: For the first exam, we used standard sequences with generalized autocalibrating partial parallel acquisition reconstruction (TSES). For the second exam, we implemented prospectively undersampled TSE sequences with DL reconstruction (TSEDL). Two radiologists assessed the TSEDL and TSES regarding image quality, artifacts, noise, edge sharpness, diagnostic confidence, and delineation of anatomical structures using an ordinal five-point Likert scale (1 = non-diagnostic; 2 = poor; 3 = moderate; 4 = good; 5 = excellent). Both sequences were compared regarding the detection of common pathologies of the hip. Comparative analyses were conducted to assess the differences between TSEDL and TSES. RESULTS Compared with TSES, TSEDL was rated to be significantly superior in terms of image quality (p ≤ 0.020) with significantly reduced noise (p ≤ 0.001) and significantly improved edge sharpness (p = 0.003). No difference was found between TSES and TSEDL concerning the extent of artifacts, diagnostic confidence, or the delineation of anatomical structures (p > 0.05). Example acquisition time reductions for the TSE sequences of 52% at 3 Tesla and 70% at 1.5 Tesla were achieved. CONCLUSION TSEDL of the hip is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared with TSES, reducing the acquisition time significantly.
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Affiliation(s)
- Judith Herrmann
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Gregor Koerzdoerfer
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Andreas Lingg
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Haidara Almansour
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Dominik Nickel
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Sebastian Werner
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
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15
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Dalili D, Isaac A, Fritz J. Selective MR neurography-guided lumbosacral plexus perineural injections: techniques, targets, and territories. Skeletal Radiol 2023; 52:1929-1947. [PMID: 37495713 DOI: 10.1007/s00256-023-04384-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 07/28/2023]
Abstract
The T12 to S4 spinal nerves form the lumbosacral plexus in the retroperitoneum, providing sensory and motor innervation to the pelvis and lower extremities. The lumbosacral plexus has a wide range of anatomic variations and interchange of fibers between nerve anastomoses. Neuropathies of the lumbosacral plexus cause a broad spectrum of complex pelvic and lower extremity pain syndromes, which can be challenging to diagnose and treat successfully. In their workup, selective nerve blocks are employed to test the hypothesis that a lumbosacral plexus nerve contributes to a suspected pelvic and extremity pain syndrome, whereas therapeutic perineural injections aim to alleviate pain and paresthesia symptoms. While the sciatic and femoral nerves are large in caliber, the iliohypogastric and ilioinguinal, genitofemoral, lateral femoral cutaneous, anterior femoral cutaneous, posterior femoral cutaneous, obturator, and pudendal nerves are small, measuring a few millimeters in diameter and have a wide range of anatomic variants. Due to their minuteness, direct visualization of the smaller lumbosacral plexus branches can be difficult during selective nerve blocks, particularly in deeper pelvic locations or larger patients. In this setting, the high spatial and contrast resolution of interventional MR neurography guidance benefits nerve visualization and targeting, needle placement, and visualization of perineural injectant distribution, providing a highly accurate alternative to more commonly used ultrasonography, fluoroscopy, and computed tomography guidance for perineural injections. This article offers a practical guide for MR neurography-guided lumbosacral plexus perineural injections, including interventional setup, pulse sequence protocols, lumbosacral plexus MR neurography anatomy, anatomic variations, and injection targets.
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Affiliation(s)
- Danoob Dalili
- Academic Surgical Unit, Southwest London Elective Orthopaedic Centre (SWLEOC), Dorking Road, Epsom, KT18 7EG, London, UK
- Department of Radiology, Epsom and St Hellier University Hospitals NHS Trust, Dorking Road, Epsom, London, KT18 7EG, UK
| | - Amanda Isaac
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine, NY, USA.
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16
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Fritz B, de Cesar Netto C, Fritz J. Multiaxial 3D MRI of the Ankle: Advanced High-Resolution Visualization of Ligaments, Tendons, and Articular Cartilage. Foot Ankle Clin 2023; 28:529-550. [PMID: 37536817 DOI: 10.1016/j.fcl.2023.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
MRI is a valuable tool for diagnosing a broad spectrum of acute and chronic ankle disorders, including ligament tears, tendinopathy, and osteochondral lesions. Traditional two-dimensional (2D) MRI provides a high image signal and contrast of anatomic structures for accurately characterizing articular cartilage, bone marrow, synovium, ligaments, tendons, and nerves. However, 2D MRI limitations are thick slices and fixed slice orientations. In clinical practice, 2D MRI is limited to 2 to 3 mm slice thickness, which can cause blurred contours of oblique structures due to volume averaging effects within the image slice. In addition, image plane orientations are fixated and cannot be changed after the scan, resulting in 2D MRI lacking multiplanar and multiaxial reformation abilities for individualized image plane orientations along oblique and curved anatomic structures, such as ankle ligaments and tendons. In contrast, three-dimensional (3D) MRI is a newer, clinically available MRI technique capable of acquiring high-resolution ankle MRI data sets with isotropic voxel size. The inherently high spatial resolution of 3D MRI permits up to five times thinner (0.5 mm) image slices. In addition, 3D MRI can be acquired image voxel with the same edge length in all three space dimensions (isotropism), permitting unrestricted multiplanar and multiaxial image reformation and postprocessing after the MRI scan. Clinical 3D MRI of the ankle with 0.5 to 0.7 mm isotropic voxel size resolves the smallest anatomic ankle structures and abnormalities of ligament and tendon fibers, osteochondral lesions, and nerves. After acquiring the images, operators can align image planes individually along any anatomic structure of interest, such as ligaments and tendons segments. In addition, curved multiplanar image reformations can unfold the entire course of multiaxially curved structures, such as perimalleolar tendons, into one image plane. We recommend adding 3D MRI pulse sequences to traditional 2D MRI protocols to visualize small and curved ankle structures to better advantage. This article provides an overview of the clinical application of 3D MRI of the ankle, compares diagnostic performances of 2D and 3D MRI for diagnosing ankle abnormalities, and illustrates clinical 3D ankle MRI applications.
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Affiliation(s)
- Benjamin Fritz
- Department of Radiology, Balgrist University Hospital, Forchstrasse 340, Zurich 8008, Switzerland; Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Cesar de Cesar Netto
- Department of Orthopaedics and Rehabilitation, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA
| | - Jan Fritz
- Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, 660 1st Avenue, New York, NY 10016, USA.
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17
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Park EH, Fritz J. The role of imaging in osteoarthritis. Best Pract Res Clin Rheumatol 2023; 37:101866. [PMID: 37659890 DOI: 10.1016/j.berh.2023.101866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/08/2023] [Accepted: 08/13/2023] [Indexed: 09/04/2023]
Abstract
Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and physiologic derangement. Advances in imaging techniques have expanded the role of imaging in evaluating osteoarthritis and functional changes. Radiography, magnetic resonance imaging, computed tomography (CT), and ultrasonography are commonly used imaging modalities, each with advantages and limitations in evaluating osteoarthritis. Radiography comprehensively analyses alignment and osseous features, while MRI provides detailed information about cartilage damage, bone marrow edema, synovitis, and soft tissue abnormalities. Compositional imaging derives quantitative data for detecting cartilage and tendon degeneration before structural damage occurs. Ultrasonography permits real-time scanning and dynamic joint evaluation, whereas CT is useful for assessing final osseous detail. Imaging plays an essential role in the diagnosis, management, and research of osteoarthritis. The use of imaging can help differentiate osteoarthritis from other diseases with similar symptoms, and recent advances in deep learning have made the acquisition, management, and interpretation of imaging data more efficient and accurate. Imaging is useful in monitoring and predicting the prognosis of osteoarthritis, expanding our understanding of its pathophysiology. Ultimately, this enables early detection and personalized medicine for patients with osteoarthritis. This article reviews the current state of imaging in osteoarthritis, focusing on the strengths and limitations of various imaging modalities, and introduces advanced techniques, including deep learning, applied in clinical practice.
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Affiliation(s)
- Eun Hae Park
- Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, New York, USA; Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Jan Fritz
- Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, New York, USA.
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18
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Park EH, de Cesar Netto C, Fritz J. MRI in Acute Ankle Sprains: Should We Be More Aggressive with Indications? Foot Ankle Clin 2023; 28:231-264. [PMID: 37137621 DOI: 10.1016/j.fcl.2023.01.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Acute ankle sprains are common sports injuries. MRI is the most accurate test for assessing the integrity and severity of ligament injuries in acute ankle sprains. However, MRI may not detect syndesmotic and hindfoot instability, and many ankle sprains are treated conservatively, questioning the value of MRI. In our practice, MRI adds value in confirming the absence or presence of ankle sprain-associated hindfoot and midfoot injuries, especially when clinical examinations are challenging, radiographs are inconclusive, and subtle instability is suspected. This article reviews and illustrates the MRI appearances of the spectrum of ankle sprains and associated hindfoot and midfoot injuries.
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Affiliation(s)
- Eun Hae Park
- Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, 660 1St Ave, 3rd Floor, New York, NY 10016, USA; Department of Radiology, Jeonbuk National University Medical School, Jeonju, Republic of Korea
| | - Cesar de Cesar Netto
- Department of Orthopaedics and Rehabilitation, University of Iowa, 200 Hawkins Dr, Iowa City, IA 52242, USA
| | - Jan Fritz
- Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, 660 1St Ave, 3rd Floor, New York, NY 10016, USA.
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19
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Preisner F, Hayes JC, Charlet T, Carinci F, Hielscher T, Schwarz D, Vollherbst DF, Breckwoldt MO, Jesser J, Heiland S, Bendszus M, Hilgenfeld T. Simultaneous Multislice Accelerated TSE for Improved Spatiotemporal Resolution and Diagnostic Accuracy in Magnetic Resonance Neurography: A Feasibility Study. Invest Radiol 2023; 58:363-371. [PMID: 36729753 DOI: 10.1097/rli.0000000000000940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVES This study aims to evaluate the utility of simultaneous multislice (SMS) acceleration for routine magnetic resonance neurography (MRN) at 3 T. MATERIALS AND METHODS Patients with multiple sclerosis underwent MRN of the sciatic nerve consisting of a standard fat-saturated T2-weighted turbo spin echo (TSE) sequence using integrated parallel acquisition technique (PAT2) acceleration and 2 T2 TSE sequences using a combination of PAT-SMS acceleration (1) to reduce scan time (PAT2-SMS2; SMS-TSE FAST ) and (2) for time neutral increase of in-plane resolution (PAT1-SMS2; SMS-TSE HR ). Acquisition times were 5:29 minutes for the standard T2 TSE, 3:12 minutes for the SMS-TSE FAST , and 5:24 minutes for the SMS-TSE HR . Six qualitative imaging parameters were analyzed by 2 blinded readers using a 5-point Likert scale and T2 nerve lesions were quantified, respectively. Qualitative and quantitative image parameters were compared, and both interrater and intrarater reproducibility were statistically assessed. In addition, signal-to-noise ratio/contrast-to-noise ratio (CNR) was obtained in healthy controls using the exact same imaging protocol. RESULTS A total of 15 patients with MS (mean age ± standard deviation, 38.1 ± 11 years) and 10 healthy controls (mean age, 29.1 ± 7 years) were enrolled in this study. CNR analysis was highly reliable (intraclass correlation coefficient, 0.755-0.948) and revealed a significant CNR decrease for the sciatic nerve for both SMS protocols compared with standard T2 TSE (SMS-TSE FAST /SMS-TSE HR , -39%/-55%; P ≤ 0.01). Intrarater and interrater reliability of qualitative image review was good to excellent (κ: 0.672-0.971/0.617-0.883). Compared with the standard T2 TSE sequence, both SMS methods were shown to be superior in reducing pulsatile flow artifacts ( P < 0.01). Ratings for muscle border sharpness, detailed muscle structures, nerve border sharpness, and nerve fascicular structure did not differ significantly between the standard T2 TSE and the SMS-TSE FAST ( P > 0.05) and were significantly better for the SMS-TSE HR than for standard T2 TSE ( P < 0.001). Muscle signal homogeneity was mildly inferior for both SMS-TSE FAST ( P > 0.05) and SMS-TSE HR ( P < 0.001). A significantly higher number of T2 nerve lesions were detected by SMS-TSE HR ( P ≤ 0.01) compared with the standard T2 TSE and SMS-TSE FAST , whereas no significant difference was observed between the standard T2 TSE and SMS-TSE FAST . CONCLUSIONS Implementation of SMS offers either to substantially reduce acquisition time by over 40% without significantly impeding image quality compared with the standard T2 TSE or to increase in-plane resolution for a high-resolution approach and improved depiction of T2 nerve lesions while keeping acquisition times constant. This addresses the specific needs of MRN by providing different imaging approaches for 2D clinical MRN.
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Affiliation(s)
- Fabian Preisner
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Jennifer C Hayes
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Tobias Charlet
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | | | - Thomas Hielscher
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Schwarz
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Dominik F Vollherbst
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Michael O Breckwoldt
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Jessica Jesser
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Sabine Heiland
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Martin Bendszus
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
| | - Tim Hilgenfeld
- From the Department of Neuroradiology, Heidelberg University Hospital, Heidelberg
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20
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Dalili D, Isaac A, Fritz J. MRI-guided sacroiliac joint injections in children and adults: current practice and future developments. Skeletal Radiol 2023; 52:951-965. [PMID: 36006462 DOI: 10.1007/s00256-022-04161-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 02/02/2023]
Abstract
Common etiologies of low back pain include degenerative arthrosis and inflammatory arthropathy of the sacroiliac joints. The diagnostic workup revolves around identifying and confirming the sacroiliac joints as a pain generator. Diagnostic sacroiliac joint injections often serve as functional additions to the diagnostic workup through eliciting a pain response that tests the hypothesis that the sacroiliac joints do or do not contribute to the patient's pain syndrome. Therapeutic sacroiliac joint injections aim to provide medium- to long-term relief of symptoms and reduce inflammatory activity and, ultimately, irreversible structural damage. Ultrasonography, fluoroscopy, computed tomography, and magnetic resonance imaging (MRI) may be used to guide sacroiliac joint injections. The populations that may benefit most from MRI-guided sacroiliac joint procedures include children, adolescents, adults of childbearing age, and patients receiving serial injections due to the ability of interventional MRI to avoid radiation exposure. Most clinical wide-bore MRI systems can be used for MRI-guided sacroiliac joint injections. Turbo spin echo pulse sequences optimized for interventional needle display visualize the needle tip with an error margin of < 1 mm or less. Published success rates of intra-articular sacroiliac joint drug delivery with MRI guidance range between 87 and 100%. The time required for MR-guided sacroiliac joint injections in adults range between 23-35 min and 40 min in children. In this article, we describe techniques for MRI-guided sacroiliac joint injections, share our practice of incorporating interventional MRI in the care of patients with sacroiliac joint mediated pain, discuss the rationales, benefits, and limitations of interventional MRI, and conclude with future developments.
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Affiliation(s)
- Danoob Dalili
- Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), Dorking Road, KT18 7EG, London, UK
| | - Amanda Isaac
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Diagnostic and Interventional Radiology, Guy's and St Thomas' Hospitals NHS Foundation Trust, London, UK
| | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine, 660 1st Ave, 3rd Floor, Rm 313, New York, NY, 10016, USA.
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21
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Murthy S, Fritz J. Metal Artifact Reduction MRI in the Diagnosis of Periprosthetic Hip Joint Infection. Radiology 2023; 306:e220134. [PMID: 36318029 DOI: 10.1148/radiol.220134] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
A 54-year-old woman presented with progressive right hip pain after hip arthroplasty 9 years earlier. The emerging role of metal artifact reduction MRI in the noninvasive diagnosis of infectious synovitis as the surrogate marker for periprosthetic hip joint infection and differentiation from other synovitis types is discussed.
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Affiliation(s)
- Sindhoora Murthy
- From the Department of Radiology, New York University Grossman School of Medicine, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016
| | - Jan Fritz
- From the Department of Radiology, New York University Grossman School of Medicine, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016
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22
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Almansour H, Herrmann J, Gassenmaier S, Afat S, Jacoby J, Koerzdoerfer G, Nickel D, Mostapha M, Nadar M, Othman AE. Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability. Radiology 2023; 306:e212922. [PMID: 36318032 DOI: 10.1148/radiol.212922] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To investigate the diagnostic interchangeability of an unrolled DL-reconstructed TSE (hereafter, TSEDL) T1- and T2-weighted acquisition method with standard TSE and to test their impact on acquisition time, image quality, and diagnostic confidence. Materials and Methods This prospective single-center study included participants with various spinal abnormalities who gave written consent from November 2020 to July 2021. Each participant underwent two MRI examinations: standard fully sampled T1- and T2-weighted TSE acquisitions (reference standard) and prospectively undersampled TSEDL acquisitions with threefold and fourfold acceleration. Image evaluation was performed by five readers. Interchangeability analysis and an image quality-based analysis were used to compare the TSE and TSEDL images. Acquisition time and diagnostic confidence were also compared. Interchangeability was tested using the individual equivalence index regarding various degenerative and nondegenerative entities, which were analyzed on each vertebra and defined as discordant clinical judgments of less than 5%. Interreader and intrareader agreement and concordance (κ and Kendall τ and W statistics) were computed and Wilcoxon and McNemar tests were used. Results Overall, 50 participants were evaluated (mean age, 46 years ± 18 [SD]; 26 men). The TSEDL method enabled up to a 70% reduction in total acquisition time (100 seconds for TSEDL vs 328 seconds for TSE, P < .001). All individual equivalence indexes were less than 4%. TSEDL acquisition was rated as having superior image noise by all readers (P < .001). No evidence of a difference was found between standard TSE and TSEDL regarding frequency of major findings, overall image quality, or diagnostic confidence. Conclusion The deep learning (DL)-reconstructed turbo spin-echo (TSE) method was found to be interchangeable with standard TSE for detecting various abnormalities of the spine at MRI. DL-reconstructed TSE acquisition provided excellent image quality, with a 70% reduction in examination time. German Clinical Trials Register no. DRKS00023278 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hallinan in this issue.
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Affiliation(s)
- Haidara Almansour
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Judith Herrmann
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Sebastian Gassenmaier
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Saif Afat
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Johann Jacoby
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Gregor Koerzdoerfer
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Dominik Nickel
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Mahmoud Mostapha
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Mariappan Nadar
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
| | - Ahmed E Othman
- From the Department of Diagnostic and Interventional Radiology (H.A., J.H., S.G., S.A., A.E.O.) and Institute of Clinical Epidemiology and Applied Biometry (J.J.), Eberhard Karls University, Tuebingen University Hospital, Hoppe-Seyler-Str 3, 72076, Tuebingen, Germany; Department of MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany (G.K., D.N.); Department of Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ (M.M., M.N.); and Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany (A.E.O.)
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Abstract
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.
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24
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Tolpadi AA, Bharadwaj U, Gao KT, Bhattacharjee R, Gassert FG, Luitjens J, Giesler P, Morshuis JN, Fischer P, Hein M, Baumgartner CF, Razumov A, Dylov D, van Lohuizen Q, Fransen SJ, Zhang X, Tibrewala R, de Moura HL, Liu K, Zibetti MVW, Regatte R, Majumdar S, Pedoia V. K2S Challenge: From Undersampled K-Space to Automatic Segmentation. Bioengineering (Basel) 2023; 10:bioengineering10020267. [PMID: 36829761 PMCID: PMC9952400 DOI: 10.3390/bioengineering10020267] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/01/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
Magnetic Resonance Imaging (MRI) offers strong soft tissue contrast but suffers from long acquisition times and requires tedious annotation from radiologists. Traditionally, these challenges have been addressed separately with reconstruction and image analysis algorithms. To see if performance could be improved by treating both as end-to-end, we hosted the K2S challenge, in which challenge participants segmented knee bones and cartilage from 8× undersampled k-space. We curated the 300-patient K2S dataset of multicoil raw k-space and radiologist quality-checked segmentations. 87 teams registered for the challenge and there were 12 submissions, varying in methodologies from serial reconstruction and segmentation to end-to-end networks to another that eschewed a reconstruction algorithm altogether. Four teams produced strong submissions, with the winner having a weighted Dice Similarity Coefficient of 0.910 ± 0.021 across knee bones and cartilage. Interestingly, there was no correlation between reconstruction and segmentation metrics. Further analysis showed the top four submissions were suitable for downstream biomarker analysis, largely preserving cartilage thicknesses and key bone shape features with respect to ground truth. K2S thus showed the value in considering reconstruction and image analysis as end-to-end tasks, as this leaves room for optimization while more realistically reflecting the long-term use case of tools being developed by the MR community.
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Affiliation(s)
- Aniket A. Tolpadi
- Department of Bioengineering, University of California, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Correspondence:
| | - Upasana Bharadwaj
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kenneth T. Gao
- Department of Bioengineering, University of California, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Rupsa Bhattacharjee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Felix G. Gassert
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Johanna Luitjens
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology, Klinikum Großhadern, Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Paula Giesler
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jan Nikolas Morshuis
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | - Paul Fischer
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | - Matthias Hein
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | | | - Artem Razumov
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Dmitry Dylov
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Quintin van Lohuizen
- Department of Radiology, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | - Stefan J. Fransen
- Department of Radiology, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | - Xiaoxia Zhang
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Radhika Tibrewala
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Hector Lise de Moura
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Kangning Liu
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Marcelo V. W. Zibetti
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ravinder Regatte
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
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25
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Lang M, Cartmell S, Tabari A, Briggs D, Pianykh O, Kirsch J, Cauley S, Lo WC, Risacher S, Filho AG, Succi MD, Rapalino O, Schaefer P, Conklin J, Huang SY. Evaluation of the Aggregated Time Savings in Adopting Fast Brain MRI Techniques for Outpatient Brain MRI. Acad Radiol 2023; 30:341-348. [PMID: 34635436 PMCID: PMC8989721 DOI: 10.1016/j.acra.2021.07.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 06/29/2021] [Accepted: 07/02/2021] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Clinical validation studies have demonstrated the ability of accelerated MRI sequences to decrease acquisition time and motion artifact while preserving image quality. The operational benefits, however, have been less explored. Here, we report our initial clinical experience in implementing fast MRI techniques for outpatient brain imaging during the COVID-19 pandemic. METHODS Aggregate acquisition times were extracted from the medical record on consecutive imaging examinations performed during matched pre-implementation (7/1/2019-12/31/2019) and post-implementation periods (7/1/2020-12/31/2020). Expected acquisition time reduction for each MRI protocol was calculated through manual collection of acquisition times for the conventional and accelerated sequences performed during the pre- and post-implementation periods. Aggregate and expected acquisition times were compared for the five most frequently performed brain MRI protocols: brain without contrast (BR-), brain with and without contrast (BR+), multiple sclerosis (MS), memory loss (MML), and epilepsy (EPL). RESULTS The expected time reductions for BR-, BR+, MS, MML, and EPL protocols were 6.6 min, 11.9 min, 14 min, 10.8 min, and 14.1 min, respectively. The overall median aggregate acquisition time was 31 [25, 36] min for the pre-implementation period and 18 [15, 22] min for the post-implementation period, with a difference of 13 min (42%). The median acquisition time was reduced by 4 min (25%) for BR-, 14.0 min (44%) for BR+, 14 min (38%) for MS, 11 min (52%) for MML, and 16 min (35%) for EPL. CONCLUSION The implementation of fast brain MRI sequences significantly reduced the acquisition times for the most commonly performed outpatient brain MRI protocols.
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Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Samuel Cartmell
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Daniel Briggs
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Oleg Pianykh
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - John Kirsch
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Stephen Cauley
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, Massachusetts
| | - Seretha Risacher
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Augusto Goncalves Filho
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Marc D Succi
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, Massachusetts
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Pamela Schaefer
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street Boston, Boston, Massachusetts; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts.
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Fritz B, Fritz J. MR Imaging–Ultrasonography Correlation of Acute and Chronic Foot and Ankle Conditions. Magn Reson Imaging Clin N Am 2023; 31:321-335. [PMID: 37019553 DOI: 10.1016/j.mric.2023.01.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Foot and ankle injuries are common musculoskeletal disorders. In the acute setting, ligamentous injuries are most common, whereas fractures, osseous avulsion injuries, tendon and retinaculum tears, and osteochondral injuries are less common. The most common chronic and overuse injuries include osteochondral and articular cartilage defects, tendinopathies, stress fractures, impingement syndromes, and neuropathies. Common forefoot conditions include traumatic and stress fractures, metatarsophalangeal and plantar plate injuries and degenerations, intermittent bursitis, and perineural fibrosis. Ultrasonography is well-suited for evaluating superficial tendons, ligaments, and muscles. MR imaging is best for deeper-located soft tissue structures, articular cartilage, and cancellous bone.
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Burke CJ, Fritz J, Samim M. Musculoskeletal Soft-tissue Masses. Magn Reson Imaging Clin N Am 2023; 31:285-308. [PMID: 37019551 DOI: 10.1016/j.mric.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Evaluation of soft-tissue masses has become a common clinical practice indication for imaging with both ultrasound and MR imaging. We illustrate the ultrasonography and MR imaging appearances of soft-tissue masses based on the various categories, updates, and reclassifications of the 2020 World Health Organization classification.
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Affiliation(s)
- Christopher J Burke
- NYU Langone Orthopedic Hospital, 301 East 17th Street, New York, NY 10003, USA.
| | - Jan Fritz
- NYU Langone Orthopedic Hospital, 301 East 17th Street, New York, NY 10003, USA
| | - Mohammad Samim
- NYU Langone Orthopedic Hospital, 301 East 17th Street, New York, NY 10003, USA
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Modern Low-Field MRI of the Musculoskeletal System: Practice Considerations, Opportunities, and Challenges. Invest Radiol 2023; 58:76-87. [PMID: 36165841 DOI: 10.1097/rli.0000000000000912] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
ABSTRACT Magnetic resonance imaging (MRI) provides essential information for diagnosing and treating musculoskeletal disorders. Although most musculoskeletal MRI examinations are performed at 1.5 and 3.0 T, modern low-field MRI systems offer new opportunities for affordable MRI worldwide. In 2021, a 0.55 T modern low-field, whole-body MRI system with an 80-cm-wide bore was introduced for clinical use in the United States and Europe. Compared with current higher-field-strength MRI systems, the 0.55 T MRI system has a lower total ownership cost, including purchase price, installation, and maintenance. Although signal-to-noise ratios scale with field strength, modern signal transmission and receiver chains improve signal yield compared with older low-field magnetic resonance scanner generations. Advanced radiofrequency coils permit short echo spacing and overall compacter echo trains than previously possible. Deep learning-based advanced image reconstruction algorithms provide substantial improvements in perceived signal-to-noise ratios, contrast, and spatial resolution. Musculoskeletal tissue contrast evolutions behave differently at 0.55 T, which requires careful consideration when designing pulse sequences. Similar to other field strengths, parallel imaging and simultaneous multislice acquisition techniques are vital for efficient musculoskeletal MRI acquisitions. Pliable receiver coils with a more cost-effective design offer a path to more affordable surface coils and improve image quality. Whereas fat suppression is inherently more challenging at lower field strengths, chemical shift selective fat suppression is reliable and homogeneous with modern low-field MRI technology. Dixon-based gradient echo pulse sequences provide efficient and reliable multicontrast options, including postcontrast MRI. Metal artifact reduction MRI benefits substantially from the lower field strength, including slice encoding for metal artifact correction for effective metal artifact reduction of high-susceptibility metallic implants. Wide-bore scanner designs offer exciting opportunities for interventional MRI. This review provides an overview of the economical aspects, signal and image quality considerations, technological components and coils, musculoskeletal tissue relaxation times, and image contrast of modern low-field MRI and discusses the mainstream and new applications, challenges, and opportunities of musculoskeletal MRI.
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Ibad HA, de Cesar Netto C, Shakoor D, Sisniega A, Liu S, Siewerdsen JH, Carrino JA, Zbijewski W, Demehri S. Computed Tomography: State-of-the-Art Advancements in Musculoskeletal Imaging. Invest Radiol 2023; 58:99-110. [PMID: 35976763 PMCID: PMC9742155 DOI: 10.1097/rli.0000000000000908] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
ABSTRACT Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in characterizing abnormalities, novel computed tomography (CT) techniques have found an emerging niche in several scenarios such as trauma, gout, and the characterization of pathologic biomechanical states during motion and weight-bearing. Recent developments and advancements in the field of musculoskeletal CT include 4-dimensional, cone-beam (CB), and dual-energy (DE) CT. Four-dimensional CT has the potential to quantify biomechanical derangements of peripheral joints in different joint positions to diagnose and characterize patellofemoral instability, scapholunate ligamentous injuries, and syndesmotic injuries. Cone-beam CT provides an opportunity to image peripheral joints during weight-bearing, augmenting the diagnosis and characterization of disease processes. Emerging CBCT technologies improved spatial resolution for osseous microstructures in the quantitative analysis of osteoarthritis-related subchondral bone changes, trauma, and fracture healing. Dual-energy CT-based material decomposition visualizes and quantifies monosodium urate crystals in gout, bone marrow edema in traumatic and nontraumatic fractures, and neoplastic disease. Recently, DE techniques have been applied to CBCT, contributing to increased image quality in contrast-enhanced arthrography, bone densitometry, and bone marrow imaging. This review describes 4-dimensional CT, CBCT, and DECT advances, current logistical limitations, and prospects for each technique.
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Affiliation(s)
- Hamza Ahmed Ibad
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Cesar de Cesar Netto
- Department of Orthopaedics and Rehabilitation, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Delaram Shakoor
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Alejandro Sisniega
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Stephen Liu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jeffrey H Siewerdsen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - John A. Carrino
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA
| | - Wojciech Zbijewski
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Shadpour Demehri
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Abstract
This article provides a focused overview of emerging technology in musculoskeletal MRI and CT. These technological advances have primarily focused on decreasing examination times, obtaining higher quality images, providing more convenient and economical imaging alternatives, and improving patient safety through lower radiation doses. New MRI acceleration methods using deep learning and novel reconstruction algorithms can reduce scanning times while maintaining high image quality. New synthetic techniques are now available that provide multiple tissue contrasts from a limited amount of MRI and CT data. Modern low-field-strength MRI scanners can provide a more convenient and economical imaging alternative in clinical practice, while clinical 7.0-T scanners have the potential to maximize image quality. Three-dimensional MRI curved planar reformation and cinematic rendering can provide improved methods for image representation. Photon-counting detector CT can provide lower radiation doses, higher spatial resolution, greater tissue contrast, and reduced noise in comparison with currently used energy-integrating detector CT scanners. Technological advances have also been made in challenging areas of musculoskeletal imaging, including MR neurography, imaging around metal, and dual-energy CT. While the preliminary results of these emerging technologies have been encouraging, whether they result in higher diagnostic performance requires further investigation.
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Affiliation(s)
- Richard Kijowski
- From the Department of Radiology, New York University Grossman School of Medicine, 660 First Ave, 3rd Floor, New York, NY 10016
| | - Jan Fritz
- From the Department of Radiology, New York University Grossman School of Medicine, 660 First Ave, 3rd Floor, New York, NY 10016
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Artificial Intelligence-Driven Ultra-Fast Superresolution MRI: 10-Fold Accelerated Musculoskeletal Turbo Spin Echo MRI Within Reach. Invest Radiol 2023; 58:28-42. [PMID: 36355637 DOI: 10.1097/rli.0000000000000928] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
ABSTRACT Magnetic resonance imaging (MRI) is the keystone of modern musculoskeletal imaging; however, long pulse sequence acquisition times may restrict patient tolerability and access. Advances in MRI scanners, coil technology, and innovative pulse sequence acceleration methods enable 4-fold turbo spin echo pulse sequence acceleration in clinical practice; however, at this speed, conventional image reconstruction approaches the signal-to-noise limits of temporal, spatial, and contrast resolution. Novel deep learning image reconstruction methods can minimize signal-to-noise interdependencies to better advantage than conventional image reconstruction, leading to unparalleled gains in image speed and quality when combined with parallel imaging and simultaneous multislice acquisition. The enormous potential of deep learning-based image reconstruction promises to facilitate the 10-fold acceleration of the turbo spin echo pulse sequence, equating to a total acquisition time of 2-3 minutes for entire MRI examinations of joints without sacrificing spatial resolution or image quality. Current investigations aim for a better understanding of stability and failure modes of image reconstruction networks, validation of network reconstruction performance with external data sets, determination of diagnostic performances with independent reference standards, establishing generalizability to other centers, scanners, field strengths, coils, and anatomy, and building publicly available benchmark data sets to compare methods and foster innovation and collaboration between the clinical and image processing community. In this article, we review basic concepts of deep learning-based acquisition and image reconstruction techniques for accelerating and improving the quality of musculoskeletal MRI, commercially available and developing deep learning-based MRI solutions, superresolution, denoising, generative adversarial networks, and combined strategies for deep learning-driven ultra-fast superresolution musculoskeletal MRI. This article aims to equip radiologists and imaging scientists with the necessary practical knowledge and enthusiasm to meet this exciting new era of musculoskeletal MRI.
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Radiomics and Deep Learning for Disease Detection in Musculoskeletal Radiology: An Overview of Novel MRI- and CT-Based Approaches. Invest Radiol 2023; 58:3-13. [PMID: 36070548 DOI: 10.1097/rli.0000000000000907] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
ABSTRACT Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radiology for various tasks, including acute injuries, chronic conditions, spinal abnormalities, and neoplasms. While early radiomics-based methods were often limited to a smaller number of higher-order image feature extractions, applying machine learning-based analytic models, multifactorial correlations, and classifiers now permits big data processing and testing thousands of features to identify relevant markers. A growing number of novel deep learning-based methods describe magnetic resonance imaging- and computed tomography-based algorithms for diagnosing anterior cruciate ligament tears, meniscus tears, articular cartilage defects, rotator cuff tears, fractures, metastatic skeletal disease, and soft tissue tumors. Initial radiomics and deep learning techniques have focused on binary detection tasks, such as determining the presence or absence of a single abnormality and differentiation of benign versus malignant. Newer-generation algorithms aim to include practically relevant multiclass characterization of detected abnormalities, such as typing and malignancy grading of neoplasms. So-called delta-radiomics assess tumor features before and after treatment, with temporal changes of radiomics features serving as surrogate markers for tumor responses to treatment. New approaches also predict treatment success rates, surgical resection completeness, and recurrence risk. Practice-relevant goals for the next generation of algorithms include diagnostic whole-organ and advanced classification capabilities. Important research objectives to fill current knowledge gaps include well-designed research studies to understand how diagnostic performances and suggested efficiency gains of isolated research settings translate into routine daily clinical practice. This article summarizes current radiomics- and machine learning-based magnetic resonance imaging and computed tomography approaches for musculoskeletal disease detection and offers a perspective on future goals and objectives.
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Postoperative MRI of the Ankle and Foot. Magn Reson Imaging Clin N Am 2022; 30:733-755. [DOI: 10.1016/j.mric.2022.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Musculoskeletal MR Image Segmentation with Artificial Intelligence. ADVANCES IN CLINICAL RADIOLOGY 2022; 4:179-188. [PMID: 36815063 PMCID: PMC9943059 DOI: 10.1016/j.yacr.2022.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Burke CJ, Khodarahmi I, Fritz J. Postoperative MR Imaging of Joints. Magn Reson Imaging Clin N Am 2022; 30:583-600. [DOI: 10.1016/j.mric.2022.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Khodarahmi I, Brinkmann IM, Lin DJ, Bruno M, Johnson PM, Knoll F, Keerthivasan MB, Chandarana H, Fritz J. New-Generation Low-Field Magnetic Resonance Imaging of Hip Arthroplasty Implants Using Slice Encoding for Metal Artifact Correction: First In Vitro Experience at 0.55 T and Comparison With 1.5 T. Invest Radiol 2022; 57:517-526. [PMID: 35239614 PMCID: PMC9363001 DOI: 10.1097/rli.0000000000000866] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Despite significant progress, artifact-free visualization of the bone and soft tissues around hip arthroplasty implants remains an unmet clinical need. New-generation low-field magnetic resonance imaging (MRI) systems now include slice encoding for metal artifact correction (SEMAC), which may result in smaller metallic artifacts and better image quality than standard-of-care 1.5 T MRI. This study aims to assess the feasibility of SEMAC on a new-generation 0.55 T system, optimize the pulse protocol parameters, and compare the results with those of a standard-of-care 1.5 T MRI. MATERIALS AND METHODS Titanium (Ti) and cobalt-chromium total hip arthroplasty implants embedded in a tissue-mimicking American Society for Testing and Materials gel phantom were evaluated using turbo spin echo, view angle tilting (VAT), and combined VAT and SEMAC (VAT + SEMAC) pulse sequences. To refine an MRI protocol at 0.55 T, the type of metal artifact reduction techniques and the effect of various pulse sequence parameters on metal artifacts were assessed through qualitative ranking of the images by 3 expert readers while taking measured spatial resolution, signal-to-noise ratios, and acquisition times into consideration. Signal-to-noise ratio efficiency and artifact size of the optimized 0.55 T protocols were compared with the 1.5 T standard and compressed-sensing SEMAC sequences. RESULTS Overall, the VAT + SEMAC sequence with at least 6 SEMAC encoding steps for Ti and 9 for cobalt-chromium implants was ranked higher than other sequences for metal reduction ( P < 0.05). Additional SEMAC encoding partitions did not result in further metal artifact reductions. Permitting minimal residual artifacts, low magnetic susceptibility Ti constructs may be sufficiently imaged with optimized turbo spin echo sequences obviating the need for SEMAC. In cross-platform comparison, 0.55 T acquisitions using the optimized protocols are associated with 45% to 64% smaller artifacts than 1.5 T VAT + SEMAC and VAT + compressed-sensing/SEMAC protocols at the expense of a 17% to 28% reduction in signal-to-noise ratio efficiency. B 1 -related artifacts are invariably smaller at 0.55 T than 1.5 T; however, artifacts related to B 0 distortion, although frequently smaller, may appear as signal pileups at 0.55 T. CONCLUSIONS Our results suggest that new-generation low-field SEMAC MRI reduces metal artifacts around hip arthroplasty implants to better advantage than current 1.5 T MRI standard of care. While the appearance of B 0 -related artifacts changes, reduction in B 1 -related artifacts plays a major role in the overall benefit of 0.55 T.
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Affiliation(s)
- Iman Khodarahmi
- Department of Radiology, New York University Grossman School of Medicine
| | | | - Dana J. Lin
- Department of Radiology, New York University Grossman School of Medicine
| | - Mary Bruno
- Department of Radiology, New York University Grossman School of Medicine
| | | | - Florian Knoll
- Department of Radiology, New York University Grossman School of Medicine
| | | | - Hersh Chandarana
- Department of Radiology, New York University Grossman School of Medicine
| | - Jan Fritz
- Department of Radiology, New York University Grossman School of Medicine
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Almansour H, Herrmann J, Gassenmaier S, Lingg A, Nickel MD, Kannengiesser S, Arberet S, Othman AE, Afat S. Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity. Acad Radiol 2022; 30:863-872. [PMID: 35810067 DOI: 10.1016/j.acra.2022.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/20/2022] [Accepted: 06/04/2022] [Indexed: 11/29/2022]
Abstract
RATIONALE AND OBJECTIVES To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interpolated breath-hold examination (VIBESR) at 3 Tesla. The standard T1-weighted images were used as the reference standard (VIBESD). MATERIALS AND METHODS Patients with diverse abdominal pathologies, who underwent a clinically indicated contrast-enhanced abdominal VIBE magnetic resonance imaging at 3T between March and June 2021 were retrospectively included. Following the acquisition of the standard VIBESD sequences, additional images for the non-contrast, dynamic contrast-enhanced and post-contrast T1-weighted VIBE acquisition were retrospectively reconstructed using the same raw data and employing a prototypical deep learning-based super-resolution reconstruction algorithm. The algorithm was designed to enhance edge sharpness by avoiding conventional k-space filtering and to perform a partial Fourier reconstruction in the slice phase-encoding direction for a predefined asymmetric sampling ratio. In the retrospective reconstruction, the asymmetric sampling was realized by omitting acquired samples at the end of the acquisition and therefore corresponding to a shorter acquisition. Four radiologists independently analyzed the image datasets (VIBESR and VIBESD) in a blinded manner. Outcome measures were: sharpness of abdominal organs, sharpness of vessels, image contrast, noise, hepatic lesion conspicuity and size, overall image quality and diagnostic confidence. These parameters were statistically compared and interrater reliability was computed using Fleiss' Kappa and intraclass correlation coefficient (ICC). Finally, the rate of detection of hepatic lesions was documented and was statistically compared using the paired Wilcoxon test. RESULTS A total of 32 patients aged 59 ± 16 years (23 men (72%), 9 women (28%)) were included. For VIBESR, breath-hold time was significantly reduced by approximately 13.6% (VIBESR 11.9 ± 1.2 seconds vs. VIBESD: 13.9 ± 1.4 seconds, p < 0.001). All readers rated sharpness of abdominal organs, sharpness of vessels to be superior in images with VIBESR (p values ranged between p = 0.005 and p < 0.001). Despite reduction of acquisition time, image contrast, noise, overall image quality and diagnostic confidence were not compromised, as there was no evidence of a difference between VIBESR and VIBESD (p > 0.05). The inter-reader agreement was substantial with a Fleiss' Kappa of >0.7 in all contrast phases. A total of 13 hepatic lesions were analyzed. The four readers observed a superior lesion conspicuity in VIBESR than in VIBESD (p values ranged between p = 0.046 and p < 0.001). In terms of lesion size, there was no significant difference between VIBESD and VIBESR for all readers. Finally, there was an excellent inter-reader agreement regarding lesion size (ICC > 0.9). For all readers, no statistically significant difference was observed regarding detection of hepatic lesions between VIBESD and VIBESR. CONCLUSION The deep learning-based super-resolution reconstruction with partial Fourier in the slice phase-encoding direction enabled a reduction of breath-hold time and improved image sharpness and lesion conspicuity in T1-weighted gradient echo sequences in abdominal magnetic resonance imaging at 3 Tesla. Faster acquisition time without compromising image quality or diagnostic confidence was possible by using this deep learning-based reconstruction technique.
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Affiliation(s)
- Haidara Almansour
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Judith Herrmann
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Andreas Lingg
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | | | | | - Simon Arberet
- Digital Technology & Innovation, Siemens Healthineers, Princeton, New Jersey
| | - Ahmed E Othman
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany; Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany.
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
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MRI evaluation of soft tissue tumors: comparison of a fast, isotropic, 3D T2-weighted fat-saturated sequence with a conventional 2D T2-weighted fat-saturated sequence for tumor characteristics, resolution, and acquisition time. Eur Radiol 2022; 32:8670-8680. [PMID: 35751699 DOI: 10.1007/s00330-022-08937-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/24/2022] [Accepted: 05/30/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To test whether a 4-fold accelerated 3D T2-weighted (T2) CAIPIRINHA SPACE TSE sequence with isotropic voxel size is equivalent to conventional 2DT2 TSE for the evaluation of intrinsic and perilesional soft tissue tumors (STT) characteristics. METHODS For 108 patients with histologically-proven STTs, MRI, including 3DT2 (CAIPIRINHA SPACE TSE) and 2DT2 (TSE) sequences, was performed. Two radiologists evaluated each sequence for quality (diagnostic, non-diagnostic), tumor characteristics (heterogeneity, signal intensity, margin), and the presence or absence of cortical involvement, marrow edema, and perilesional edema (PLE); tumor size and PLE extent were measured. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios and acquisition times for 2DT2 in two planes and 3DT2 sequences were reported. Descriptive statistics and inter-method agreement were reported. RESULTS Image quality was diagnostic for all sequences (100% [108/108]). No difference was observed between 3DT2 and 2DT2 tumor characteristics (p < 0.05). There was no difference in mean tumor size (3DT2: 2.9 ± 2.5 cm, 2DT2: 2.8 ± 2.6 cm, p = 0.4) or PLE extent (3DT2:0.5 ± 1.2 cm, 2DT2:0.5 ± 1.0 cm, p = 0.9) between the sequences. There was no difference in the SNR of tumors, marrow, and fat between the sequences, whereas the SNR of muscle was higher (p < 0.05) on 3DT2 than 2DT2. CNR measures on 3DT2 were similar to 2DT2 (p > 0.1). The average acquisition time was shorter for 3DT2 compared with 2DT2 (343 ± 127 s vs 475 ± 162 s, respectively). CONCLUSION Isotropic 3DT2 MRI offers higher spatial resolution, faster acquisition times, and equivalent assessments of STT characteristics compared to conventional 2DT2 MRI in two planes. 3DT2 is interchangeable with a 2DT2 sequence in tumor protocols. KEY POINTS • Isotropic 3DT2 CAIPIRINHA SPACE TSE offers higher spatial resolution than 2DT2 TSE and is equivalent to 2DT2 TSE for assessments of soft tissue tumor intrinsic and perilesional characteristics. • Multiplanar reformats of 3DT2 CAIPIRINHA SPACE TSE can substitute for 2DT2 TSE acquired in multiple planes, thereby reducing the acquisition time of MRI tumor protocols. • 3DT2 CAIPIRINHA SPACE TSE and 2DT2 TSE had similar CNR of tissues.
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Artificial intelligence in musculoskeletal imaging: a perspective on value propositions, clinical use, and obstacles. Skeletal Radiol 2022; 51:239-243. [PMID: 33983500 DOI: 10.1007/s00256-021-03802-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 04/25/2021] [Accepted: 04/25/2021] [Indexed: 02/08/2023]
Abstract
Artificial intelligence and deep learning (DL) offer musculoskeletal radiology exciting possibilities in multiple areas, including image reconstruction and transformation, tissue segmentation, workflow support, and disease detection. Novel DL-based image reconstruction algorithms correcting aliasing artifacts, signal loss, and noise amplification with previously unobtainable effectiveness are prime examples of how DL algorithms deliver promised value propositions in musculoskeletal radiology. The speed of DL-based tissue segmentation promises great efficiency gains that may permit the inclusion of tissue compositional-based information routinely into radiology reports. Similarly, DL algorithms give rise to a myriad of opportunities for workflow improvements, including intelligent and adaptive hanging protocols, speech recognition, report generation, scheduling, precertification, and billing. The value propositions of disease-detecting DL algorithms include reduced error rates and increased productivity. However, more studies using authentic clinical workflow settings are necessary to fully understand the value of DL algorithms for disease detection in clinical practice. Successful workflow integration and management of multiple algorithms are critical for translating the value propositions of DL algorithms into clinical practice but represent a major roadblock for which solutions are critically needed. While there is no consensus about the most sustainable business model, radiology departments will need to carefully weigh the benefits and disadvantages of each commercially available DL algorithm. Although more studies are needed to understand the value and impact of DL algorithms on clinical practice, DL technology will likely play an important role in the future of musculoskeletal imaging.
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Fritz B, Fritz J. Artificial intelligence for MRI diagnosis of joints: a scoping review of the current state-of-the-art of deep learning-based approaches. Skeletal Radiol 2022; 51:315-329. [PMID: 34467424 PMCID: PMC8692303 DOI: 10.1007/s00256-021-03830-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 05/17/2021] [Accepted: 05/23/2021] [Indexed: 02/02/2023]
Abstract
Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A variety of investigational deep learning algorithms have been developed to detect anterior cruciate ligament tears, meniscus tears, and rotator cuff disorders. Additional deep learning-based MRI algorithms have been investigated to detect Achilles tendon tears, recurrence prediction of musculoskeletal neoplasms, and complex segmentation of nerves, bones, and muscles. Proof-of-concept studies suggest that deep learning algorithms may achieve similar diagnostic performances when compared to human readers in meta-analyses; however, musculoskeletal radiologists outperformed most deep learning algorithms in studies including a direct comparison. Earlier investigations and developments of deep learning algorithms focused on the binary classification of the presence or absence of an abnormality, whereas more advanced deep learning algorithms start to include features for characterization and severity grading. While many studies have focused on comparing deep learning algorithms against human readers, there is a paucity of data on the performance differences of radiologists interpreting musculoskeletal MRI studies without and with artificial intelligence support. Similarly, studies demonstrating the generalizability and clinical applicability of deep learning algorithms using realistic clinical settings with workflow-integrated deep learning algorithms are sparse. Contingent upon future studies showing the clinical utility of deep learning algorithms, artificial intelligence may eventually translate into clinical practice to assist detection and characterization of various conditions on musculoskeletal MRI exams.
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Affiliation(s)
- Benjamin Fritz
- Department of Radiology, Balgrist University Hospital, Forchstrasse 340, CH-8008 Zurich, Switzerland ,Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Jan Fritz
- New York University Grossman School of Medicine, New York University, New York, NY 10016 USA
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Khodarahmi I, Fritz J. The Value of 3 Tesla Field Strength for Musculoskeletal Magnetic Resonance Imaging. Invest Radiol 2021; 56:749-763. [PMID: 34190717 DOI: 10.1097/rli.0000000000000801] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Musculoskeletal magnetic resonance imaging (MRI) is a careful negotiation between spatial, temporal, and contrast resolution, which builds the foundation for diagnostic performance and value. Many aspects of musculoskeletal MRI can improve the image quality and increase the acquisition speed; however, 3.0-T field strength has the highest impact within the current diagnostic range. In addition to the favorable attributes of 3.0-T field strength translating into high temporal, spatial, and contrast resolution, many 3.0-T MRI systems yield additional gains through high-performance gradients systems and radiofrequency pulse transmission technology, advanced multichannel receiver technology, and high-end surface coils. Compared with 1.5 T, 3.0-T MRI systems yield approximately 2-fold higher signal-to-noise ratios, enabling 4 times faster data acquisition or double the matrix size. Clinically, 3.0-T field strength translates into markedly higher scan efficiency, better image quality, more accurate visualization of small anatomic structures and abnormalities, and the ability to offer high-end applications, such as quantitative MRI and magnetic resonance neurography. Challenges of 3.0-T MRI include higher magnetic susceptibility, chemical shift, dielectric effects, and higher radiofrequency energy deposition, which can be managed successfully. The higher total cost of ownership of 3.0-T MRI systems can be offset by shorter musculoskeletal MRI examinations, higher-quality examinations, and utilization of advanced MRI techniques, which then can achieve higher gains and value than lower field systems. We provide a practice-focused review of the value of 3.0-T field strength for musculoskeletal MRI, practical solutions to challenges, and illustrations of a wide spectrum of gainful clinical applications.
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Affiliation(s)
- Iman Khodarahmi
- From the Division of Musculoskeletal Radiology, Department of Radiology, NYU Grossman School of Medicine, New York, NY
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Dalili D, Fritz J, Isaac A. 3D MRI of the Hand and Wrist: Technical Considerations and Clinical Applications. Semin Musculoskelet Radiol 2021; 25:501-513. [PMID: 34547815 DOI: 10.1055/s-0041-1731652] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
In the last few years, major developments have been observed in the field of magnetic resonance imaging (MRI). Advances in both scanner hardware and software technologies have witnessed great leaps, enhancing the diagnostic quality and, therefore, the value of MRI. In musculoskeletal radiology, three-dimensional (3D) MRI has become an integral component of the diagnostic pathway at our institutions. This technique is particularly relevant in patients with hand and wrist symptoms, due to the intricate nature of the anatomical structures and the wide range of differential diagnoses for most presentations. We review the benefits of 3D MRI of the hand and wrist, commonly used pulse sequences, clinical applications, limitations, and future directions. We offer guidance for enhancing the image quality and tips for image interpretation of 3D MRI of the hand and wrist.
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Affiliation(s)
- Danoob Dalili
- Epsom and St Helier University Hospitals, London, United Kingdom
| | - Jan Fritz
- NYU Grossman School of Medicine, New York University, New York, New York
| | - Amanda Isaac
- Guy's and St. Thomas' Hospitals NHS Foundation Trust, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London (KCL), London, United Kingdom
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43
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Ezzati F, Chalian M, Pezeshk P. 3D MRI of the Rheumatic Diseases. Semin Musculoskelet Radiol 2021; 25:425-432. [PMID: 34547808 DOI: 10.1055/s-0041-1731058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Magnetic resonance imaging (MRI) is commonly used to evaluate musculoskeletal pathologies due to its high spatial resolution and excellent tissue contrast. The diagnosis of rheumatic diseases can often be challenging. Investigation with conventional two-dimensional MRI is helpful for diagnosis and monitoring treatment. In the past few years, three-dimensional (3D) MRI has been more commonly used to assess joint pathologies including inflammatory and rheumatic diseases. This review discusses the techniques and protocols of 3D MRI and its diagnostic yield in the assessment of rheumatic diseases, along with different examples.
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Affiliation(s)
- Fatemeh Ezzati
- Division of Rheumatic and Autoimmune Diseases, Department of Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Majid Chalian
- Division of Musculoskeletal Radiology, Department of Radiology, University of Washington, Seattle, Washington
| | - Parham Pezeshk
- Division of Musculoskeletal Radiology, Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
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44
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Del Grande F, Hinterholzer N, Nanz D. 3D MRI: Technical Considerations and Practical Integration. Semin Musculoskelet Radiol 2021; 25:381-387. [PMID: 34547803 DOI: 10.1055/s-0041-1731059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
One of the main advantages of three-dimensional (3D) magnetic resonance imaging (MRI) is the possibility of isotropic voxels and reconstructed planar cuts through the volumetric data set in any orientation with multiplanar reformation software through real-time evaluation. For example, reformats by the radiologist during reporting allows exploitation of the full potential of isotropic 3D volumetric acquisition or through standardized retrospective reformats of thicker predefined slices of an isotropic volumetric data set by technologists. The main challenges for integrating 3D fast spin echo (FSE) and turbo spin-echo (TSE) MRI in clinical practice are a long acquisition time and some artifacts, whereas for integrating 3D gradient-recalled echo protocols, the main challenges are lower signal-to-noise ratios (SNRs) and the inability to produce intermediate, and T2-weighted contrast. The implementation of bidirectional parallel imaging acquisition and random undersampling acceleration strategies of 3D TSE pulse sequences substantially shortens the examination time with only minor SNR reductions. This article provides an overview of general technical considerations of 3D FSE and TSE sequences in musculoskeletal MRI. It also describes how these sequences achieve efficient data acquisition and reviews the main advantages and challenges for their introduction to clinical practice.
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Affiliation(s)
- Filippo Del Grande
- Clinica di Radiologia EOC, Istituto di Imaging della Svizzera Italiana (IIMSI), Lugano, Svizzera
| | - Natalie Hinterholzer
- SCMI, Swiss Center for Musculoskeletal Imaging, Balgrist Campus AG, Zürich, Switzerland
| | - Daniel Nanz
- SCMI, Swiss Center for Musculoskeletal Imaging, Balgrist Campus AG, Zürich, Switzerland.,University of Zürich, Zürich, Switzerland
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45
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Fritz B, Fritz J, Sutter R. 3D MRI of the Ankle: A Concise State-of-the-Art Review. Semin Musculoskelet Radiol 2021; 25:514-526. [PMID: 34547816 DOI: 10.1055/s-0041-1731332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Magnetic resonance imaging (MRI) is a powerful imaging modality for visualizing a wide range of ankle disorders that affect ligaments, tendons, and articular cartilage. Standard two-dimensional (2D) fast spin-echo (FSE) and turbo spin-echo (TSE) pulse sequences offer high signal-to-noise and contrast-to-noise ratios, but slice thickness limitations create partial volume effects. Modern three-dimensional (3D) FSE/TSE pulse sequences with isotropic voxel dimensions can achieve higher spatial resolution and similar contrast resolutions in ≤ 5 minutes of acquisition time. Advanced acceleration schemes have reduced the blurring effects of 3D FSE/TSE pulse sequences by affording shorter echo train lengths. The ability for thin-slice partitions and multiplanar reformation capabilities eliminate relevant partial volume effects and render modern 3D FSE/TSE pulse sequences excellently suited for MRI visualization of several oblique and curved structures around the ankle. Clinical efficiency gains can be achieved by replacing two or three 2D FSE/TSE sequences within an ankle protocol with a single isotropic 3D FSE/TSE pulse sequence. In this article, we review technical pulse sequence properties for 3D MRI of the ankle, discuss practical considerations for clinical implementation and achieving the highest image quality, compare diagnostic performance metrics of 2D and 3D MRI for major ankle structures, and illustrate a broad spectrum of ankle abnormalities.
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Affiliation(s)
- Benjamin Fritz
- Department of Radiology, University Hospital Balgrist, Zurich, Switzerland.,Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Jan Fritz
- New York University Grossman School of Medicine, New York University, New York, New York
| | - Reto Sutter
- Department of Radiology, University Hospital Balgrist, Zurich, Switzerland.,Faculty of Medicine, University of Zurich, Zurich, Switzerland
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Abstract
Three-dimensional (3D) magnetic resonance imaging of the spine is now clinically feasible due to technological advancements. Its advantages over two-dimensional imaging include higher in-plane spatial resolution and the ability for reformation in any plane that enables time savings in image acquisition and aids more accurate interpretation. Multispectral 3D techniques for imaging around metal are sometimes useful for evaluating anatomy adjacent to spinal fixation hardware. 3D gradient-recalled echo sequences, including ultrashort or zero time to echo sequences, can provide osseous detail similar to conventional computed tomography.
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Affiliation(s)
- Meghan Sahr
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York
| | - Ek Tsoon Tan
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York
| | - Darryl B Sneag
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, New York
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Pasoglou V, Van Nieuwenhove S, Peeters F, Duchêne G, Kirchgesner T, Lecouvet FE. 3D Whole-Body MRI of the Musculoskeletal System. Semin Musculoskelet Radiol 2021; 25:441-454. [PMID: 34547810 DOI: 10.1055/s-0041-1730401] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
With its outstanding soft tissue contrast, spatial resolution, and multiplanar capacities, magnetic resonance imaging (MRI) has become a widely used technique. Whole-body MRI (WB-MRI) has been introduced among diagnostic methods for the staging and follow-up assessment in oncologic patients, and international guidelines recommend its use. In nononcologic applications, WB-MRI is as a promising imaging tool in inflammatory diseases, such as seronegative arthritis and inflammatory myopathies. Technological advances have facilitated the introduction of three-dimensional (3D) almost isotropic sequences in MRI examinations covering the whole body. The possibility to reformat 3D images in any plane with equal or almost equal resolution offers comprehensive understanding of the anatomy, easier disease detection and characterization, and finally contributes to correct treatment planning. This article illustrates the basic principles, advantages, and limitations of the 3D approach in WB-MRI examinations and provides a short review of the literature.
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Affiliation(s)
- Vassiliki Pasoglou
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Sandy Van Nieuwenhove
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Frank Peeters
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Gaetan Duchêne
- MR applications, General Electric Healthcare, Diegem, Belgium
| | - Thomas Kirchgesner
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Frederic E Lecouvet
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
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Fritz J. Musculoskeletal 3D MRI: A Decade of Developments and Innovations Coming to Fruition. Semin Musculoskelet Radiol 2021; 25:379-380. [PMID: 34547802 DOI: 10.1055/s-0041-1733946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Jan Fritz
- Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, New York, New York
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Del Grande F, Rashidi A, Luna R, Delcogliano M, Stern SE, Dalili D, Fritz J. Five-Minute Five-Sequence Knee MRI Using Combined Simultaneous Multislice and Parallel Imaging Acceleration: Comparison with 10-Minute Parallel Imaging Knee MRI. Radiology 2021; 299:635-646. [PMID: 33825510 DOI: 10.1148/radiol.2021203655] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background Rapid knee MRI using combined simultaneous multislice (SMS) technique and parallel imaging (PI) acceleration can add value through reduced acquisition time but requires validation of clinical efficacy. Purpose To evaluate the performance of clinical fourfold SMS-PI-accelerated, 5-minute, five-sequence, multicontrast knee MRI protocols compared with standard twofold PI-accelerated, 10-minute knee MRI protocols. Materials and Methods Adults with painful knee conditions were prospectively enrolled from April 2018 to October 2019. Participants underwent fourfold SMS-PI-accelerated, 5-minute, turbo spin-echo (TSE) knee MRI and standard-of-care twofold PI-accelerated, 10-minute, TSE knee MRI at either 1.5 T or 3.0 T. Three radiologists independently evaluated the knee MRI studies for meniscal, tendinous, ligamentous, and osseocartilaginous injuries. Statistical analyses included k-based intermethod agreements and diagnostic performance testing. P < .05 was considered indicative of a statistically significant difference. Results A total of 252 adults were evaluated (mean age ± standard deviation, 47 years ± 17; 134 men). Among the participants, 104 (mean age, 42 years ± 18; 57 women) were in the 1.5-T arm and 148 (mean age, 46 years ± 17; 87 men) were in the 3.0-T arm. Twenty-nine participants (mean age, 38 years ± 12; 15 men) in the 1.5-T arm and 42 (mean age, 41 years ± 16; 24 men) in the 3.0-T arm underwent arthroscopy a mean of 45 days ± 31 and 45 days ± 22 after MRI, respectively. Intermethod agreements were good at 1.5 T (κ >0.71 [95% CI: 0.56, 0.83]) and very good at 3.0 T (κ >0.85 [95% CI: 0.69, 0.96]). The diagnostic performances of corresponding 5-minute and 10-minute MRI protocols were similar for 1.5 T, with areas under the receiver operating characteristic curve (AUCs) greater than 0.78 (95% CI: 0.71, 0.84) (P > .32), and 3.0 T, with AUCs greater than 0.83 (95% CI: 0.78, 0.88) (P > .32). Conclusion Comparisons of 5-minute five-sequence simultaneous multislice- and parallel imaging (PI)-accelerated and 10-minute five-sequence PI-accelerated turbo spin-echo MRI of the knee suggest similar performances at 1.5 and 3.0 T. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Subhas in this issue.
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Affiliation(s)
- Filippo Del Grande
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Ali Rashidi
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Rodrigo Luna
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Marco Delcogliano
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Steven E Stern
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Danoob Dalili
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
| | - Jan Fritz
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (F.D.G., A.R., R.L., D.D.); Department of Radiology, Ospedale Regionale di Lugano, Lugano, Switzerland (F.D.G.), Department of Orthopedic Surgery, Ospedale Regionale di Lugano, Lugano, Ticino, Switzerland (M.D.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Nuffield Orthopedic Center, Oxford University Hospitals NHS Foundation Trust, Oxford, England (D.D.); and Department of Radiology, Grossman School of Medicine, New York University, 660 1st Ave, 3rd Floor, Room 313, New York, NY 10016 (J.F.)
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