Technology and Tool Development for BACPAC: Qualitative and Quantitative Analysis of Accelerated Lumbar Spine MRI with Deep-Learning Based Image Reconstruction at 3T.

OBJECTIVES: To evaluate whether combining fast acquisitions with deep-learning reconstruction can provide diagnostically useful images and quantitative assessment comparable to standard-of-care acquisitions for lumbar spine magnetic resonance imaging (MRI). METHODS: Eighteen patients were imaged with both standard protocol and fast protocol using reduced signal averages, each protocol including sagittal fat-suppressed T2-weighted, sagittal T1-weighted, and axial T2-weighted 2D fast spin-echo sequences. Fast-acquisition data was additionally reconstructed using vendor-supplied deep-learning reconstruction with three different noise reduction factors. For qualitative analysis, standard images as well as fast images with and without deep-learning reconstruction were graded by three radiologists on five different categories. For quantitative analysis, convolutional neural networks were applied to sagittal T1-weighted images to segment intervertebral discs and vertebral bodies, and disc heights and vertebral body volumes were derived. RESULTS: Based on noninferiority testing on qualitative scores, fast images without deep-learning reconstruction were inferior to standard images for most categories. However, deep-learning reconstruction improved the average scores, and noninferiority was observed over 24 out of 45 comparisons (all with sagittal T2-weighted images while 4/5 comparisons with sagittal T1-weighted and axial T2-weighted images). Interobserver variability increased with 50 and 75% noise reduction factors. Deep-learning reconstructed fast images with 50% and 75% noise reduction factors had comparable disc heights and vertebral body volumes to standard images (r2≥ 0.86 for disc heights and r2≥ 0.98 for vertebral body volumes). CONCLUSIONS: This study demonstrated that deep-learning-reconstructed fast-acquisition images have the potential to provide noninferior image quality and comparable quantitative assessment to standard clinical images.

Institution-wide shape analysis of 3D spinal curvature and global alignment parameters.

The spine is an articulated, 3D structure with 6 degrees of translational and rotational freedom. Clinical studies have shown spinal deformities are associated with pain and functional disability in both adult and pediatric populations. Clinical decision making relies on accurate characterization of the spinal deformity and monitoring of its progression over time. However, Cobb angle measurements are time-consuming, are limited by interobserver variability, and represent a simplified 2D view of a 3D structure. Instead, spine deformities can be described by 3D shape parameters, addressing the limitations of current measurement methods. To this end, we develop and validate a deep learning algorithm to automatically extract the vertebral midline (from the upper endplate of S1 to the lower endplate of C7) for frontal and lateral radiographs. Our results demonstrate robust performance across datasets and patient populations. Approximations of 3D spines are reconstructed from the unit normalized midline curves of 20,118 pairs of full spine radiographs belonging to 15,378 patients acquired at our institution between 2008 and 2020. The resulting 3D dataset is used to describe global imbalance parameters in the patient population and to build a statistical shape model to describe global spine shape variations in preoperative deformity patients via eight interpretable shape parameters. The developed method can identify patient subgroups with similar shape characteristics without relying on an existing shape classification system.

Magnetization-prepared spoiled gradient-echo snapshot imaging for efficient measurement of R2 -R1ρ in knee cartilage.

PURPOSE: To validate the potential of quantifying R2 -R1ρ using one pair of signals with T1ρ preparation and T2 preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (Tprep ) for in vivo knee MRI. METHODS: Bloch equation simulations were first performed to assess the accuracy of quantifying R2 -R1ρ using T1ρ - and T2 -prepared signals with an equivalent Tprep . For validation of this technique in comparison to the conventional approach that calculates R2 -R1ρ after estimating both T2 and T1ρ , phantom experiments and in vivo validation with five healthy subjects and five osteoarthritis patients were performed at a clinical 3T scanner. RESULTS: Bloch equation simulations demonstrated that the accuracy of this efficient R2 -R1ρ quantification method and the optimal Tprep can be affected by image signal-to-noise ratio (SNR) and tissue relaxation times, but quantification can be closest to the reference with an around 25 ms Tprep for knee cartilage. Phantom experiments demonstrated that the proposed method can depict R2 -R1ρ changes with agarose gel concentration. With in vivo data, significant correlation was observed between cartilage R2 -R1ρ measured from the conventional and the proposed methods, and a Tprep of 25.6 ms provided the most agreement by Bland-Altman analysis. R2 -R1ρ was significantly lower in patients than in healthy subjects for most cartilage compartments. CONCLUSION: As a potential biomarker to indicate cartilage degeneration, R2 -R1ρ can be efficiently measured using one pair of T1ρ -prepared and T2 -prepared signals with an optimal Tprep considering cartilage relaxation times and image SNR.

Maximizing the use of batch production of 18F-FDOPA for imaging of brain tumors to increase availability of hybrid PET/MR imaging in clinical setting.

BACKGROUND: Amino acid PET imaging of brain tumors has been shown to play an important role in predicting tumor grade, delineation of tumor margins, and differentiating tumor recurrence from the background of postradiation changes, but is not commonly used in clinical practice because of high cost. We propose that PET/MRI imaging of patients grouped to the day of tracer radiosynthesis will significantly decrease the cost of PET imaging, which will improve patient access to PET. METHODS: Seventeen patients with either primary brain tumors or metastatic brain tumors were recruited for imaging on 3T PET/MRI and were scanned on 4 separate days in groups of 3 to 5 patients. The first group of consecutively imaged patients contained 3 patients, followed by 2 groups of 5 patients, and a last group of 4 patients. RESULTS: For each of the patients, standard of care gadolinium-enhanced MRI and dynamic PET imaging with 18F-FDOPA amino acid tracer was obtained. The total cost savings of scanning 17 patients in batches of 4 as opposed to individual radiosynthesis was 48.5% ($28 321). Semiquantitative analysis of tracer uptake in normal brain were performed with appropriate accumulation and expected subsequent washout. CONCLUSION: Amino acid PET tracers have been shown to play a critical role in the characterization of brain tumors but their adaptation to clinical practice has been limited because of the high cost of PET. Scheduling patient imaging to maximally use the radiosynthesis of imaging tracer significantly reduces the cost of PET and results in increased availability of PET tracer use in neuro-oncology.

Patients with Type 2 Diabetes Exhibit a More Mineralized Deep Cartilage Layer Compared with Nondiabetic Controls: A Pilot Study.

OBJECTIVE: To assess differences in biochemical composition of the deep cartilage layer in subjects with type 2 diabetes mellitus (T2DM) and nondiabetic controls using UTE (ultra-short echo time) T2* mapping and to investigate the association of vascular health and UTE T2* measurements. DESIGN: Ten subjects with T2DM matched for age, sex, and body mass index with 10 nondiabetic controls. A 3D UTE sequence with 6 echo times was acquired using 3T magnetic resonance imaging of the knee. For UTE T2* analysis, the deep cartilage layer was segmented and analyzed in 5 compartments (patella, medial, and lateral femur and tibia). The ankle brachial index (ABI) was obtained in all subjects. Linear regression analyses were used to assess associations of T2DM and UTE T2* relaxation times and the associations of ABI measurements and UTE measurements. RESULTS: Compared with nondiabetic controls, T2DM subjects had significantly lower mean T2*-UTE in the patella (mean difference 4.87 ms; 95% confidence interval [CI] 1.09-8.65; P = 0.015), the lateral tibia (mean difference 2.26 ms; 95% CI 0.06-4.45; P = 0.045), and the lateral femur (mean difference 4.96 ms; 95% CI 0.19-9.73; P = 0.043). Independent of diabetic status, subjects with higher ABI values, indicating better vascular health, had higher T2*-UTE of the patella (coefficient 15.2; 95% CI 3.3-21.4; P = 0.017), the medial tibia (coefficient 9.8; 95% CI 1.0-18.6; P = 0.031), and the lateral femur (coefficient 18.8; 95% CI 3.3-34.3; P = 0.021). CONCLUSIONS: T2*-UTE measurements of the deep cartilage layer were consistently lower in subjects with T2DM and in subjects with impaired vascular health, likely indicating increased mineralization of this layer.

Longitudinal analysis of the contribution of 3D patella and trochlear bone shape on patellofemoral joint osteoarthritic features.

To explore bone shape features that are associated with patellofemoral joint (PFJ) osteoarthritic features. Thirty subjects with PFJ degeneration (six males, 53.2 ± 9.8 years) and 23 controls (12 males, 48.1 ± 10.6 years) were included. Magnetic resonance (MR) assessment was performed to provide bone segmentation, morpholgocial grading, and cartilage relaxation times. In addition, subject self-reported symptoms were reported. Logistic regressions were used to identify the shape features that were associated with the presence and worsening of PFJ morphological lesions over 3 years, and worsening of self-reported symptoms. Statistical parametric mapping was used to evaluate the associations between shape features and cartilage relaxation times at 3 years. Results indicated that subjects with PFJ degeneration exhibited a trochlea with longer lateral condyle and shallower trochlear groove (adjusted odds ratio [OR] = 0.30; 95% confidence interval [CI]: 0.10, 0.86; P = .025). Subjects with worsening of PFJ degeneration exhibited a patella with equally distributed facets (adjusted OR = 3.14; 95% CI: 1.05, 9.37; P = .040) and lateral bump (adjusted OR = 0.14; 95% CI: 0.02, 0.83; P = .030). No shape features were associated with worsening of self-reported symptoms. Elevated T1ρ and T2 times at 3 years were associated with a patella with a lateral hook, equally distributed facets, round and thick as well as a trochlea larger in size (R = 0.38~0.46, P = .015~.025). The study demonstrated the ability of 3D statistical shape modeling to quantify patella and trochlear bone shape features that are associated with the presence and progression of PFJ osteoarthritic features.

Investigating the Association of Metabolic Biomarkers With Knee Cartilage Composition and Structural Abnormalities Using MRI: A Pilot Study.

OBJECTIVE: The goal of this study was to explore the metabolic syndrome-associated phenotype of osteoarthritis by investigating the cross-sectional associations of glycemic markers and serum lipids with knee cartilage composition and structural abnormalities in middle-aged adults. DESIGN: Twenty participants between 40 to 70 years of age with Kellgren-Lawrence score 0-1 in at least one knee were recruited at a single center. Knee cartilage composition was assessed using 3.0 T cartilage T2 and T1ρ mapping. Evaluation of structural knee abnormalities was performed using the modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). Linear regression was used to assess the associations of standardized fasting glucose (FG), hemoglobin A1c (HbA1c), insulin, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), non-HDL cholesterol, and triglycerides with cartilage T2 and T1ρ as well as WORMS subscores, adjusting for body mass index. RESULTS: Higher FG and higher HbA1c were associated with higher WORMS meniscus sum (beta coefficient 1.31 [95% confidence interval (CI): 0.57, 2.05], P = 0.002 per standard deviation [SD] increase in FG; beta coefficient 0.90 [95% CI: 0.07, 1.73], P = 0.035 per SD increase in HbA1c). Also, higher total cholesterol and higher non-HDL cholesterol were associated with higher WORMS cartilage sum (beta coefficient 0.94 [95% CI: 0.01, 1.86], P = 0.048 per SD increase in total cholesterol; beta coefficient 1.05 [95% CI: 0.14, 1.96], P = 0.03 per SD increase in non-HDL cholesterol). CONCLUSIONS: Higher FG and HbA1c were associated with increased meniscal degeneration while higher total and non-HDL cholesterol were associated with increased cartilage degeneration.

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain.

Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. Bone is a dynamic tissue undergoing continuous remodeling with the competing activity of osteoblasts, which produce the new bone matrix, and osteoclasts, whose function is to eliminate mineralized bone. [18F]-NaF is a positron emission tomography (PET) radiotracer that enables visualization of bone metabolism. [18F]-NaF is chemically absorbed into hydroxyapatite in the bone matrix by osteoblasts and can thus noninvasively detect osteoblastic activity, which is occult to conventional imaging techniques. Kinetic modeling of dynamic [18F]-NaF-PET data provides detailed quantitative measures of bone metabolism. Conventional semi-quantitative PET data, which utilizes standardized uptake values (SUVs) as a measure of radiotracer activity, is referred to as a static technique due to its snapshot of tracer uptake in time.  Kinetic modeling, however, utilizes dynamic image data where tracer levels are continuously acquired providing tracer uptake temporal resolution. From the kinetic modeling of dynamic data, quantitative values like blood flow and metabolic rate (i.e., potentially informative metrics of tracer dynamics) can be extracted, all with respect to the measured activity in the image data. When combined with dual modality PET-MRI, region-specific kinetic data can be correlated with anatomically registered high-resolution structural and pathologic information afforded by MRI. The goal of this methodological manuscript is to outline detailed techniques for performing and analyzing dynamic [18F]-NaF-PET-MRI data. The lumbar facet joint is a common site of degenerative arthritis disease and a common cause for axial low back pain.  Recent studies suggest [18F]-NaF-PET may serve as a useful biomarker of painful facetogenic disease.  The human lumbar facet joint will, therefore, be used as a prototypical region of interest for dynamic [18F]-NaF-PET-MRI analysis in this manuscript.

[18 F]-Sodium Fluoride PET/MR Imaging for Bone-Cartilage Interactions in Hip Osteoarthritis: A Feasibility Study.

This study characterized the distribution of [18 F]-sodium fluoride (NaF) uptake and blood flow in the femur and acetabulum in hip osteoarthritis (OA) patients to find associations between bone remodeling and cartilage composition in the presence of morphological abnormalities using simultaneous positron emission tomography and magnetic resonance imaging (PET/MR), quantitative magnetic resonance imaging (MRI) and femur shape modeling. Ten patients underwent a [18 F]-NaF PET/MR dynamic scan of the hip simultaneously with: (i) fast spin-echo CUBE for morphology grading and (ii) T1ρ /T2 magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots for cartilage, bone segmentation, bone shape modeling, and T1ρ /T2 quantification. The standardized uptake values (SUVs) and Patlak kinetic parameter (Kpat ) were calculated for each patient as PET outcomes, using an automated post-processing pipeline. Shape modeling was performed to extract the variations in bone shapes in the patients. Pearson's correlation coefficients were used to study the associations between bone shapes, PET outcomes, and patient reported pain. Direct associations between quantitative MR and PET evidence of bone remodeling were established in the acetabulum and femur. Associations of shaft thickness with SUV in the femur (p = 0.07) and Kpat in the acetabulum (p = 0.02), cam deformity with acetabular score (p = 0.09), osteophytic growth on the femur head with Kpat (p = 0.01) were observed. Pain had increased correlations with SUV in the acetabulum (p = 0.14) and femur (p = 0.09) when shaft thickness was accounted for. This study demonstrated the ability of [18 F]-NaF PET-MRI, 3D shape modeling, and quantitative MRI to investigate cartilage-bone interactions and bone shape features in hip OA, providing potential investigative tools to diagnose OA. © 2019 The Authors. Journal of Orthopaedic Research® published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society J Orthop Res 37:2671-2680, 2019.

Quantitative and Visual Assessments toward Potential Sub-mSv or Ultrafast FDG PET Using High-Sensitivity TOF PET in PET/MRI.

PURPOSE: Newer high-performance time-of-flight (TOF) positron emission tomography (PET) systems have the capability to preserve diagnostic image quality with low count density, while maintaining a high raw photon detection sensitivity that would allow for a reduction in injected dose or rapid data acquisition. To assess this, we performed quantitative and visual assessments of the PET images acquired using a highly sensitive (23.3 cps/kBq) large field of view (25-cm axial) silicon photomultiplier (SiPM)-based TOF PET (400-ps timing resolution) integrated with 3 T-MRI in comparison to PET images acquired on non-TOF PET/x-ray computed tomography (CT) systems. PROCEDURES: Whole-body 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT was acquired for 15 patients followed by whole body PET/magnetic resonance imaging (MRI) with an average injected dose of 325 ± 84 MBq. The PET list mode data from PET/MRI were reconstructed using full datasets (4 min/bed) and reduced datasets (2, 1, 0.5, and 0.25 min/bed). Qualitative assessment between PET/CT and PET/MR images were made. A Likert-type scale between 1 and 5, 1 for non-diagnostic, 3 equivalent to PET/CT, and 5 superior quality, was used. Maximum and mean standardized uptake values (SUVmax and SUVmean) of normal tissues and lesions detected were measured and compared. RESULTS: Mean visual assessment scores were 3.54 ± 0.32, 3.62 ± 0.38, and 3.69 ± 0.35 for the brain and 3.05 ± 0.49, 3.71 ± 0.45, and 4.14 ± 0.44 for the whole-body maximum intensity projections (MIPs) for 1, 2, and 4 min/bed PET/MR images, respectively. The SUVmean values for normal tissues were lower and statistically significant for images acquired at 4, 2, 1, 0.5, and 0.25 min/bed on the PET/MR, with values of - 18 ± 28 % (p < 0.001), - 16 ± 29 % (p = 0.001), - 16 ± 31 % (p = 0.002), - 14 ± 35 % (p < 0.001), and - 13 ± 34 % (p = 0.002), respectively. SUVmax and SUVpeak values of all lesions were higher and statistically significant (p < 0.05) for 4, 2, 1, 0.50, and 0.25 min/bed PET/MR datasets. CONCLUSION: High-sensitivity TOF PET showed comparable but still better visual image quality even at a much reduced activity in comparison to lower-sensitivity non-TOF PET. Our data translates to a seven times reduction in either injection dose for the same time or total scan time for the same injected dose. This "ultra-sensitivity" PET system provides a path to clinically acceptable extremely low-dose FDG PET studies (e.g., sub 1 mCi injection or sub-mSv effective dose) or PET studies as short as 1 min/bed (e.g., 6 min of total scan time) to cover whole body without compromising diagnostic performance.