Vertebral level-dependent, angular, and linear translations of the spine have been measured in 2D and 3D using several imaging methods to quantify postural changes due to loading conditions and tasks. Here, we propose and validate a semiautomated method for measuring lumbar intervertebral angles and translations from upright MRI images using an endplate-based, joint coordinate system (JCS). This method was validated using 3D printed structures, representing intervertebral discs (IVD) at predetermined angles and heights, which were positioned between adjacent cadaveric vertebrae as a gold standard. Excellent agreement between our measurements and the gold standard was found for intervertebral angles in all anatomical planes (ICC > .997) and intervertebral distance measurements (ICC > .949). The proposed endplate-based JCS was compared with the vertebral body-based JCS proposed by the International Society of Biomechanics (ISB) using the 3D printed structures placed between 3 adjacent vertebrae from a cadaver with scoliosis. The endplate-based method was found to have better agreement with angles in the sagittal plane (ICC = 0.985) compared with the vertebral body-based method (ICC = .280). Thus, this method is accurate for measuring 3D intervertebral angles in the healthy and diseased lumbar spine.

Background The relationship between lumbar spine posture and muscle structure is not well understood. Objectives To investigate the predictive capacity of muscle structure on lumbar spine posture in active-duty Marines. Methods Forty-three Marines were scanned in this cross-sectional study, using an upright magnetic resonance imaging scanner while standing without load and standing, sitting, and prone on elbows with body armor. Cobb, horizontal, and sacral angles were measured. Marines were then scanned while unloaded in supine using a supine magnetic resonance imaging scanner. The imaging protocol consisted of T2 intervertebral disc mapping; high-resolution, anatomical, fat-water separation, and diffusion tensor imaging to quantify disc hydration and muscle volume, fat fraction, and restricted diffusion profiles in the lumbar muscles. A stepwise multiple linear regression model was used to identify physiological measures predictive of lumbar spine posture. Results The multiple regression model demonstrated that fractional anisotropy of the erector spinae was a significant predictor of lumbar posture for 7 of 18 dependent variables measured, and explained 20% to 35% of the variance in each model. Decreased fractional anisotropy of the erector spinae predicted decreased lordosis, lumbosacral extension, and anterior pelvic tilt. Conclusion Fractional anisotropy is inversely related with muscle fiber size, which is associated with the isometric force-generating capacity of a muscle fiber. This suggests that stronger erector spinae muscles predict decreased lordosis, lumbosacral extension, and anterior pelvic tilt in a highly trained population. J Orthop Sports Phys Ther 2018;48(8):613-621. Epub 17 May 2018. doi:10.2519/jospt.2018.7865.

Study design

Repeated measures.

Objective

The purpose of this study was to quantify the effect of operationally relevant loads and distributions on lumbar spine (LS) in a group of active-duty Marines.

Summary of background data

Low-back pain has been associated with heavy load carriage among military personnel. Although there are data describing the LS posture in response to load, the effect of varying load characteristics on LS posture remains unknown.

Methods

Magnetic resonance images of Marines (n = 12) were acquired when standing unloaded and when carrying 22, 33, and 45 kg of load distributed both 50% to 50% and 20% to 80% anteriorly and posteriorly. Images were used to measure LS and pelvic postures. Two-way repeated-measures ANOVA and posthoc tests were used to compare LS posture across load magnitudes and distributions (α = 0.05). This project was founded by the US Army Medical Research Acquisition Activity, Award No. W81XWH-13-2-0043, under Work Unit No. 1310.

Results

No changes in LS posture were induced when load was evenly distributed. When load was carried in the 20% to 80% distribution lumbosacral flexion increased as a result of sacral anterior rotation and overall reduced lumbar lordosis. This pattern was greater as load was increased between 22 and 33 kg, but did not increase further between 33 and 45 kg. We observed that the inferior LS became uniformly less lordotic, independently of load magnitude. However, the superior LS became progressively more lordotic with increasing load magnitude CONCLUSION.: Postural adaptations were found only when load was carried with a posterior bias, suggesting that load-carriage limits based on postural changes are relevant when loads are nonuniformly distributed. Although the tendency would be to interpret that loads should be carried symmetrically to protect the spine, the relationship between postural changes and injury are not clear. Finally, the operational efficiency of carrying load in this distribution needs to be tested.

Level of evidence

3.

Magnetic resonance imaging (MRI) is a diagnostic tool that can be used to noninvasively assess lumbar muscle size and fatty infiltration, important biomarkers of muscle health. Diffusion tensor imaging (DTI) is an MRI technique that is sensitive to muscle microstructural features such as fiber size (an important biomarker of muscle health), which is typically only assessed using invasive biopsy techniques. The goal of this study was to establish normative values of level-dependent lumbar muscle size, fat signal fraction, and restricted diffusion assessed by MRI in a highly active population. Forty-two active-duty Marines were imaged using a (a) high-resolution anatomical, (b) fat-water separation, and (c) DT-MRI scan. The multifidus and erector spinae muscles were compared at each level using two-way repeated measures ANOVA. Secondary analysis included Three dimensional (3D) reconstructions to qualitatively assess lumbar muscle size, fatty infiltration, and fiber orientation via tractography. The erector spinae was found to be larger than the multifidus above L5, with lower fat signal fraction above L3, and a less restricted diffusion profile than the multifidus above L4, with this pattern reversed in the lower lumbar spine. 3D reconstructions demonstrated accumulations of epimuscular fat in the anterior and posterior regions of the lumbar musculature, with minimal intramuscular fatty infiltration. Tractography images demonstrated different orientations of adjacent lumbar musculature, which cannot be visualized with standard MRI pulse sequences. The level dependent differences found in this study provide a normative baseline, for which to better understand whole muscle and microstructural changes associated with aging, low back pain, and pathology.

Military training aims to improve load carriage performance and reduce risk of injuries. Data describing the lumbar spine (LS) postural response to load carriage throughout training are limited. We hypothesised that training would reduce the LS postural response to load. The LS posture of 27 Marines was measured from upright MR images: with and without load (22.6 kg) at the beginning, middle, and end of School of Infantry (SOI) training. Disc degeneration was graded at L5-S1. No changes in posture and disc degeneration were found throughout training. During load carriage the LS became less lordotic and the sacrum more horizontal. Marines with disc degeneration had larger sacral postural perturbations in response to load. Our findings suggest that the postural response to load is defined more by the task needs than by the physical condition of the Marine. Practitioner Summary: The effect of military training on lumbar spine posture is unknown. The lumbar posture of 27 Marines was measured from upright MR images, with and without load throughout infantry training. No changes in posture or IVD degeneration were found across training. Marines with degeneration at the L5-S1 level had larger sacral postural perturbations in response to load.

Low back pain has a 70% higher prevalence in members of the armed forces than in the general population, possibly due to the loads and positions soldiers experience during training and combat. Although the influence of heavy load carriage on standing lumbar spine posture in this population is known, postures in other operationally relevant positions are unknown. Therefore, the purpose of this study was to characterize the effect of simulated military operational positions under relevant loading conditions on global and local lumbar spine postures in active duty male US Marines. Secondary objectives were to evaluate if intervertebral disc degeneration and low back pain affect lumbar spine postures. Magnetic resonance images were acquired on an upright scanner in the following operational positions: Natural standing with no external load, standing with body armor (11.3 kg), sitting with body armor, and prone on elbows with body armor. Custom software was used to measure global lumbar spine posture: Lumbosacral flexion, sacral slope, lordosis, local measures of intervertebral angles, and intervertebral distances. Sitting resulted in decreased lumbar lordosis at all levels of the spine except L1-L2. When subjects were prone on elbows, a significant increase in local lordosis was observed only at L5-S1 compared with all other positions. Marines with disc degeneration (77%) or history of low back pain (72%) had decreased lumbar range of motion and less lumbar extension than healthy Marines. These results indicate that a male Marine's pathology undergoes a stereotypic set of postural changes during functional tasks, which may impair performance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2145-2153, 2017.

The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.

Background

Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI₄ ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI₄ -C₁ , yielded greatest tumor conspicuity.

Purpose

To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI₄ -C₁ ) as a quantitative voxel-level classifier of PCa.

Study type

Retrospective.

Subjects

Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa.

Field strength/sequence

A 3 T, multishell diffusion-weighted and axial T2-weighted sequences.

Assessment

High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI₄ -C₁ and conventional ADC. Classifier images were also generated.

Statistical tests

Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI₄ -C₁ was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR₉₀ ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05.

Results

RSI₄ -C₁ outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR₉₀ (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05).

Data conclusion

RSI₄ -C₁ yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning.

Evidence level

3 TECHNICAL EFFICACY: Stage 2.

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10^-3, 2.8 × 10^-3, and >3.0 ×10^-2 mm²/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

Background

Multicompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer.

Purpose

To optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo.

Study type

Retrospective.

Subjects

Forty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer.

Field strength/sequence

3T multishell diffusion-weighted sequence.

Assessment

Multicompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps.

Statistical tests

Analysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models.

Results

The lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm² /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P < 0.05). Residuals were lowest in the peripheral zone and highest in tumors. Tumor tissue showed the largest reduction in fitting residual by increasing model order. Tumors had a greater proportion of signal from compartment 1 than normal tissue (P < 0.05). Tumor CNR and SIR were greater on compartment-1 signal maps than conventional DWI (P < 0.05) and increased with model order.

Data conclusion

The 4-compartment signal model best described diffusion in the prostate. Compartmental signal contributions revealed by this model may improve assessment of prostate cancer. Level of Evidence 3 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:628-639.