Clinical implementation of accelerated T2 mapping: Quantitative magnetic resonance imaging as a biomarker for annular tear and lumbar disc herniation

Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.

Lumbar disc herniation: Epidemiology, clinical and radiologic diagnosis WFNS spine committee recommendations

Objective

To formulate the most current, evidence-based recommendations regarding the epidemiology, clinical diagnosis, and radiographic diagnosis of lumbar herniated disk (LDH).

Methods

A systematic literature search in PubMed, MEDLINE, and CENTRAL was performed from 2012 to 2022 using the search terms "herniated lumbar disc", "epidemiology", "prevention" "clinical diagnosis", and "radiological diagnosis". Screening criteria resulted in 17, 16, and 90 studies respectively that were analyzed regarding epidemiology, clinical diagnosis, and radiographic diagnosis of LDH. Using the Delphi method and two rounds of voting at two separate international meetings, ten members of the WFNS (World Federation of Neurosurgical Societies) Spine Committee generated eleven final consensus statements.

Results

The lifetime risk for symptomatic LDH is 1-3%; of these, 60-90% resolve spontaneously. Risk factors for LDH include genetic and environmental factors, strenuous activity, and smoking. LDH is more common in males and in 30-50 year olds. A set of clinical tests, including manual muscle testing, sensory testing, Lasegue sign, and crossed Lasegue sign are recommended to diagnose LDH. Magnetic resonance imaging (MRI) is the gold standard for confirming suspected LDH.

Conclusions

These eleven final consensus statements provide current, evidence-based guidelines on the epidemiology, clinical diagnosis, and radiographic diagnosis of LDH for practicing spine surgeons worldwide.

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging

Rationale and objectives

To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 TSE).

Material and methods

Volunteers were included to evaluate the robustness and consecutive patients for morphological evaluation. They were scanned on a 3 T MR-scanner. Healthy volunteers underwent GRAPPATINI of the brain three times (day 1: scan/rescan; day 2: follow-up). Patients between the ages of 18 and 85 years who were able to provide written informed consent and who had no MRI contraindications were included. For morphological comparison two radiologists with 5 and 7 years of experience in brain MRI evaluated image quality using a Likert scale (1 being poor, 4 being excellent) in a blinded and randomized fashion.

Results

Images were successfully acquired in ten volunteers with a mean age of 25 years (ranging from 22 to 31 years) and 52 patients (23 men/29 women) with a mean age of 55 years (range of 22-83 years). Most brain regions showed repeatable and reproducible T2 values (rescan: CoV 0.75%-2.06%, ICC 69%-92.3%; follow-up: CoV 0.41%-1.59%, ICC 79.4%-95.8%), except for the caudate nucleus (rescan: CoV 7.25%, ICC 66.3%; follow-up: CoV 4.78%, ICC 80.9%). Image quality of sT2w was rated inferior to T2 TSE (median for T2 TSE: 3; sT2w: 1-2), but measurements revealed good interrater reliability of sT2w (lesion counting: ICC 0.85; diameter measure: ICC 0.68 and 0.67).

Conclusion

GRAPPATINI is a feasible and robust T2 mapping sequence of the brain on intra- and intersubject level. The resulting sT2w depict brain lesions comparable to T2 TSE despite its inferior image quality.

Artificial intelligence in spine surgery

The continuous progress of research and clinical trials has offered a wide variety of information concerning the spine and the treatment of the different spinal pathologies that may occur. Planning the best therapy for each patient could be a very difficult and challenging task as it often requires thorough processing of the patient's history and individual characteristics by the clinician. Clinicians and researchers also face problems when it comes to data availability due to patients' personal information protection policies. Artificial intelligence refers to the reproduction of human intelligence via special programs and computers that are trained in a way that simulates human cognitive functions. Artificial intelligence implementations to daily clinical practice such as surgical robots that facilitate spine surgery and reduce radiation dosage to medical staff, special algorithms that can predict the possible outcomes of conservative versus surgical treatment in patients with low back pain and disk herniations, and systems that create artificial populations with great resemblance and similar characteristics to real patients are considered to be a novel breakthrough in modern medicine. To enhance the body of the related literature and inform the readers on the clinical applications of artificial intelligence, we performed this review to discuss the contribution of artificial intelligence in spine surgery and pathology.

T1ρ, T2 and T2* mapping of lumbar intervertebral disc degeneration: a comparison study

BACKGROUND

Early and accurate assessment of lumbar intervertebral disc degeneration (IVDD) is very important to therapeutic strategy. This study aims to correlate and compare the performances of T1ρ, T2 and T2* mapping for Pfirrmann grades and morphologic changes in the IVDD.

METHODS

This prospective study included 39 subjects with 195 lumbar discs. T1ρ, T2 and T2* mapping were performed, and T1ρ, T2 and T2* values of nucleus pulposus (NP), and anterior and posterior annulus fibrosus were measured. IVDD was assessed with Pfirrmann grading and morphologic changes (normal, bulging, herniation and annular fissure). The performances of T1ρ, T2 and T2* relaxation times were compared for detecting early (Pfirrmann grade II-III) and advanced degeneration (Pfirrmann grade IV-V), as well as for morphologic changes.

RESULTS

T2 relaxation times was strongly corelated with T1ρ and T2* relaxation times. Areas under the curves (AUCs) of T1ρ, T2 and T2* relaxation times of NP were 0.70, 0.87 and 0.80 for early degeneration, and 0.91, 0.95 and 0.82 for advanced degeneration, respectively. AUCs of T1ρ, T2 and T2* relaxation times of NP were 0.78, 0.83 and 0.64 for bulging discs, 0.87, 0.89 and 0.69 for herniated discs, and 0.79, 0.82 and 0.69 for annular tearing, respectively. The AUC of T2 relaxation time was significantly higher than those of T1ρ relaxation times (both P < 0.01) for early IVDD, and the AUCs of T1ρ and T2 relaxation times for assessing advanced degeneration and morphologic changes were similar (P > 0.05) but significantly higher than that of T2*relaxation time (P < 0.01).

CONCLUSIONS

T2 mapping performed better than T1ρ mapping for the detection of early IVDD. T1ρ and T2 mapping performed similarly but better than T2* mapping for advanced degeneration and morphologic changes of IVDD.

Region of interest-specific loss functions improve T2 quantification with ultrafast T2 mapping MRI sequences in knee, hip and lumbar spine

MRI T2 mapping sequences quantitatively assess tissue health and depict early degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral discs (IVDs) but require long acquisition times. In MSK imaging, small features in cartilage and IVDs are crucial for diagnoses and must be preserved when reconstructing accelerated data. To these ends, we propose region of interest-specific postprocessing of accelerated acquisitions: a recurrent UNet deep learning architecture that provides T2 maps in knee cartilage, hip cartilage, and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions, optimizing for cartilage and IVD performance with a multi-component loss function that most heavily penalizes errors in those regions. Quantification errors in knee and hip cartilage were under 10% and 9% from acceleration factors R = 2 through 10, respectively, with bias for both under 3 ms for most of R = 2 through 12. In IVDs, mean quantification errors were under 12% from R = 2 through 6. A Gray Level Co-Occurrence Matrix-based scheme showed knee and hip pipelines outperformed state-of-the-art models, retaining smooth textures for most R and sharper ones through moderate R. Our methodology yields robust T2 maps while offering new approaches for optimizing and evaluating reconstruction algorithms to facilitate better preservation of small, clinically relevant features.

Detection of Imperceptible Intervertebral Disc Fissures in Conventional MRI-An AI Strategy for Improved Diagnostics

Annular fissures in the intervertebral discs are believed to be closely related to back pain. However, no sensitive non-invasive method exists to detect annular fissures. This study aimed to propose and test a method capable of detecting the presence and position of annular fissures in conventional magnetic resonance (MR) images non-invasively. The method utilizes textural features calculated from conventional MR images combined with attention mapping and artificial intelligence (AI)-based classification models. As ground truth, reference standard computed tomography (CT) discography was used. One hundred twenty-three intervertebral discs in 43 patients were examined with MR imaging followed by discography and CT. The fissure classification model determined the presence of fissures with 100% sensitivity and 97% specificity. Moreover, the true position of the fissures was correctly determined in 90 (87%) of the analyzed discs. Additionally, the proposed method was significantly more accurate at identifying fissures than the conventional radiological high-intensity zone marker. In conclusion, the findings suggest that the proposed method is a promising diagnostic tool to detect annular fissures of importance for back pain and might aid in clinical practice and allow for new non-invasive research related to the presence and position of individual fissures.

Applicative value of T2 mapping in evaluating lumbosacral nerve root injury induced by lumbosacral disc herniation

BACKGROUND

To alleviate the damage caused by nerve root entrapment mediated by lumbosacral disc herniation (LDH), an imaging method that allows quantitative evaluation of the lumbosacral nerve injury is necessary.

PURPOSE

To investigate the diagnostic value of magnetic resonance (MR) T2 mapping in nerve root injury caused by LDH.

MATERIAL AND METHODS

A total of 70 patients with unilateral sciatic nerve pain and 35 healthy volunteers were divided into three groups: LDH with nerve root entrapment; LDH without nerve root entrapment; and 35 healthy volunteers. All participants underwent 3.0-T MR with T1-weighted (T1W) imaging, T2-weighted (T2W) imaging, and T2-mapping images. T2 was measured and observed with the left and right nerve roots of the L4-S1 segments in healthy volunteers; the differences between the three groups were compared. T2 and the relaxation rate of nerve root injury were analyzed.

RESULTS

T2 showed significant differences among the three groups (F = 89.494; P = 0.000), receiver operating characteristic curve revealed that the T2 relaxation threshold was 79 ms, the area under curve (AUC) area was 0.86, sensitivity was 0.77, and specificity was 0.74; the T2 relaxation rate was 1.06, the AUC area was 0.88, sensitivity was 0.74, and specificity was 0.85.

CONCLUSION

T2 mapping could quantitatively evaluate the nerve root injury with lumbar disc degeneration. Hence, it can be used for the clinical evaluation of nerve root entrapment caused by LDH.

Data-driven myelin water imaging based on T1 and T2 relaxometry

Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T₁ and T₂ relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T₁ /T₂ data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.

Intradiscal injection of monosodium iodoacetate induces intervertebral disc degeneration in an experimental rabbit model

Background

Establishing an optimal animal model for intervertebral disc (IVD) degeneration is essential for developing new IVD therapies. The intra-articular injection of monosodium iodoacetate (MIA), which is commonly used in animal models of osteoarthritis, induces cartilage degeneration and progressive arthritis in a dose- and time-dependent manner. The purpose of this study was to determine the effect of MIA injections into rabbit IVDs on the progression of IVD degeneration evaluated by radiographic, micro-computerized tomography (micro-CT), magnetic resonance imaging (MRI), and histological analyses.

Methods

In total, 24 New Zealand White (NZW) rabbits were used in this study. Under general anesthesia, lumbar discs from L1–L2 to L4–L5 had a posterolateral percutaneous injection of MIA in contrast agent (CA) (L1–L2: CA only; L2–L3: MIA 0.01 mg; L3–L4: 0.1 mg; L4–L5: 1.0 mg; L5–L6: non-injection (NI) control). Disc height was radiographically monitored biweekly until 12 weeks after injection. Six rabbits were sacrificed at 2, 4, 8, and 12 weeks post-injection and processed for micro-CT, MRI (T2-mapping), and histological analyses. Three-dimensional (3D) disc height in five anatomical zones was evaluated by 3D reconstruction of micro-CT data.

Results

Disc height of MIA-injected discs (L2–L3 to L4–L5) gradually decreased time-dependently (P < 0.0001). The disc height of MIA 0.01 mg-injected discs was significantly higher than those of MIA 0.1 and 1.0 mg-injected discs (P < 0.01, respectively). 3D micro-CT analysis showed the dose- and time-dependent decrease of 3D disc height of MIA-injected discs predominantly in the posterior annulus fibrosus (AF) zone. MRI T2 values of MIA 0.1 and 1.0 mg-injected discs were significantly decreased compared to those of CA and/or NI controls (P < 0.05). Histological analyses showed progressive time- and dose-degenerative changes in the discs injected with MIA (P < 0.01). MIA induced cell death in the rabbit nucleus pulposus with a high percentage, while the percentage of cell clones was low.

Conclusions

The results of this study showed, for the first time, that the intradiscal injection of MIA induced degenerative changes of rabbit IVDs in a time- and dose-dependent manner. This study suggests that MIA injection into rabbit IVDs could be used as an animal model of IVD degeneration for developing future treatments.

Quantitative T2 mapping of the sacroiliac joint cartilage at 3T in patients with axial spondyloarthropathies

OBJECTIVE

To evaluate the diagnostic value of T2 mapping of sacroiliac joint cartilage in patients with axial spondyloarthropathies (SpA).

METHODS

Thirty-seven SpA patients and 43 controls (mean age: 36.5 ± 8.2; 20 men) prospectively underwent conventional MRI and T2 mapping of the sacroiliac joints at 3 T. SpA patients and their sacroiliac joints were categorized into active and inactive based on the presence of bone marrow edema on the conventional MRI. T2-relaxation times were measured by drawing six manual ROIs on the cartilaginous part of the joints. T2 values of the bilateral iliac and sacral joint cartilages for each patient (T2_subject), iliac and sacral cartilages for each sacroiliac joint (T2_joint), iliac cartilage (T2_iliac), and sacral cartilage (T2_sacral) were calculated and compared between SpA patients and controls, and active and inactive joints.

RESULTS

The T2_subject of SpA patients (50.48 ± 5.32 ms) was significantly higher than the T2_subject of the controls (46.33 ± 3.30 ms, p < 0.001). Selecting an optimal T2_subject cut-off value of 48.77 to differentiate SpA patients from controls revealed a sensitivity and a specificity of 62.2% and 81.4% respectively (AUC = 0.739). In SpA patients, T2_joint, T2_iliac, and T2_sacral values of the inactive joints were not significantly different from those of the active joints (p = 0.088, p = 0.179, and p = 0.069). T2_joint, T2_iliac, and T2_sacral values of the inactive joints of SpA patients were significantly higher than those of the controls (p = 0.012, p = 0.029, and p = 0.016).

CONCLUSIONS

T2 values of both active and inactive sacroiliac joint cartilages of SpA patients were increased. Thus, T2 mapping may be used in the diagnosis of SpA.

KEY POINTS

• Sacroiliac cartilage T2 values of SpA patients increase compared to those of the non-SpA controls. • Sacroiliac cartilage T2 values of active and inactive joints of SpA patients increase compared to those of the non-SpA controls. • Sacroiliac cartilage T2 values of active and inactive joints of SpA patients do not show statistically significant difference.

Differentiating brucella spondylitis from tuberculous spondylitis by the conventional MRI and MR T2 mapping: a prospective study

Background

Brucella spondylitis (BS) and tuberculous spondylitis (TS), caused initially by bacteremia, are the two leading types of granulomatous spinal infections. BS is easy to miss or may be misdiagnosed as TS. Our purpose aims to differentiate BS from TS in conventional MR imaging and MR T2 mapping.

Methods

We performed on 26 BS and 27 TS patients conventional MR imaging and MR T2 mapping. We analyzed the features in conventional MR imaging and measured T2 values of the lesion vertebrae (LV) and unaffected adjacent vertebrae (UAV) in BS and TS patients, respectively.

Results

There were no significant differences in sex, age, national between BS and TS. There was significantly lower severity of vertebral destruction, vertebral posterior convex deformity, dead bone, and abscess scope in BS when compared to TS (p  <  0.001, p  =  0.048, p  <  0.001, p  <  0.001, respectively). The vertebral hyperplasia was significantly higher in BS when compared to TS (p  <  0.001). The T2 value of the LV with BS was markedly higher than that in the UAV with BS and that in the LV and UAV with TS (p  <  0.001, p  <  0.037, p  <  0.001, respectively). The T2 value of the LV with TS was significantly higher than that of the UAV in TS and BS (p  <  0.001, p  <  0.001, respectively). There were no significant differences in the T2 value of the UAV between BS and TS (p  =  0.568).

Conclusions

The qualitative and quantitative evaluation may differentiate BS from TS. The conventional MR imaging helps to distinguish BS from TS by several distinctive features. MR T2 mapping has the additional potential to provide quantitative information between BS and TS.

Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review

Chronic Low Back Pain (LBP) is a symptom that may be caused by several diseases, and it is currently the leading cause of disability worldwide. The increased amount of digital images in orthopaedics has led to the development of methods related to artificial intelligence, and to computer vision in particular, which aim to improve diagnosis and treatment of LBP. In this manuscript, we have systematically reviewed the available literature on the use of computer vision in the diagnosis and treatment of LBP. A systematic research of PubMed electronic database was performed. The search strategy was set as the combinations of the following keywords: "Artificial Intelligence", "Feature Extraction", "Segmentation", "Computer Vision", "Machine Learning", "Deep Learning", "Neural Network", "Low Back Pain", "Lumbar". Results: The search returned a total of 558 articles. After careful evaluation of the abstracts, 358 were excluded, whereas 124 papers were excluded after full-text examination, taking the number of eligible articles to 76. The main applications of computer vision in LBP include feature extraction and segmentation, which are usually followed by further tasks. Most recent methods use deep learning models rather than digital image processing techniques. The best performing methods for segmentation of vertebrae, intervertebral discs, spinal canal and lumbar muscles achieve Sørensen-Dice scores greater than 90%, whereas studies focusing on localization and identification of structures collectively showed an accuracy greater than 80%. Future advances in artificial intelligence are expected to increase systems' autonomy and reliability, thus providing even more effective tools for the diagnosis and treatment of LBP.

The Clinical Diagnostic Value of Lumbar Intervertebral Disc Herniation Based on MRI Images

MRI was used to measure the changes in the angle of the facet joints of the lumbar spine and analyze the relationship between it and the herniated lumbar intervertebral disc. Analysis of the causes of lumbar disc herniation from the anatomy and morphology of the spine provides a basis for the early diagnosis and prevention of lumbar disc herniation. There is a certain correlation between the changes shown in MRI imaging of lumbar disc herniation and the TCM syndromes of lumbar intervertebral disc herniation. There is a correlation between the syndromes of lumbar disc herniation and the direct signs of MRI: pathological type, herniated position, and degree of herniation. Indirect signs with MR, nerve root compression and dural sac compression, are related. The MRI examination results can help syndrome differentiation to improve its accuracy to a certain extent. MRI has high sensitivity for the measurement of the angle of the facet joints of the lumbar spine and can be used to study the correlation between the changes of the facet joint angles and the herniated disc. Facet joint asymmetry is closely related to lateral lumbar disc herniation, which may be one of its pathogenesis factors. The herniated intervertebral disc is mostly on the sagittal side of the facet joint, and the facet joint angle on the side of the herniated disc is more sagittal. The asymmetry of the facet joints is not related to the central lumbar disc herniation, and the angle of the facet joints on both sides of the central lumbar disc herniation is partial sagittal.