Sagittal balance and intervertebral disc composition in patients with low back pain.

The aim of this study was to verify the relationship between quantitative T2 relaxation measurements of lumbar intervertebral discs (IVDs) and spinopelvic parameters in patients with chronic low back pain. The study was approved by the Clinical Hospital of the Ribeirao Preto Medical School (USP) Ethics Committee, and written consent was obtained from all patients. A total of 455 IVDs from 91 consecutive patients with chronic low back pain were included in this prospective study. All subjects were assessed using the Oswestry Disability Index and visual analogue scale questionnaires and were confirmed to have no other spine diseases except disc degeneration. Spinopelvic parameters including the pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), sagittal vertical axis (SVA), global tilt (GT), T1 pelvic angle (TPA), lumbar lordosis (LL), thoracic kyphosis (TK), pelvic incidence minus lumbar lordosis mismatch (PI-LL), and lack of lumbar lordosis (LLL) were measured. The study group was categorized according to the Roussouly classification. Sagittal T2 maps were acquired to extract the IVD relaxation times, and the complete manual segmentation of IVDs at all levels was performed using Display® software. Lumbar IVD T2 relaxation times showed significant correlation with PT (P<0.01), GT (P<0.01), TPA (P<0.01), PI-LL (P=0.01), and LLL (P=0.01). No difference was noted between Roussouly subtypes regarding T2 relaxation times at any disc level. Data from questionnaires showed no correlation with T2 relaxation times. Global tilt and T1 pelvic angle were correlated with IVD composition changes (T2 relaxometry). There was no correlation between clinical symptoms and IVD T2 relaxation times.

Sagittal balance and intervertebral disc composition in patients with low back pain

The aim of this study was to verify the relationship between quantitative T2 relaxation measurements of lumbar intervertebral discs (IVDs) and spinopelvic parameters in patients with chronic low back pain. The study was approved by the Clinical Hospital of the Ribeirao Preto Medical School (USP) Ethics Committee, and written consent was obtained from all patients. A total of 455 IVDs from 91 consecutive patients with chronic low back pain were included in this prospective study. All subjects were assessed using the Oswestry Disability Index and visual analogue scale questionnaires and were confirmed to have no other spine diseases except disc degeneration. Spinopelvic parameters including the pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), sagittal vertical axis (SVA), global tilt (GT), T1 pelvic angle (TPA), lumbar lordosis (LL), thoracic kyphosis (TK), pelvic incidence minus lumbar lordosis mismatch (PI-LL), and lack of lumbar lordosis (LLL) were measured. The study group was categorized according to the Roussouly classification. Sagittal T2 maps were acquired to extract the IVD relaxation times, and the complete manual segmentation of IVDs at all levels was performed using Display® software. Lumbar IVD T2 relaxation times showed significant correlation with PT (P<0.01), GT (P<0.01), TPA (P<0.01), PI-LL (P=0.01), and LLL (P=0.01). No difference was noted between Roussouly subtypes regarding T2 relaxation times at any disc level. Data from questionnaires showed no correlation with T2 relaxation times. Global tilt and T1 pelvic angle were correlated with IVD composition changes (T2 relaxometry). There was no correlation between clinical symptoms and IVD T2 relaxation times.

T1ρ and T2 mapping of the intervertebral disk: comparison of different methods of segmentation.

BACKGROUND AND PURPOSE: Intervertebral disk biochemical composition could be accessed in vivo by T1ρ and T2 relaxometry. We found no studies in the literature comparing different segmentation methods for data extraction using these techniques. Our aim was to compare different manual segmentation methods used to extract T1ρ and T2 relaxation times of intervertebral disks from MR imaging. Seven different methods of partial-disk segmentation techniques were compared with whole-disk segmentation as the reference standard. MATERIALS AND METHODS: Sagittal T1ρ and T2 maps were generated by using a 1.5T MR imaging scanner in 57 asymptomatic volunteers 20-40 years of age. Two hundred eighty-five lumbar disks were separated into 2 groups: nondegenerated disk (Pfirrmann I and II) and degenerated disk (Pfirrmann III and IV). In whole-disk segmentation, the disk was segmented in its entirety on all sections. Partial-disk segmentation methods included segmentation of the disk into 6, 5, 4, 3, and 1 sagittal sections. Circular ROIs positioned in the nucleus pulposus and annulus fibrosus were also used to extract T1ρ and T2, and data were compared with whole-disk segmentation RESULTS: In the nondegenerated group, segmentation of ≥5 sagittal sections showed no statistical difference with whole-disk segmentation. All the remaining partial-disk segmentation methods and circular ROIs showed different results from whole-disk segmentation (P < .001). In the degenerated disk group, all methods were statistically similar to whole-disk segmentation. All partial-segmentation methods, including circular ROIs, showed strong linear correlation with whole-disk segmentation in both the degenerated and nondegenerated disk groups. CONCLUSIONS: Manual segmentation showed strong reproducibility for T1ρ and T2 and strong linear correlation between partial- and whole-disk segmentation. Absolute T1ρ and T2 values extracted from different segmentation techniques were statistically different in disks with Pfirrmann grades I and II.

Classification of vertebral compression fractures in magnetic resonance images using spectral and fractal analysis.

Fractures with partial collapse of vertebral bodies are generically referred to as "vertebral compression fractures" or VCFs. VCFs can have different etiologies comprising trauma, bone failure related to osteoporosis, or metastatic cancer affecting bone. VCFs related to osteoporosis (benign fractures) and to cancer (malignant fractures) are commonly found in the elderly population. In the clinical setting, the differentiation between benign and malignant fractures is complex and difficult. This paper presents a study aimed at developing a system for computer-aided diagnosis to help in the differentiation between malignant and benign VCFs in magnetic resonance imaging (MRI). We used T1-weighted MRI of the lumbar spine in the sagittal plane. Images from 47 consecutive patients (31 women, 16 men, mean age 63 years) were studied, including 19 malignant fractures and 54 benign fractures. Spectral and fractal features were extracted from manually segmented images of 73 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor classifier with the Euclidean distance. Results obtained show that combinations of features derived from Fourier and wavelet transforms, together with the fractal dimension, were able to obtain correct classification rate up to 94.7% with area under the receiver operating characteristic curve up to 0.95.