Ari Borthakur

Novel diagnostic and prognostic methods for disc degeneration and low back pain

Low back pain (LBP) is the world’s leading debilitating condition [1]. It is estimated that 80% of the general population in the United States will develop LBP at one point in time [2,3]. Such pain can lead to diminished daily function and quality of life and work disability [4,5]. Not surprisingly, spine surgery to address LBP is one of the top five surgeries performed in the United States [6] where approximately 90-billion US dollars in health-care expenses are used annually to treat LBP [7]. As data indicate, LBP is clearly related with detrimental socioeconomic and health-care consequences that motivate efforts to identify LPB risk factors to develop improved prevention and treatment strategies. Although the etiology of LBP is multifaceted, disc degeneration (DD) has been suggested to be one of the most prominent risk factors [8–11]. However, whether DD is synonymous with LBP continues to be a topic of immense controversy. In this article, we review the current data regarding pain generating pathways and epidemiological evidence associating DD with LBP. In further support of this association, we review novel disc imaging techniques that may increase LBP diagnostic sensitivity and specificity. Finally, we discuss relevant aspects of the field of pain genes that may shed further light as to the links between DD and pain.

SPIN LOCKED BALANCED STEADY-STATE FREE PRECESSION (SLSSFP)

A spin‐locked balanced steady‐state free‐precession (slSSFP) pulse sequence is described that combines a balanced gradient‐echo acquisition with an off‐resonance spin‐lock pulse for fast MRI. The transient and steady‐state magnetization trajectory was solved numerically using the Bloch equations and was shown to be similar to balanced steady‐state free‐precession (bSSFP) for a range of T2/T1 and flip angles, although the slSSFP steady‐state could be maintained with considerably lower radio frequency (RF) power. In both simulations and brain scans performed at 7T, slSSFP was shown to exhibit similar contrast and signal‐to‐noise ratio (SNR) efficiency to bSSFP, but with significantly lower power. Magn Reson Med, 2009.

T1ρ Magnetic Resonance Imaging to Assess Cartilage Damage After Primary Shoulder Dislocation

Objectives: Anterior shoulder dislocation is a common injury with an estimated incidence of 23.1/100,000 person-years. In anterior dislocation, associated injuries typically involve the anteroinferior glenoid and posterosuperior humeral head. Patients who suffer a shoulder dislocation are at higher risk of developing glenohumeral arthropathy; the risk increases with recurrent dislocations. However, little is known about the initial cartilage damage after a primary shoulder dislocation. T1ρ is a magnetic resonance imaging (MRI) modality that allows quantification of cartilage proteoglycan content and can be used to detect physiologic changes in cartilage without intravenous contrast. Cartilage degeneration is characterized by decreased proteoglycan content, which results in an increased T1ρ relaxation constant. T1ρ MRI can detect differences in knee cartilage between Kellgren-Lawrence grades as well as acetabular cartilage changes in patients with femoroacetabular impingement. The objectives of this prospective study were to determine if T1ρ MRI can detect cartilage damage following primary shoulder dislocation and to assess for patterns in cartilage damage in anterior dislocations. Methods: This study received Institutional Review Board approval. Nine patients (mean age 31.3 years, range 20-59) who had sustained anterior shoulder dislocations underwent a 3T T1ρ MRI within ten days of their injury. Five control patients without prior dislocation or glenohumeral arthritis also underwent 3T T1ρ MRI. The T1ρ relaxation constant was determined for the entire glenoid and humeral head for dislocation and control patients. In addition, the glenoid was divided into nine zones, and T1ρ values were determined for each zone in dislocated and control patients to assess for differences between the two groups and to identify any patterns in cartilage damage in dislocated patients. Results: T1ρ mapping of glenohumeral cartilage in dislocated shoulders showed significant cartilage damage. Overall T1ρ values were increased in dislocated shoulders compared to control shoulders for glenoid and humeral head cartilage (53.46±0.99 vs. 36.60±3.6 and 46.50±1.1 vs. 36.19±1.7, respectively; mean±SEM, p = 0.0025, Fig. 1A). Furthermore, T1ρ values were significantly increased in all glenoid zones in dislocated shoulders compared to controls except for posterior/inferior (p = 0.064 for posterior/inferior, p < 0.02 for all other zones, Fig. 1B). However, there were no significant differences in T1ρ values between glenoid zones in dislocated shoulders across patients, reflecting widespread cartilage damage. Conclusion: T1ρ MRI is sensitive for detecting cartilage damage and proteoglycan loss after shoulder dislocation. T1ρ values were significantly higher (lower proteoglycan content) in nearly all glenoid zones in dislocated shoulders compared to controls and approached significant difference in the posterior/inferior zone. Although the anteroinferior glenoid and posterosuperior humeral head are characteristically affected in anterior dislocation, cartilage damage was surprisingly more widespread and affected the entire joint. The etiology of diffuse cartilage damage is unknown but may be due to hemarthrosis or additional trauma to the joint during humeral head relocation. Longer-term studies are needed to determine if the initial cartilage damage persists and if cartilage damage worsens with repeat dislocations.

Quantifying T1-rho in Alzheimer’s disease

clearance t1/2 and distribution volume ratios (DVR) were calculated through graphical analysis using the cerebellum as reference region. PIB parameters were compared with FDG uptake. Images showed marked binding in all AD subjects, especially in frontal, parietal and lateral temporal cortices as well as in the caudate nuclei with relative sparing of occipital and sensorimotor cortex, and very low uptake in cerebellar cortex. Images in LBD subjects were similar to AD subjects, though slightly higher uptake was observed in occipital and sensorimotor cortex. Cortical PIB clearance was significantly slower in LBD (t1/2 109 /28 min) and AD patients (t1/2 92 /13 min) when compared with control subjects (t1/2 61 /9 min). Clearance from cerebellar cortex was the same in all groups. Significantly higher DVR in neocortical areas were observed in AD (1.99 /0.36, p 0.01) and LBD patients (1.81 /0.25, p 0.01) when compared with control subjects (1.25 /0.23). There was an inverse correlation between PIB binding and glucose metabolism (r -0.67, p 0.0001). Regional uptake asymmetry indices were greater in LBD both in PIB and FDG studies. Conclusion: C-PIB PET suggests that cortical A is present in LBD subjects with progressive dementia in a similar degree to AD subjects. Longitudinal studies are warranted to more clearly define the role of A deposition in the development of dementia in both AD and LBD.