Brain volume loss in individuals over time: Source of variance and limits of detectability.

BACKGROUND: Brain volume loss measured from magnetic resonance imaging (MRI) is a marker of neurodegeneration and predictor of disability progression in MS, and is commonly used to assess drug efficacy at the group level in clinical trials. Whether measures of brain volume loss could be useful to help guide management of individual patients depends on the relative magnitude of the changes over a given interval to physiological and technical sources of variability. GOAL: To understand the relative contributions of neurodegeneration vs. physiological and technical sources of variability to measurements of brain volume loss in individuals. MATERIAL AND METHODS: Multiple T1-weighted 3D MPRAGE images were acquired from a healthy volunteer and MS patient over varying time intervals: 7 times on the first day (before breakfast at 7:30AM and then every 2 â€‹h for 12 â€‹h), each day for the next 6 working days, and 6 times over the remainder of the year, on 2 â€‹Siemens MRI scanners: 1.5T Sonata (S1) and 3.0T TIM Trio (S2). Scan-reposition-rescan data were acquired on S2 for daily, monthly and 1-year visits. Percent brain volume change (PBVC) was measured from baseline to each follow-up scan using FSL/SIENA. We estimated the effect of physiologic fluctuations on brain volume using linear regression of the PBVC values over hourly and daily intervals. The magnitude of the physiological effect was estimated by comparing the root-mean-square error (RMSE) of the regression of all the data points relative to the regression line, for the hourly scans vs the daily scans. Variance due to technical sources was assessed as the RMSE of the regression over time using the intracranial volume as a reference. RESULTS: The RMSE of PBVC over 12 â€‹h, for both scanners combined, ("Hours", 0.15%), was similar to the day-to-day variation over 1 week ("Days", 0.14%), and both were smaller than the RMS error over the year (0.21%). All of these variations, however, were smaller than the scan-reposition-rescan RMSE (0.32%). The variability of PBVC for the individual scanners followed the same trend. The standard error of the mean (SEM) for PBVC was 0.26 for S1, and 0.22 for S2. From these values, we computed the minimum detectable change (MDC) to be 0.7% on S1 and 0.6% on S2. The location of the brain along the z-axis of the magnet inversely correlated with brain volume change for hourly and daily brain volume fluctuations (p â€‹< â€‹0.01). CONCLUSION: Consistent diurnal brain volume fluctuations attributable to physiological shifts were not detectable in this small study. Technical sources of variation dominate measured changes in brain volume in individuals until the volume loss exceeds around 0.6-0.7%. Reliable interpretation of measured brain volume changes as pathological (greater than normal aging) in individuals over 1 year requires changes in excess of about 1.1% (depending on the scanner). Reliable brain atrophy detection in an individual may be feasible if the rate of brain volume loss is large, or if the measurement interval is sufficiently long.

Surface-based analysis reveals regions of reduced cortical magnetization transfer ratio in patients with multiple sclerosis: a proposed method for imaging subpial demyelination.

The in vivo detection of subpial cortical gray matter lesions in multiple sclerosis is challenging. We quantified the spatial extent of subpial decreases in the magnetization transfer ratio (MTR) of cortical gray matter in subjects with multiple sclerosis, as such reductions may indicate regions of cortical demyelination. We exploited the unique geometry of cortical lesions by using two-dimensional parametric surface models of the cortex instead of traditional three-dimensional voxel-wise analyses. MTR images were mapped onto intermediate surfaces between the pial and white matter surfaces and were used to compute differences between secondary-progressive MS (n = 12), relapsing-remitting MS (n = 12), and normal control (n = 12) groups as well as between each individual patient and the normal controls. We identified large regions of significantly reduced cortical MTR in secondary-progressive patients when compared with normal controls. We also identified large regions of reduced cortical MTR in 11 individual patients (8 secondary-progressive, 3 relapsing-remitting). The secondary-progressive patients showed larger areas of abnormally low MTR compared with relapsing-remitting patients both at the group level and on an individual basis. The spatial distributions of abnormal MTR preferentially involved cingulate cortex, insula, and the depths of sulci, in agreement with pathological descriptions of subpial gray matter lesion distribution. These findings suggest that our method is a plausible in vivo imaging technique for quantifying subpial cortical demyelinating lesions in patients with multiple sclerosis and, furthermore, can be applied at the typical clinical field strength of 1.5 T.

Primary progressive multiple sclerosis: part of the MS disease spectrum or separate disease entity?

Multiple sclerosis (MS), the most frequent demyelinating disease, is characterized by a variable disease course. The majority of patients starts with relapsing remitting (RR) disease; approximately 50-60% of these patients progress to secondary progressive (SP) disease. Only about 15% of the patients develop a progressive disease course from onset, termed primary progressive multiple sclerosis (PPMS); the underlying pathogenic mechanisms responsible for onset of the disease with either PPMS or relapsing remitting multiple sclerosis (RRMS) are unknown. Patients with PPMS do not show a female predominance and usually have a later onset of disease compared to patients with RRMS. Monozygous twins can be concordant or discordant for disease courses indicating that the disease course is not only genetically determined. Primary progressive multiple sclerosis and secondary progressive multiple sclerosis (SPMS) share many similarities in imaging and pathological findings. Differences observed among the different disease courses are more of a quantitative than qualitative nature suggesting that the different phenotypes are part of a disease spectrum modulated by individual genetic predisposition and environmental influences. In this review, we summarize the knowledge regarding the clinical, epidemiological, imaging, and pathological characteristics of PPMS and compare those characteristics with RRMS and SPMS.

Evaluation of automated techniques for the quantification of grey matter atrophy in patients with multiple sclerosis.

Several methods exist and are frequently used to quantify grey matter (GM) atrophy in multiple sclerosis (MS). Fundamental to all available techniques is the accurate segmentation of GM in the brain, a difficult task confounded even further by the pathology present in the brains of MS patients. In this paper, we examine the segmentations of six different automated techniques and compare them to a manually defined reference standard. Results demonstrate that, although the algorithms perform similarly to manual segmentations of cortical GM, severe shortcomings are present in the segmentation of deep GM structures. This deficiency is particularly relevant given the current interest in the role of GM in MS and the numerous reports of atrophy in deep GM structures.

Gradient distortions in MRI: characterizing and correcting for their effects on SIENA-generated measures of brain volume change.

Precise and accurate quantification of whole-brain atrophy based on magnetic resonance imaging (MRI) data is an important goal in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease and multiple sclerosis. We found that inconsistent MRI positioning of subjects is common in typically acquired clinical trial data - particularly along the magnet's long (i.e., Z) axis. We also found that, if not corrected for, the gradient distortion effects associated with such Z-shifts can significantly decrease the accuracy and precision of MRI-derived measures of whole-brain atrophy - negative effects that increase in magnitude with (i) increases in the Z-distance between the brains to be compared and (ii) increases in the Z-distance from magnet isocenter of the center of the pair of brains to be compared. These gradient distortion effects can be reduced by accurate subject positioning, and they can also be corrected post hoc with the use of appropriately-generated gradient-distortion correction fields. We used a novel DUPLO-based phantom to develop a spherical-harmonics-based gradient distortion field that was used to (i) correct for observed Z-shift-associated gradient distortion effects on SIENA-generated measures of brain atrophy and (ii) simulate the gradient distortion effects that might be expected with a greater range of Z-shifts than those that we were able to acquire. Our results suggest that consistent alignment to magnet isocenter and/or correcting for the observed effects of gradient distortion should lead to more accurate and precise estimates of brain-related changes and, as a result, to increased statistical power in studies aimed at understanding the natural progression and the effective treatment of neurodegenerative disorders.

The metabolic epicenter of supratentorial gliomas: a 1H-MRSI study.

BACKGROUND: Assessing the impact of glioma location on prognosis remains elusive. We approached the problem using multivoxel proton magnetic resonance spectroscopic imaging (1H-MRSI) to define a tumor "metabolic epicenter", and examined the relationship of metabolic epicenter location to survival and histopathological grade. METHODS: We studied 54 consecutive patients with a supratentorial glioma (astrocytoma or oligodendroglioma, WHO grades II-IV). The metabolic epicenter in each tumor was defined as the 1H-MRSI voxel containing maximum intra-tumoral choline on preoperative imaging. Tumor location was considered the X-Y-Z coordinate position, in a standardized stereotactic space, of the metabolic epicenter. Correlation between epicenter location and survival or grade was assessed. RESULTS: Metabolic epicenter location correlated significantly with patient survival for all tumors (r2 = 0.30, p = 0.0002) and astrocytomas alone (r2 = 0.32, p = 0.005). A predictive model based on both metabolic epicenter location and histopathological grade accounted for 70% of the variability in survival, substantially improving on histology alone to predict survival. Location also correlated significantly with grade (r2 = 0.25, p = 0.001): higher grade tumors had a metabolic epicenter closer to the midpoint of the brain. CONCLUSIONS: The concept of the metabolic epicenter eliminates several problems related to existing methods of classifying glioma location. The location of the metabolic epicenter is strongly correlated with overall survival and histopathological grade, suggesting that it reflects biological factors underlying glioma growth and malignant dedifferentiation. These findings may be clinically relevant to predicting patterns of local glioma recurrence, and in planning resective surgery or radiotherapy.

1H-MRS quantification of tNA and tCr in patients with multiple sclerosis: a meta-analytic review.

Meta-analysis was performed on the results of 75 comparisons from the 30 peer-reviewed publications that used proton magnetic resonance spectroscopy (1H-MRS) or spectroscopic imaging to (i) quantify the mean concentrations of total creatine (tCr, found in neurons, astrocytes and oligodendrocytes), and/or total N-acetyl groups (tNA, found only in neurons), in the lesional and/or non-lesional white matter (WM) and/or the grey matter (GM) of patients with multiple sclerosis (MS) and (ii) compare these values with those in the homologous tissues of normal controls (NC). For mean [tNA] values, there was (i) a large-effect-sized overall decrease in patients' lesional WM relative to NC WM (25 comparisons), (ii) a medium-effect-sized overall decrease in patients' non-lesional WM relative to NC WM (36 comparisons) and (iii) a medium-effect-sized overall decrease in patients' GM relative to NC GM (14 comparisons). Patients' mean [tNA] values were sometimes statistically normal but were never statistically increased. For mean [tCr] values, there was (i) no statistically significant overall change in the patients' lesional WM relative to NC WM (24 comparisons), although statistically significant increases and decreases were sometimes found, (ii) a medium-effect-sized overall increase in patients' non-lesional WM relative to NC WM (33 comparisons) and (iii) no statistically significant overall change in patients' GM relative to NC GM (12 comparisons), although a significant decrease was found in one comparison. Of 41 comparisons with statistically significant changes, 38 combined in a way that would probably result in decreased mean [tNA]/[tCr] ratios such that (i) 66% had statistically decreased mean [tNA] and statistically unchanged mean [tCr] values, (ii) 13% had statistically decreased mean [tNA] and statistically increased mean [tCr] values and (iii) 21% had statistically unchanged mean [tNA] values and statistically increased mean [tCr] values. Of the 25 comparisons that came from studies that also analysed [tNA]/[tCr] ratios, the direction of change in mean [tNA] values and mean [tNA]/[tCr] ratios was concordant in 84%. In comparisons that quantified both [tNA] and [tCr], there was a similar amount of variability in both measures in each of the different tissue types studied, both in patients and NCs. Together, these results suggest that within-voxel tNA/tCr ratios can be interpreted as valid and accurate surrogate measures of 'cerebral tissue integrity'-with decreased tNA/tCr ratios indicating some combination of neuroaxonal disturbance, oligodendroglial disturbance, and astrocytic proliferation. These results also suggest that, although within-voxel tNA/tCr ratios are not perfect indicators of [tNA] content, they do represent a practical compromise to acquiring surrogate measures of within-voxel neuroaxonal integrity.

Magnetization transfer can predict clinical evolution in patients with multiple sclerosis.

The clinical course of multiple sclerosis (MS) is highly variable ranging from benign to aggressive, and is difficult to predict. Since magnetization transfer (MT) imaging can detect focal abnormalities in normal-appearing white matter (NAWM) before the appearance of lesions on conventional MRI, we hypothesized that changes in MT might be able to predict the clinical evolution of MS. We assessed MR data from MS patients who were subsequently followed clinically for 5 years. We computed the mean MT ratio (MTr) in gray matter, in lesions identified on T2-weighted MRI, and in NAWM, as well as in a thick central brain slice for each patient. Patients were divided into stable and worsening groups according to their change in Expanded Disability Status Scale (EDSS) scores over 5 years. We calculated the sensitivity, specificity, predictive value, and odds ratio of the baseline MTr measures in order to assess their prognostic utility. We found significant differences in baseline MTr values in NAWM (p = 0.005) and brain slice (p = 0.03) between clinically stable and worsening MS patients. When these MTr values were compared with changes in EDSS over 5 years, a strong correlation was found between the EDSS changes and MTr values in both NAWM (SRCC = -0.76, p < 0.001) and in the brain slice (SRCC = 0.59, p = 0.01). Baseline NAWM MTr correctly predicted clinical evolution in 15/18 patients (1 false positive and 2 false negatives), yielding a positive predictive value of 77.78 %, a negative predictive value of 88.89 %, and an odds ratio of 28. The relationship between 5-year changes in EDSS and MTr values in T2 weighted MRI lesions was weaker (SRCC = -0.43, p = 0.07). Our data support the notion that the quantification of MTr in the NAWM can predict the clinical evolution of MS. Lower MTr values predict poorer long-term clinical outcome. Abnormalities of MTr values in the NAWM are more relevant to the development of future patient disability than those in the T2-weighted MRI lesions.

Gabapentin therapy for amyotrophic lateral sclerosis: lack of improvement in neuronal integrity shown by MR spectroscopy.

BACKGROUND AND PURPOSE: Proton MR spectroscopy has revealed impaired neuronal integrity in the motor cortex of patients with amyotrophic lateral sclerosis (ALS). We hypothesized that the N-acetylaspartate (NAA)-creatine (Cr) ratios in the motor cortex and adjacent brain could reflect the therapeutic effectiveness of gabapentin (GBP) treatment in ALS. METHODS: Eight patients with ALS underwent MR spectroscopy before and 26.5 days +/- 8.8 after starting GBP. In 10 patients with ALS who were not treated with GBP, paired spectra were obtained 21.4 days +/- 7.2 apart. Fourteen healthy subjects underwent a single MR spectroscopic examination. The NAA/Cr ratio was measured in the precentral gyrus, the postcentral gyrus, the superior parietal lobule, the supplementary motor area, and the premotor cortex. RESULTS: The NAA/Cr ratio was decreased in the precentral and postcentral gyri of patients with ALS compared with healthy controls. In those with ALS, the change in the NAA/Cr ratio was not different between treated patients and untreated patients in any of the regions studied. CONCLUSION: No improvement in neuronal integrity was detected in motor and nonmotor cerebral regions after GBP treatment. This result agrees with that of prior investigations showing the equivocal clinical effectiveness of GBP for ALS and supports the validity of the NAA/Cr ratio as a surrogate of therapeutic effectiveness.

Proton magnetic resonance spectroscopic imaging can predict length of survival in patients with supratentorial gliomas.

OBJECTIVE: We compared the ability of proton magnetic resonance spectroscopic imaging ((1)H-MRSI) measures with that of standard clinicopathological measures to predict length of survival in patients with supratentorial gliomas. METHODS: We developed two sets of leave-one-out logistic regression models based on either 1) intratumoral (1)H-MRSI features, including maximum values of a) choline and b) lactate-lipid, c) number of (1)H-MRSI voxels with low N-acetyl group values, and d) number of (1)H-MRSI voxels with high lactate-lipid values, all (a-d) of which were normalized to creatine in normal-appearing brain, or 2) standard clinicopathological features, including a) tumor histopathological grade, b) patient age, c) performance of surgical debulking, and d) tumor diagnosis (i.e., oligodendroglioma, astrocytoma). We assessed the accuracy of these two models in predicting patient survival for 6, 12, 24, and 48 months by performing receiver operating characteristic curve analysis. Cox proportional hazards analysis was performed to assess the extent to which patient survival could be explained by the above predictors. We then performed a series of leave-one-out linear multiple regression analyses to determine how well patient survival could be predicted in a continuous fashion. RESULTS: The results of using the models based on (1)H-MRSI and clinicopathological features were equally good, accounting for 81 and 64% of the variability (r(2)) in patients' actual survival durations. All features except number of (1)H-MRSI voxels with lactate-lipid/creatine values of at least 1 were significant predictors of survival in the (1)H-MRSI model. Two features (tumor grade and debulking) were found to be significant predictors in the clinicopathological model. Survival as a continuous variable was predicted accurately on the basis of the (1)H-MRSI data (r = 0.77, P < 0.001; median prediction error, 1.7 mo). CONCLUSION: Our results suggest that appropriate analysis of (1)H-MRSI data can predict survival in patients with supratentorial gliomas at least as accurately as data derived from more invasive clinicopathological features.

Multiple sclerosis vs acute disseminated encephalomyelitis in childhood.

The initial presenting clinical and laboratory findings of either acute disseminated encephalomyelitis or the first attack of multiple sclerosis in the pediatric population were compared and contrasted. A retrospective review of the medical records was conducted of all children younger than 17 years who presented with either the diagnosis of acute disseminated encephalomyelitis or multiple sclerosis between 1987 and 2001. Seventeen cases of clinically definite multiple sclerosis (seven female, mean age 12.4 +/- 4.5 years) and seven cases of acute disseminated encephalomyelitis (three female; mean age 8.7 +/- 3.8 years) were reviewed. Systemic and nonfocal neurologic symptoms were more commonly evident in acute disseminated encephalomyelitis than in multiple sclerosis: fever (43% vs 6%), headache (57% vs 24%), fatigue (71% vs 29%), vomiting (57% vs 0%), and encephalopathy (71% vs 6%). In multiple sclerosis patients, T(2)-weighted white matter magnetic resonance imaging lesions were more commonly located in the corpus callosum (64% vs 17%) and the periventricular area (91% vs 50%) compared with those in patients with acute disseminated encephalomyelitis. These results suggest that acute disseminated encephalomyelitis and multiple sclerosis can be differentiated to some degree according to clinical and radiologic data at initial presentation, which is important because the long-term prognosis for childhood multiple sclerosis appears to be less favorable.

Brain volume and fatigue in patients with postpoliomyelitis syndrome.

BACKGROUND: Acute paralytic poliomyelitis is associated with encephalitis. Early brain inflammation may produce permanent neuronal injury with brain atrophy, which may result in symptoms such as fatigue. Brain volume has not been assessed in postpoliomyelitis syndrome (PPS). OBJECTIVE: To determine whether brain volume is decreased compared with that in normal controls, and whether brain volume is associated with fatigue in patients with PPS. DESIGN: A cross-sectional study. SETTING: Tertiary university-affiliated hospital postpolio and multiple sclerosis (MS) clinics. PARTICIPANTS: Forty-nine ambulatory patients with PPS, 28 normal controls, and 53 ambulatory patients with MS. METHODS: We studied the brains of all study subjects with magnetic resonance imaging by using a 1.5 T Siemens Sonata machine. The subjects completed the Fatigue Severity Scale. Multivariable linear regression models were computed to evaluate the contribution of PPS and MS compared with controls to explain brain volume. MAIN OUTCOME MEASUREMENTS: Normalized brain volume (NBV) was assessed with the automated program Structured Image Evaluation, using Normalization, of Atrophy method from the acquired magnetic resonance images. This method may miss brainstem atrophy. RESULTS: Technically adequate NBV measurements were available for 42 patients with PPS, 27 controls, and 49 patients with MS. The mean (standard deviation) age was 60.9 ± 7.6 years for patients with PPS, 47.0 ± 14.6 years for controls, and 46.2 ± 9.4 years for patients with MS. In a multivariable model adjusted for age and gender, NBV was not significantly different in patients with PPS compared with that in controls (P = .28). As expected, when using a similar model for patients with MS, NBV was significantly decreased compared with that in controls (P = .006). There was no significant association between NBV and fatigue in subjects with PPS (Spearman ρ = 0.23; P = .19). CONCLUSIONS: No significant whole-brain atrophy was found, and no association of brain volume with fatigue in PPS. Brain atrophy was confirmed in MS. It is possible that brainstem atrophy was not recognized by this study.

Large, nonplateauing relationship between clinical disability and cerebral white matter lesion load in patients with multiple sclerosis.

OBJECTIVE: To better characterize the relationship between cerebral white matter lesion load (CWM-LL) and clinical disability by (1) covering the entire range of the Kurtzke Expanded Disability Status Scale (EDSS), (2) minimizing nonbiological sources of variability, and (3) increasing pathologic specificity by studying CWM lesions that are hypointense on T1-weighted magnetic resonance imaging. DESIGN: Cross-sectional, retrospective study. SETTING: Hospital-based multiple sclerosis (MS) clinic. Patients  A total of 110 patients with untreated MS were recruited and studied from June 1, 1997, through June 30, 2003. MAIN OUTCOME MEASURES: Cube-rooted CWM-LL and EDSS-measured clinical disability scores. RESULTS: We found a large, nonplateauing relationship between cube-rooted CWM-LL and concurrent EDSS scores, more so for T1-hypointense than T2-hyperintense lesions (r = 0.619 vs 0.548). Correlations between the EDSS scores and CWM-LL diminished when, as typically done in clinical trials, only those patients with EDSS scores of 0 to 6.0 were studied (n = 92; r = 0.523 for T1-hypointense lesions and r = 0.457 for T2-hyperintense lesions); more important, a series of boot-strapped correlations suggested that this decrease was not simply due to smaller sample size, and these relationships remained even after correcting for disease duration. CONCLUSION: A large, nonplateauing relationship exists between CWM-LL and EDSS-measured clinical disability when patients with MS are studied to examine the entire range of disability, minimize nonbiological sources of variability, and increase pathologic specificity.

(1)H-MRSI evidence for cortical gray matter pathology that is independent of cerebral white matter lesion load in patients with secondary progressive multiple sclerosis.

We examined: (i) neuro-axonal disturbance (as indicated by (1)H-MRSI NA/Cr values) in the cortical grey matter (cGM) of 10 untreated patients with relapsing-remitting (RR) and 10 with secondary-progressive (SP) multiple sclerosis (MS), and (ii) the relationships between cGM-NA/Cr values and the degree of EDSS-measured clinical disability and cerebral white-matter (WM) lesion load (LL) in these patients. Whereas mean and median cGM-NA/Cr values in our RR group were similar to those in 18 age-matched normal controls (NC), large statistically-significant decreases (between 14.3% and 18.5%) were found in our SP group relative to both our RR and NC groups. When data from all patients was combined, we found: (i) a large negative correlation between EDSS scores and cGM-NA/Cr values (r=-0.55); and (ii) a larger negative correlation of cGM-NA/Cr values with cerebral T1-hypointese WM-LL (T1-LL, r=-0.73) than with cerebral T2-hyperintense-LL (T2-LL, r=-0.63). Importantly, (i) correlations of WM-LL with cGM-NA/Cr were larger in the RR group than in the SP group (T1-LL: r=-0.79 vs. -0.54; T2-LL: r=-0.63 vs. -0.51), and (ii) cerebral WM-LL values could not fully account for the extent of the decrease in mean cGM-NA/Cr that was seen in our SP group relative to our NC group. Our observations are consistent with the possibilities that: (i) in patients with RR-MS, (1)H-MRSI-measured cGM neuro-axonal disturbances are strongly related to the effects of axonal transection that are associated with cerebral WM lesions; and (ii) in patients with SP-MS, such cGM neuro-axonal disturbances are more severe and are associated with a more-widespread degenerative process (which probably includes a considerable degree of cortical demyelination).

Fatigue in post-poliomyelitis syndrome: association with disease-related, behavioral, and psychosocial factors.

OBJECTIVE: To determine the biopsychosocial correlates of general, physical, and mental fatigue in patients with postpoliomyelitis syndrome (PPS) by assessing the additional contribution of potentially modifiable factors after accounting for important nonmodifiable disease-related factors. It was hypothesized that disease-related, behavioral, and psychosocial factors would contribute in different ways to general, physical, and mental fatigue in PPS and that a portion of fatigue would be determined by potentially modifiable factors. DESIGN: Cross-sectional study. SETTING: A tertiary university-affiliated hospital post-polio clinic. PATIENTS: Fifty-two ambulatory patients with PPS who were not severely depressed were included. ASSESSMENT OF RISK FACTORS: Potential correlates for fatigue included disease-related factors (acute polio weakness, time since acute polio, PPS duration, muscle strength, pain, forced vital capacity, maximum inspiratory pressure, maximum expiratory pressure, body mass index, disability, fibromyalgia), behavioral factors (physical activity, sleep quality), and psychosocial factors (depression, stress, self-efficacy). MAIN OUTCOME MEASUREMENTS: Fatigue was assessed with the Multidimensional Fatigue Inventory (MFI; assesses fatigue on 5 subscales) and the Fatigue Severity Scale (FSS). RESULTS: Multivariate models were computed for MFI General, Physical, and Mental Fatigue. Age-adjusted multivariate models with nonmodifiable factors included the following predictors of (1) MFI General Fatigue: maximum inspiratory pressure, fibromyalgia, muscle strength; (2) MFI Physical Fatigue: maximum expiratory pressure, muscle strength, age, time since acute polio; and (3) MFI Mental Fatigue: none. The following potentially modifiable predictors made an additional contribution to the models: (1) MFI General Fatigue: stress, depression; (2) MFI Physical Fatigue: physical activity, pain; and (3) MFI Mental Fatigue: stress. CONCLUSIONS: PPS fatigue is multidimensional. Different types of fatigue are determined by different variables. Potentially modifiable factors account for a portion of fatigue in PPS.

Prospective serial proton MR spectroscopic assessment of response to tamoxifen for recurrent malignant glioma.

OBJECTIVE: Early prediction of imminent failure during chemotherapy for malignant glioma has the potential to guide proactive alterations in treatment before frank tumor progression. We prospectively followed patients with recurrent malignant glioma receiving tamoxifen chemotherapy using proton magnetic resonance spectroscopic imaging ((1)H-MRSI) to identify intratumoral metabolic changes preceding clinical and radiological failure. METHODS: We performed serial (1)H-MRSI examinations to assess intratumoral metabolite intensities in 16 patients receiving high-dose oral tamoxifen monotherapy for recurrent malignant glioma (WHO grade III or IV) as part of a phase II clinical trial. Patients were followed until treatment failure, death, or trial termination. RESULTS: Patients were officially classified as responders (7 patients) or non-responders (9 patients) 8 weeks into treatment. At 8 weeks, responders and non-responders had different intratumoral intensities across all measured metabolites except choline. Beyond 8 weeks, metabolite intensities remained stable in all responders, but changed again with approaching disease progression. Choline, lipid, choline/NAA, and lactate/NAA were significantly elevated (P < 0.02), while creatine (P < 0.04) was significantly reduced, compared to stabilized levels on average 4 weeks prior to failure. Lactate was significantly elevated (P = 0.036) fully 8 weeks prior to failure. In one patient who was still responding to tamoxifen at the conclusion of the trial, metabolite intensities never deviated from 8-week levels for the duration of follow-up. CONCLUSIONS: Characteristic global intratumoral metabolic changes, detectable on serial (1)H-MRSI studies, occur in response to chemotherapy for malignant glioma and may predict imminent treatment failure before actual clinical and radiological disease progression.