Nancy A. Obuchowski

Magnetic resonance imaging of the lumbar spine in people without back pain

BACKGROUND The relation between abnormalities in the lumbar spine and low back pain is controversial. We examined the prevalence of abnormal findings on magnetic resonance imaging (MRI) scans of the lumbar spine in people without back pain. METHODS We performed MRI examinations on 98 asymptomatic people. The scans were read independently by two neuroradiologists who did not know the clinical status of the subjects. To reduce the possibility of bias in interpreting the studies, abnormal MRI scans from 27 people with back pain were mixed randomly with the scans from the asymptomatic people. We used the following standardized terms to classify the five intervertebral disks in the lumbosacral spine: normal, bulge (circumferential symmetric extension of the disk beyond the interspace), protrusion (focal or asymmetric extension of the disk beyond the interspace), and extrusion (more extreme extension of the disk beyond the interspace). Nonintervertebral disk abnormalities, such as facet arthropathy, were also documented. RESULTS Thirty-six percent of the 98 asymptomatic subjects had normal disks at all levels. With the results of the two readings averaged, 52 percent of the subjects had a bulge at at least one level, 27 percent had a protrusion, and 1 percent had an extrusion. Thirty-eight percent had an abnormality of more than one intervertebral disk. The prevalence of bulges, but not of protrusions, increased with age. The most common nonintervertebral disk abnormalities were Schmorls nodes (herniation of the disk into the vertebral-body end plate), found in 19 percent of the subjects; annular defects (disruption of the outer fibrous ring of the disk), in 14 percent; and facet arthropathy (degenerative disease of the posterior articular processes of the vertebrae), in 8 percent. The findings were similar in men and women. CONCLUSIONS On MRI examination of the lumbar spine, many people without back pain have disk bulges or protrusions but not extrusions. Given the high prevalence of these findings and of back pain, the discovery by MRI of bulges or protrusions in people with low back pain may frequently be coincidental.

Association between Peridural Scar and Recurrent Radicular Pain after Lumbar Discectomy: Magnetic Resonance Evaluation

The purpose of this study was to investigate the presence of any correlation between recurrent radicular pain during the first six months following first surgery for herniated lumbar intervertebral disc and the amount of lumbar peridural fibrosis as defined by MR imaging. 197 patients who underwent first-time single-level unilateral discectomy for lumbar disc herniation were evaluated in a randomized, double-blind, controlled multicenter clinical trial. Clinical assessments, performed by physicians blinded to patient treatment status, were conducted preoperatively and at one and six months postoperatively. The enhanced MR images of the operative site utilized in the analysis were obtained at six months postoperatively. Radicular pain was recorded by the patient using a validated visual analog pain scale in which 0 = no pain and 10 = excruciating pain. The data obtained at the 6 month time point were analyzed for an association between amount of peridural scars as measured by MR imaging and clinical failure as defined by the recurrence of radicular pain. The results showed that the probability of recurrent pain increases when scar score increases. Patients having extensive peridural scar were 3.2 times more likely to experience recurrent radicular pain than those patients with less extensive peridural scarring. In conclusion, this prospective, controlled, randomized, blinded, multicenter study has demonstrated that there is a significant association between the presence of extensive peridural scar and the occurrence of recurrent radicular pain.

Nonparametric analysis of clustered ROC curve data.

Current methods for estimating the accuracy of diagnostic tests require independence of the test results in the sample. However, cases in which there are multiple test results from the same patient are quite common. In such cases, estimation and inference of the accuracy of diagnostic tests must account for intracluster correlation. In the present paper, the structural components method of DeLong, DeLong, and Clarke-Pearson (1988, Biometrics 44, 837-844) is extended to the estimation of the Receiver Operating Characteristics (ROC) curve area for clustered data, incorporating the concepts of design effect and effective sample size used by Rao and Scott (1992, Biometrics 48, 577-585) for clustered binary data. Results of a Monte Carlo simulation study indicate that the size of statistical tests that assume independence is inflated in the presence of intracluster correlation. The proposed method, on the other hand, appropriately handles a wide variety of intracluster correlations, e.g., correlations between true disease statuses and between test results. In addition, the method can be applied to both continuous and ordinal test results. A strategy for estimating sample size requirements for future studies using clustered data is discussed.

Assessing spectral algorithms to predict atherosclerotic plaque composition with normalized and raw intravascular ultrasound data.

Spectral analysis of backscattered intravascular ultrasound (IVUS) data has demonstrated the ability to characterize plaque. We compared the ability of spectral parameters (e.g., slope, midband fit and y-intercept), computed via classic Fourier transform (CPSD), Welch power spectrum (WPSD) and autoregressive (MPSD) models, to classify plaque composition. Data were collected ex vivo from 32 human left anterior descending coronary arteries. Regions-of-interest (ROIs), selected from histology, comprised 64 collagen-rich, 24 fibrolipidic, 23 calcified and 37 calcified-necrotic regions. A novel quantitative method was used to correlate IVUS data with corresponding histologic sections. Periodograms of IVUS samples, identified for each ROI, were used to calculate spectral parameters. Statistical classification trees (CT) were computed with 75% of the data for plaque characterization. The remaining data were used to assess the accuracy of the CTs. The overall accuracies for normalized spectra with CPSD, WPSD and MPSD were, respectively, 84.7%, 85.6% and 81.1% (training data) and 54.1%, 64.9% and 37.8% (test data). These numbers were improved to 89.2%, 91.9% and 89.2% (training) and 62.2%, 73% and 59.5% (test) when the calcified and calcified-necrotic regions were combined for analysis. Most CTs misclassified a few fibrolipidic regions as collagen, which is histologically acceptable, and the unnormalized and normalized spectra results were similar.

Quantitative classification of breast tumors in digitized mammograms.

The goal of this study was to develop a technique to distinguish benign and malignant breast lesions in secondarily digitized mammograms. A set of 51 mammograms (two views/patient) containing lesions of known pathology were evaluated using six different morphological descriptors: circularity, mu R/sigma R (where mu R = mean radial distance of tumor boundary, sigma R = standard deviation); compactness, P2/A (where P = perimeter length of tumor boundary and A = area of the tumor); normalized moment classifier; fractal dimension; and a tumor boundary roughness (TBR) measurement (the number of angles in the tumor boundary with more than one boundary point divided by the total number of angles in the boundary). The lesion was segmented from the surrounding background using an adaptive region growing technique. Ninety-seven percent of the lesions were segmented using this approach. An ROC analysis was performed for each parameter and the results of this analysis were compared to each other and to those obtained from a subjective review by two board-certified radiologists who specialize in mammography. The results of the analysis indicate that all six parameters are diagnostic for malignancy with areas under their ROC curves ranging from 0.759 to 0.928. We observed a trend towards increased specificity at low false-negative rates (0.01 and 0.001) with the TBR measurement. Additionally, the diagnostic accuracy of a classification model based on this parameter was similar to that of the subjective reviewers.

On the comparison of correlated proportions for clustered data

McNemars test is often used to compare two proportions estimated from paired observations. We propose a method extending this to the case where the observations are sampled in clusters. The proposed method is simple to implement and makes no assumptions about the correlation structure. We conducted a Monte Carlo simulation study to compare the size and power of the proposed method with a test developed earlier by Eliasziw and Donner. In the presence of intracluster correlation, the size of McNemars test can greatly exceed the nominal level. The size of Eliasziw and Donners test is also inflated for some correlation patterns. The proposed method, on the other hand, is close to the nominal size for a variety of correlation patterns, although it is slightly less powerful than Eliasziw and Donners procedure. The proposed method is a good alternative to Eliasziw and Donners test when, in practice, little is known about the correlation pattern of the data.

Sample size calculations in studies of test accuracy.

Methods for determining sample size for studies of the accuracy of diagnostic tests are reviewed. Several accuracy indices are considered, including sensitivity and specificity, the full and partial area under the receiver operating characteristic curve, the sensitivity at a fixed false positive rate, and the likelihood ratio. Sample size formulae are presented for studies evaluating a single test and studies comparing the accuracy of tests. Four real examples illustrate the concepts involved in sample size determination. Lastly, various study design issues are discussed, such as sampling methods, choices in format for the test results, and the issue of replicated readings.

Contrast-to-Noise Ratio and Low-Contrast Object Resolution on Full- and Low-Dose MDCT: SAFIRE Versus Filtered Back Projection in a Low-Contrast Object Phantom and in the Liver

OBJECTIVE The purpose of this article is to evaluate the effect of sinogram-affirmed iterative reconstruction (SAFIRE) on contrast-to-noise ratio (CNR) compared with filtered back projection (FBP) and to determine whether SAFIRE improves low-contrast object detection or conspicuity in a low-contrast object phantom and in the liver on full- and low-dose examinations. SUBJECTS AND METHODS A low-contrast object phantom was scanned at 100%, 70%, 50%, and 30% dose using a single-source made of a dual-source MDCT scanner, with the raw data reconstructed with SAFIRE and FBP. Unenhanced liver CT scans in 22 patients were performed using a dual-source MDCT. The raw data from both tubes (100% dose) were reconstructed using FBP, and data from one tube (50% dose) were reconstructed using both FBP and SAFIRE. CNR was measured in the phantom and in the liver. Noise, contrast, and CNR were compared using paired Student t tests. Six readers assessed sphere detection and conspicuity in the phantom and liver-inferior vena cava conspicuity in the patient data. The phantom and patient data were assessed using multiple-variable logistic regression. RESULTS The phantom at 70% and 50% doses with SAFIRE had decreased noise and increased CNR compared with the 100% dose with FBP. In the liver, the mean CNR improvement at 50% dose with SAFIRE compared with FBP was 31.4% and 88% at 100% and 50% doses, respectively (p < 0.001). Sphere object detection and conspicuity improved with SAFIRE (p < 0.001). However, smaller spheres were obscured on both FBP and SAFIRE images at lower doses. Liver-vessel conspicuity improved with SAFIRE over 50%-dose FBP in 67.4% of cases (p < 0.001), and versus 100%-dose FBP, improved in 38.6% of cases (p = 0.085). As a predictor for detection, CNR alone had a discriminatory ability (c-index, 0.970) similar to that of the model that analyzed dose, lesion size, attenuation difference, and reconstruction technique (c-index, 0.978). CONCLUSION Lower dose scans reconstructed with SAFIRE have a higher CNR. The ability of SAFIRE to improve low-contrast object detection and conspicuity depends on the radiation dose level. At low radiation doses, low-contrast objects are invisible, regardless of reconstruction technique.

Nonstress delayed-enhancement magnetic resonance imaging of the myocardium predicts improvement of function after revascularization for chronic ischemic heart disease with left ventricular dysfunction ☆

BACKGROUND The extent of myocardial scarring of the left ventricle (LV) is important in patients with chronic ischemic heart disease (CIHD). With delayed-enhancement magnetic resonance imaging (DE-MRI), scarred myocardium (hyper-enhanced) is easily distinguishable from viable (dark) myocardium. This investigation assessed the use of DE-MRI for predicting functional improvement after coronary artery bypass grafting (CABG) in patients with CIHD and significant LV dysfunction. METHODS The patient population (n = 29) with CIHD and LV dysfunction (ejection fraction 28% +/- 10%) underwent both DE-MRI, to delineate scarred regions before revascularization, and echocardiography (Echo), to assess segmental function before and after CABG (interval 188 +/- 57 days). Using a 16-segment model, LV myocardium was semiquantitatively analyzed for scarring based on DE-MRI and for improvements in resting function by pre- and post-CABG Echo. RESULTS Before CABG, 82% of targeted myocardial segments had abnormal contraction; 78% showed scarring, including 38% with greater than mild amounts (25%-100%). Normal contraction was found in 18% of segments before revascularization; scarred areas were identified in 42%, 84% of which had, at most, minimal amounts (0%-24%). Of segments with pre-CABG dysfunction, 82% with no evidence of scar recovered, compared to only 18% with > or =50% scarring. Amount of hyper-enhancement was a very good indicator of improvement of function, especially at the > or =50%/segment threshold; overall accuracy was 0.74 (95% CI 0.66-0.82, P <.001). CONCLUSIONS In patients with CIHD and significant LV dysfunction, DE-MRI can predict likelihood of functional improvement after revascularization.

Confidence intervals for the receiver operating characteristic area in studies with small samples

RATIONALE AND OBJECTIVES The authors performed this study to address two practical questions. First, how large does the sample size need to be for confidence intervals (CIs) based on the usual asymptotic methods to be appropriate? Second, when the sample size is smaller than this threshold, what alternative method of CI construction should be used? MATERIALS AND METHODS The authors performed a Monte Carlo simulation study where 95% CIs were constructed for the receiver operating characteristic (ROC) area and for the difference between two ROC areas for rating and continuous test results--for ROC areas of moderate and high accuracy--by using both parametric and nonparametric estimation methods. Alternative methods evaluated included several bootstrap CIs and CIs with the Student t distribution. RESULTS For the difference between two ROC areas, CIs based on the asymptotic theory provided adequate coverage even when the sample size was very small (20 patients). In contrast, for a single ROC area, the asymptotic methods do not provide adequate CI coverage for small samples; for ROC areas of high accuracy, the sample size must be large (more than 200 patients) for the asymptotic methods to be applicable. The recommended alternative (bootstrap percentile, bootstrap t, or bootstrap bias-corrected accelerated method) depends on the estimation approach, format of the test results, and ROC area. CONCLUSION Currently, there is not a single best alternative for constructing CIs for a single ROC area for small samples.