HDL associates with insulin resistance and beta-cell dysfunction in South Asian families at risk of type 2 diabetes.

OBJECTIVE: Dyslipidemia precedes type 2 diabetes (T2D) and worsens with increasing glucose intolerance. First degree relatives of T2D patients have an increased risk to develop dyslipidemia and glucose intolerance. The aim of the present study was to assess the relation between the development of dyslipidemia and glucose intolerance in first-degree relatives of T2D patients. RESEARCH DESIGN AND METHODS: Fasting lipoprotein profiles were determined by density gradient ultracentrifugation in T2D patients and their first-degree relatives (42 Caucasians and 33 South Asians), and in 29 normoglycemic controls from non-T2D families. Glucose tolerance, insulin sensitivity index (ISI) and insulin disposition index (DI) were assessed by an extended, frequently sampled oral glucose tolerance test (OGTT), and fractional insulin synthesis rate (FSR) was measured by 13C-leucine enrichment in urinary C-peptide during the OGTT. RESULTS: Of the first-degree relatives, 40, 16 and 19 had NGT, prediabetes and T2D, respectively. NGT family members had lower plasma HDL-cholesterol (HDLC) (1.34 ± 0.07 vs 1.58 ± 0.06 mmol/L; p = 0.015), HDL2-C (0.41 ± 0.05 vs 0.57 ± 0.05 mmol/L; p = 0.021) and HDL3-C (0.62 ± 0.03 vs 0.72 ± 0.02 mmol/L; p = 0.043) than controls. HDL2-C levels tended to decrease with increasing glucose intolerance state. In South Asians, buoyant LDL-C levels decreased with increasing glucose intolerance state (p = 0.006). In South Asian families, HDL-C correlated with both ISI and DI (ß 0.42; p = 0.04 and ß 0.53; p = 0.01, respectively), whereas HDL2-C and HDL3-C levels correlated with DI (ß 0.64; p = 0.002 and ß 0.57; p = 0.005, respectively). HDL2-C and plasma triglyceride correlated with FSR (ß 0.48; p = 0.033 and ß -0.50; p = 0.029, respectively). CONCLUSIONS: Low HDL2-C and HDL3-C levels are present in NGT first-degree relatives of T2D patients, and HDL2-C tend to decrease further with increasing glucose intolerance. In South Asian families HDL2-C and HDL3-C levels linked predominantly to deteriorating beta cell function.

Definition of the prostate in CT and MRI: a multi-observer study.

PURPOSE: To determine, in three-dimensions, the difference between prostate delineation in magnetic resonance (MR) and computer tomography (CT) images for radiotherapy treatment planning. PATIENTS AND METHODS: Three radiation oncologists, considered experts in the field, outlined the prostate without seminal vesicles both on CT, and axial, coronal, and sagittal MR images for 18 patients. To compare the resulting delineated prostates, the CT and MR scans were matched in three-dimensions using chamfer matching on bony structures. The volumes were measured and the interscan and interobserver variation was determined. The spatial difference between delineation in CT and MR (interscan variation) as well as the interobserver variation were quantified and mapped three-dimensionally (3D) using polar coordinates. A urethrogram was performed and the location of the tip of the dye column was compared with the apex delineated in CT and MR images. RESULTS: Interscan variation: CT volumes were larger than the axial MR volumes in 52 of 54 delineations. The average ratio between the CT and MR volumes was 1.4 (standard error of mean, SE: 0.04) which was significantly different from 1 (p < 0.005). Only small differences were observed between the volumes outlined in the various MR scans, although the coronal MR volumes were smallest. The CT derived prostate was 8 mm (standard deviation, SD: 6 mm) larger at the base of the seminal vesicles and 6 mm (SD 4 mm) larger at the apex of the prostate than the axial MRI. Similar figures were obtained for the CT and the other MRI scans. Interobserver variation: The average ratio between the volume derived by one observer for a particular scan and patient and the average volume was 0.95, 0.97, and 1.08 (SE 0.01) for the three observers, respectively. The 3D pattern of the overall observer variation (1 SD) for CT and axial MRI was similar and equal to 3.5 to 2.8 mm at the base of the seminal vesicles and 3 mm at the apex. CONCLUSION: CT-derived prostate volumes are larger than MR derived volumes, especially toward the seminal vesicles and the apex of the prostate. This interscan variation was found to be larger than the interobserver variation. Using MRI for delineation of the prostate reduces the amount of irradiated rectal wall, and could reduce rectal and urological complications.

Automatic registration of pelvic computed tomography data and magnetic resonance scans including a full circle method for quantitative accuracy evaluation.

The purpose of this study is to develop a method for registration of CT and MR scans of the pelvis with minimal user interaction and to obtain a means for objective quantification of the registration accuracy of clinical data without markers. CT scans were registered with proton density MR scans using chamfer matching on automatically segmented bone. A fixed threshold was used to segment CT, while morphological filters were used to segment MR. The method was tested with transverse and coronal MR scans of 18 patients and sagittal MR scans of 8 patients. The registration accuracy was estimated by comparing (triangulating) registrations of a single CT scan with MR in different orientations in a "full circle." For example, CT is first matched on transverse MR, next transverse MR is matched independently on coronal MR, and finally coronal MR is matched independently on CT. The product of the three transformations is the identity if all matching steps are perfect. Deviations from identity occur both due to random errors and due to some types of systematic errors. MR was registered on MR (to close the "circle") by minimization of rms voxel value differences. CT-MR registration takes about 1 min, including user interaction. The random error for CT-MR registration with transverse or coronal MR was 0.5 mm in translation and 0.4 degree in rotation (standard deviation) for each axis. A systematic registration error of about 1 mm was demonstrated along the MR frequency encoding direction, which is attributed to the chemical shift. In conclusion, the presented algorithm efficiently and accurately registers pelvic CT and MR scans on bone. The "full circle" method provides an estimate of the registration accuracy on clinical data.

The potential impact of CT-MRI matching on tumor volume delineation in advanced head and neck cancer.

PURPOSE: To study the potential impact of the combined use of CT and MRI scans on the Gross Tumor Volume (GTV) estimation and interobserver variation. METHODS AND MATERIALS: Four observers outlined the GTV in six patients with advanced head and neck cancer on CT, axial MRI, and coronal or sagittal MRI. The MRI scans were subsequently matched to the CT scan. The interobserver and interscan set variation were assessed in three dimensions. RESULTS: The mean CT derived volume was a factor of 1.3 larger than the mean axial MRI volume. The range in volumes was larger for the CT than for the axial MRI volumes in five of the six cases. The ratio of the scan set common (i.e., the volume common to all GTVs) and the scan set encompassing volume (i.e., the smallest volume encompassing all GTVs) was closer to one in MRI (0.3-0.6) than in CT (0.1-0.5). The rest volumes (i.e., the volume defined by one observer as GTV in one data set but not in the other data set) were never zero for CT vs. MRI nor for MRI vs. CT. In two cases the craniocaudal border was poorly recognized on the axial MRI but could be delineated with a good agreement between the observers in the coronal/sagittal MRI. CONCLUSIONS: MRI-derived GTVs are smaller and have less interobserver variation than CT-derived GTVs. CT and MRI are complementary in delineating the GTV. A coronal or sagittal MRI adds to a better GTV definition in the craniocaudal direction.

Effect of image artifacts, organ motion, and poor segmentation on the reliability and accuracy of three-dimensional chamfer matching.

Our objective was to investigate the influence of various image artifacts on three-dimensional chamfer matching. A number of artificial and natural artifacts (for instance, as a model for CT-MR matching) were introduced or suppressed in pairs of pelvic CT scans, and a perturbation study was used to determine reliability and accuracy in a well known ground truth situation. In general, chamfer matching is extremely robust against missing data, low resolution, and poor segmentation of the images. In the presence of artifacts, minimization of the average distance outperformed minimization of the root-mean-square distance. Outliers in the scan from which the point list is obtained must be avoided. For example, rotation of the femurs reduces CT-CT registration accuracy by 1-2 mm. The robustness of chamfer matching is confirmed by a limited perturbation study of CT-MR registration for the pelvic region. In conclusion, chamfer matching is extremely accurate and reliable if outliers are avoided in the scan from which the point list is derived, and the average distance is used as a cost function.

Interactive three dimensional inspection of patient setup in radiation therapy using digital portal images and computed tomography data.

PURPOSE: Presently, the majority of clinical tools to quantify deviations in patient setup during external beam radiotherapy is based on two-dimensional (2D) analysis of portal images. The purpose of this study is to develop a tool for the inspection of the patient setup in three dimensions (3D) and to validate its clinical advantage over methods based on 2D analysis in the presence of out-of-plane rotations. METHODS AND MATERIALS: We developed an interactive procedure to quantify the setup deviation of the patient in 3D. The procedure is based on fast computation of digitally reconstructed radiographs (DRRs) in two beam directions and comparison of these DRRs with corresponding portal images. The potential of the tool is demonstrated on three selected cases of prostate and parotid gland treatment where conventional 2D analysis produced inconsistent results. The measurements from 3D analysis are compared with those obtained from the 2D analysis. RESULTS: Despite application of an immobilization cast, two investigated parotid gland setups showed rotational deviations in 3D up to 3 degrees. Two-dimensional analysis of these deviations produced inconsistent results. Analysis of the selected prostate setup in 3D showed a rotational deviation of 7 degrees around the left-right axis, possibly causing displacement of the seminal vesicles toward the borders of the conformal boost fields. Using 2D analysis, this out-of-plane rotation was misinterpreted as a translation resulting in the failure to trigger the decision protocol to correct the setup after the first fraction. Using the 3D patient setup analysis procedure, an accuracy of the order of 1 mm and 1 degree (SD) could be obtained. The computation time of the interactive DRRs is of the order of 1 s on a 60 MHz PC. The complete interactive 3D analysis requires about 10 min. CONCLUSIONS: Quantification of the patient setup in 3D provides essential additional information in cases where conventional 2D analysis is inconsistent, e.g., in the presence of out-of-plane rotations or geometrical degeneracies. The speed and accuracy of the interactive 3D patient setup inspection are acceptable for use in offline clinical studies and analysis of problem cases.

Variation in volumes, dose-volume histograms, and estimated normal tissue complication probabilities of rectum and bladder during conformal radiotherapy of T3 prostate cancer.

PURPOSE: To determine the pattern of changes of rectum and bladder structures during conformal therapy of T3 prostate cancer and the impact of these changes on the accuracy of the dose-volume histograms (DVHs) and normal tissue complication probabilities (NTCPs) of these organs, based on the planning computed tomography (CT) scan only. METHODS AND MATERIALS: For 11 T3 prostate cancer patients treated with conformal therapy, three repeat CT scans were made in Weeks 2, 4, and 6 of the treatment. The bony anatomy was aligned with the planning CT scan, using three dimensional (3D) chamfer matching. The internal and external surfaces of rectum and bladder were contoured in each scan. Three volumes were calculated for each organ: solid organ (including filling), filling, and wall volume. DVHs and NTCPs were calculated for all structures. RESULTS: The solid organ and filling volumes varied considerably between patients and within a patient and they decreased with increasing treatment time. The largest patient variation was seen for patients with large initial filling volumes. The variations of rectum and bladder wall volumes during treatment were 9 and 17% (1 standard deviation (SD)), respectively, with no time trend. The changes of the high dose (> 80 and 90% of the prescribed dose) volumes of the rectum in response to rectum filling differences were proportional to the whole rectum volume changes. The variation of the high-dose rectum wall volume was relatively small (14%, 1 SD). As a result, the NTCPs of rectum and rectum wall were the same overall and the variation of the NTCPs during treatment was about 14% (1 SD) and not correlated with rectum filling. The variation of the high-dose bladder volumes (about 14%, 1 SD) was smaller than the variation of the whole bladder volumes (30%, 1 SD). The high-dose bladder wall volume decreased significantly due to wall distention as the bladder filling increased. As a result of this complex pattern, the variation of NTCPs of bladder (85%, 1 SD) and bladder wall (88%, 1 SD) during treatment was large and significantly correlated with bladder filling. CONCLUSIONS: The planning CT scan overestimates rectum and bladder filling during treatment. Furthermore, the variation of filling is so large that only the wall structures have relatively constant volumes during treatment. For the rectum wall, the DVHs and NTCPs, as estimated from the initial scan, are representative for the whole treatment, because no correlation was seen between these parameters and organ filling. For the bladder wall, however, such a correlation was present and consequently, the initial bladder wall DVHs and NTCPs can only be representative for the whole treatment, if the bladder filling can be kept reasonably constant during treatment.

Quantification of organ motion during conformal radiotherapy of the prostate by three dimensional image registration.

PURPOSE: Knowledge about the mobility of organs relative to the bony anatomy is of great importance when preparing and verifying conformal radiotherapy. The conventional technique for measuring the motion of an organ is to locate landmarks on the organ and the bony anatomy and to compare the distance between these landmarks on subsequent computerized tomography (CT) scans. The first purpose of this study is to investigate the use of a three dimensional (3D) image registration method based on chamfer matching for measurement of the location and orientation of the whole organ relative to the bony anatomy. The second purpose is to quantify organ motion during conformal therapy of the prostate. METHODS AND MATERIALS: Four CT scans were made during the course of conformal treatment of 11 patients with prostate cancer. With the use of a 3D treatment planning system, the prostate and seminal vesicles were contoured interactively. In addition, bladder and rectum were contoured and the volume computed. Next, the bony anatomy of subsequent scans was segmented and matched automatically on the first scan. The femora and the pelvic bone were matched separately to quantify motion of the legs. Prostate (and seminal vesicle) contours from the subsequent scans were matched on the corresponding contours of the first scan, resulting in the 3D rotations and translations that describe the motion of the prostate and seminal vesicles relative to the pelvic bone. RESULTS: Bone matching of two scans with about 50 slices of 256 x 256 pixels takes about 2 min on a workstation and achieves subpixel registration accuracy. Matching of the organ contours takes about 30 s. The accuracy in determining the relative movement of the prostate is 0.5 to 0.9 mm for translations (depending on the axis) and 1 degree for rotations (standard deviations). Because all organ contours are used for matching, small differences in delineation of the prostate, missing slices, or differences in slice distance have only a limited influence on the accuracy. Rotations of the femora and the pelvic bone are quantified with about 0.4 degree accuracy. A strong correlation was found between rectal volume and anterior-posterior translation and rotation around the left-right axis of the prostate. Consequently, these parameters had the largest standard deviations of 2.7 mm and 4.0 degrees. Bladder filling had much less influence. Less significant correlations were found between various leg rotations and pelvic and prostate motion. Standard deviations of the rotation angles of the pelvic bone were less than 1 degree in all directions. CONCLUSIONS: Using 3D image registration, the motion of organs relative to bony anatomy has been quantified accurately. Uncertainties in contouring and visual interpretation of the scans have a much smaller influence on the measurement of organ displacement with our new method than with conventional methods. We have quantified correlations between rectal filling, leg motions, and prostate motion.

Optimization of automatic portal image analysis.

The purpose of this study is to quantify and optimize the performance of an automatic portal image analysis procedure under clinical conditions and to compare the performance with that of human operators. A new method, based on analysis of variance, is introduced to quantify the clinical performance of portal image analysis tools in terms of systematic and random variations. The automatic portal image analysis procedure is based on chamfer matching. Two image enhancement techniques have been investigated in the automatic procedure: morphological top-hat (MTH) transformation and multiscale medial axis (MMA) transformation. The performance of these enhancements was quantified and optimized as a function of filter size using images obtained from clinical treatment. All images used for this study were obtained from pelvic treatment fields by means of an electronic portal imaging device. The random variations in the alignment of AP fields are typically 0.5 mm and 0.5 degrees (1 SD) for both the human operators and the optimized automatic analysis procedure. Random variations in the alignment of lateral pelvic fields are typically twice as large for all operators. MMA enhancement yields smaller random variations than MTH enhancement for lateral fields, but the differences are marginal for AP fields. The optimized automatic analysis procedure has a success rate ranging from 99% for AP large fields to 96% for lateral fields and 85% for AP boost fields. The accuracy of the method is comparable with the accuracy of the human operators for most investigated fields. For lateral boost fields and simultaneous boost fields, the random variations of the automatic analysis are typically two times larger than the variations of the human operators. Automatic analysis is 4 to 20 times faster than human operators yielding a large reduction in work load.