PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-8 (8)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
Document Types
1.  Correlations between Functional Imaging Markers Derived from PET/CT and Diffusion-Weighted MRI in Diffuse Large B-Cell Lymphoma and Follicular Lymphoma 
PLoS ONE  2014;9(1):e84999.
Objectives
To investigate the correlations between functional imaging markers derived from positron emission tomography/computed tomography (PET/CT) and diffusion-weighted magnetic resonance imaging (DWI) in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). Further to compare the usefulness of these tumor markers in differentiating diagnosis of the two common types of Non-Hodgkin's lymphoma (NHL).
Materials and Methods
Thirty-four consecutive pre-therapy adult patients with proven NHL (23 DLBCL and 11 FL) underwent PET/CT and MRI examinations and laboratory tests. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and metabolic tumor burden (MTB) were determined from the PET/CT images. DWI was performed in addition to conventional MRI sequences using two b values (0 and 800 s/mm2). The minimum and mean apparent diffusion coefficient (ADCmin and ADCmean) were measured on the parametric ADC maps.
Results
The SUVmax correlated inversely with the ADCmin (r = −0.35, p<0.05). The ADCmin, ADCmean, serum thymidine kinase (TK), Beta 2-microglobulin (B2m), lactate dehydrogenase (LD), and C-reactive protein (CRP) correlated with both whole-body MTV and whole-body MTB (p<0.05 or 0.01). The SUVmax, TK, LD, and CRP were significantly higher in the DLBCL group than in the FL group. Receiver operating characteristic curve analysis showed that they were reasonable predictors in differentiating DLBCL from FL.
Conclusions
The functional imaging markers determined from PET/CT and DWI are associated, and the SUVmax is superior to the ADCmin in differentiating DLBCL from FL. All the measured serum markers are associated with functional imaging markers. Serum LD, TK, and CRP are useful in differentiating DLBCL from FL.
doi:10.1371/journal.pone.0084999
PMCID: PMC3893149  PMID: 24454777
2.  3D Texture Analysis Reveals Imperceptible MRI Textural Alterations in the Thalamus and Putamen in Progressive Myoclonic Epilepsy Type 1, EPM1 
PLoS ONE  2013;8(7):e69905.
Progressive myoclonic epilepsy type 1 (EPM1) is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA) to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA.
doi:10.1371/journal.pone.0069905
PMCID: PMC3726751  PMID: 23922849
3.  Comparison of Five Parathyroid Scintigraphic Protocols 
Objectives. We compared five parathyroid scintigraphy protocols in patients with primary (pHPT) and secondary hyperparathyroidism (sHPT) and studied the interobserver agreement. The dual-tracer method (99mTc-sestamibi/123I) was used with three acquisition techniques (parallel-hole planar, pinhole planar, and SPECT/CT). The single-tracer method (99mTc-sestamibi) was used with two acquisition techniques (double-phase parallel-hole planar, and SPECT/CT). Thus five protocols were used, resulting in five sets of images. Materials and Methods. Image sets of 51 patients were retrospectively graded by four experienced nuclear medicine physicians. The final study group consisted of 24 patients (21 pHPT, 3 sHPT) who had been operated upon. Surgical and histopathologic findings were used as the standard of comparison. Results. Thirty abnormal parathyroid glands were found in 24 patients. The sensitivities of the dual-tracer method (76.7–80.0%) were similar (P = 1.0). The sensitivities of the single-tracer method (13.3–31.6%) were similar (P = 0.625). All differences in sensitivity between these two methods were statistically significant (P < 0.012). The interobserver agreement was good. Conclusion. This study indicates that any dual-tracer protocol with 99mTc-sestamibi and 123I is superior for enlarged parathyroid gland localization when compared with single-tracer protocols using 99mTc-sestamibi alone. The parathyroid scintigraphy was found to be independent of the reporter.
doi:10.1155/2013/921260
PMCID: PMC3564434  PMID: 23431436
4.  Repeatability and variation of region-of-interest methods using quantitative diffusion tensor MR imaging of the brain 
BMC Medical Imaging  2012;12:30.
Background
Diffusion tensor imaging (DTI) is increasingly used in various diseases as a clinical tool for assessing the integrity of the brain’s white matter. Reduced fractional anisotropy (FA) and an increased apparent diffusion coefficient (ADC) are nonspecific findings in most pathological processes affecting the brain’s parenchyma. At present, there is no gold standard for validating diffusion measures, which are dependent on the scanning protocols, methods of the softwares and observers. Therefore, the normal variation and repeatability effects on commonly-derived measures should be carefully examined.
Methods
Thirty healthy volunteers (mean age 37.8 years, SD 11.4) underwent DTI of the brain with 3T MRI. Region-of-interest (ROI) -based measurements were calculated at eleven anatomical locations in the pyramidal tracts, corpus callosum and frontobasal area. Two ROI-based methods, the circular method (CM) and the freehand method (FM), were compared. Both methods were also compared by performing measurements on a DTI phantom. The intra- and inter-observer variability (coefficient of variation, or CV%) and repeatability (intra-class correlation coefficient, or ICC) were assessed for FA and ADC values obtained using both ROI methods.
Results
The mean FA values for all of the regions were 0.663 with the CM and 0.621 with the FM. For both methods, the FA was highest in the splenium of the corpus callosum. The mean ADC value was 0.727 ×10-3 mm2/s with the CM and 0.747 ×10-3 mm2/s with the FM, and both methods found the ADC to be lowest in the corona radiata. The CV percentages of the derived measures were < 13% with the CM and < 10% with the FM. In most of the regions, the ICCs were excellent or moderate for both methods. With the CM, the highest ICC for FA was in the posterior limb of the internal capsule (0.90), and with the FM, it was in the corona radiata (0.86). For ADC, the highest ICC was found in the genu of the corpus callosum (0.93) with the CM and in the uncinate fasciculus (0.92) with FM.
Conclusions
With both ROI-based methods variability was low and repeatability was moderate. The circular method gave higher repeatability, but variation was slightly lower using the freehand method. The circular method can be recommended for the posterior limb of the internal capsule and splenium of the corpus callosum, and the freehand method for the corona radiata.
doi:10.1186/1471-2342-12-30
PMCID: PMC3533516  PMID: 23057584
5.  Development of a Research Dedicated Archival System (TARAS) in a University Hospital 
Journal of Digital Imaging  2010;24(5):864-873.
Recent healthcare policies have influenced the manner in which patient data is handled in research projects, and the regulations concerning protected health information have become significantly tighter. Thus, new procedures are needed to facilitate research while protecting the confidentiality of patient data and ensuring the integrity of clinical work in the expanding environment of electronic files and databases. We have addressed this problem in a university hospital setting by developing the Tampere Research Archival System (TARAS), an extensive data warehouse for research purposes. This dynamic system includes numerous integrated and pseudonymized imaging studies and clinical data. In a pilot study on asthma patients, we tested and improved the functionality of the data archival system. TARAS is feasible to use in retrieving, analyzing, and processing both image and non-image data. In this paper, we present a detailed workflow of the implementation process of the data warehouse, paying special attention to administrative, ethical, practical, and data security concerns. The establishment of TARAS will enhance and accelerate research practice at Tampere University Hospital, while also improving the safety of patient information as well as the prospects for national and international research collaboration. We hope that much can be learned from our experience of planning, designing, and implementing a research data warehouse combining imaging studies and medical records in a university hospital.
doi:10.1007/s10278-010-9350-1
PMCID: PMC3180537  PMID: 21042830
PACS; Research PACS; Hospital information systems; Research Archival System; TARAS; Medical research; Large scale; Pseudonymization
6.  Effect of slice thickness on brain magnetic resonance image texture analysis 
Background
The accuracy of texture analysis in clinical evaluation of magnetic resonance images depends considerably on imaging arrangements and various image quality parameters. In this paper, we study the effect of slice thickness on brain tissue texture analysis using a statistical approach and classification of T1-weighted images of clinically confirmed multiple sclerosis patients.
Methods
We averaged the intensities of three consecutive 1-mm slices to simulate 3-mm slices. Two hundred sixty-four texture parameters were calculated for both the original and the averaged slices. Wilcoxon's signed ranks test was used to find differences between the regions of interest representing white matter and multiple sclerosis plaques. Linear and nonlinear discriminant analyses were applied with several separate training and test sets to determine the actual classification accuracy.
Results
Only moderate differences in distributions of the texture parameter value for 1-mm and simulated 3-mm-thick slices were found. Our study also showed that white matter areas are well separable from multiple sclerosis plaques even if the slice thickness differs between training and test sets.
Conclusions
Three-millimeter-thick magnetic resonance image slices acquired with a 1.5 T clinical magnetic resonance scanner seem to be sufficient for texture analysis of multiple sclerosis plaques and white matter tissue.
doi:10.1186/1475-925X-9-60
PMCID: PMC2970603  PMID: 20955567
7.  Texture analysis of MR images of patients with Mild Traumatic Brain Injury 
BMC Medical Imaging  2010;10:8.
Background
Our objective was to study the effect of trauma on texture features in cerebral tissue in mild traumatic brain injury (MTBI). Our hypothesis was that a mild trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection but could be detected with texture analysis (TA).
Methods
We imaged 42 MTBI patients by using 1.5 T MRI within three weeks of onset of trauma. TA was performed on the area of mesencephalon, cerebral white matter at the levels of mesencephalon, corona radiata and centrum semiovale and in different segments of corpus callosum (CC) which have been found to be sensitive to damage. The same procedure was carried out on a control group of ten healthy volunteers. Patients' TA data was compared with the TA results of the control group comparing the amount of statistically significantly differing TA parameters between the left and right sides of the cerebral tissue and comparing the most discriminative parameters.
Results
There were statistically significant differences especially in several co-occurrence and run-length matrix based parameters between left and right side in the area of mesencephalon, in cerebral white matter at the level of corona radiata and in the segments of CC in patients. Considerably less difference was observed in the healthy controls.
Conclusions
TA revealed significant changes in texture parameters of cerebral tissue between hemispheres and CC segments in TBI patients. TA may serve as a novel additional tool for detecting the conventionally invisible changes in cerebral tissue in MTBI and help the clinicians to make an early diagnosis.
doi:10.1186/1471-2342-10-8
PMCID: PMC3161385  PMID: 20462439
8.  Non-Hodgkin lymphoma response evaluation with MRI texture classification 
Background
To show magnetic resonance imaging (MRI) texture appearance change in non-Hodgkin lymphoma (NHL) during treatment with response controlled by quantitative volume analysis.
Methods
A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests.
Results
NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images.
Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue.
Conclusion
Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.
doi:10.1186/1756-9966-28-87
PMCID: PMC2711966  PMID: 19545438

Results 1-8 (8)