Dataset Information

Acute pancreatitis with gradient echo T2*-weighted magnetic resonance imaging.

ABSTRACT: BACKGROUND:To study gradient recalled echo (GRE) T2*-weighted imaging (T2*WI) for normal pancreas and acute pancreatitis (AP). METHODS:Fifty-one patients without any pancreatic disorders (control group) and 117 patients with AP were recruited. T2* values derived from T2*WI of the pancreas were measured for the two groups. The severity of AP was graded by the magnetic resonance severity index (MRSI) and the Acute Physiology and Chronic Healthy Evaluation II (APACHE II) scoring system. Logistic regression was used to analyze the relationship between the T2* values and AP severity. The usefulness of the T2* value for diagnosing AP and the relationship between the T2* values and the severity of AP were analyzed. RESULTS:On GRE-T2*WI, the normal pancreas showed a well-marinated and consistently homogeneous isointensity. Edematous AP, as well as the non-necrotic area in necrotizing AP, showed ill-defined but homogeneous signal intensity. AP with pancreatic hemorrhage showed a decreased T2* value and a signal loss on the signal decay curve. The T2* value of pancreas in the AP group was higher than that of the control group (t=-8.20, P<0.05). The T2* value tended to increase along with the increase in MRSI scores but not with the APACHE II scores (P>0.05). AP was associated with a one standard deviation increment in the T2* value (OR =1.37; 95% CI: 1.216-1.532). CONCLUSIONS:T2*WI demonstrates a few characteristics of the normal pancreas and AP, which could potentially be helpful for detecting hemorrhage, and contributes to diagnosing AP and its severity.

SUBMITTER: Tang MY

PROVIDER: S-EPMC4858464 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Acute pancreatitis with gradient echo T2*-weighted magnetic resonance imaging.

Tang Meng Yue MY Chen Tian Wu TW Huang Xiao Hua XH Li Xing Hui XH Wang Si Yue SY Liu Nian N Zhang Xiao Ming XM

Quantitative imaging in medicine and surgery 20160401 2

<h4>Background</h4>To study gradient recalled echo (GRE) T2*-weighted imaging (T2*WI) for normal pancreas and acute pancreatitis (AP).<h4>Methods</h4>Fifty-one patients without any pancreatic disorders (control group) and 117 patients with AP were recruited. T2* values derived from T2*WI of the pancreas were measured for the two groups. The severity of AP was graded by the magnetic resonance severity index (MRSI) and the Acute Physiology and Chronic Healthy Evaluation II (APACHE II) scoring syst ...[more]

PMID: 27190768

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Project description:ObjectiveTo explore the diagnostic value of radiomics model based on magnetic resonance T2-weighted imaging for predicting the recurrence of acute pancreatitis.MethodsWe retrospectively collected 190 patients with acute pancreatitis (AP), including 122 patients with initial acute pancreatitis (IAP) and 68 patients with recurrent acute pancreatitis (RAP). At the same time, the clinical characteristics of the two groups were collected. They were randomly divided into training group and validation group in the ratio of 7:3. One hundred thirty-four cases in the training group, including 86 cases of IAP and 48 cases of RAP. There were 56 cases in the validation group, including 36 cases of IAP and 20 cases of RAP. Least absolute shrinkage and selection operator (LASSO) were used for feature screening. Logistic regression was used to establish the radiomics model, clinical model and combined model for predicting AP recurrence. The predictive ability of the three models was evaluated by the area under the curve (AUC). The recurrence risk in patients with AP was assessed using the nomogram.ResultsThe AUCs of radiomics model in training group and validation group were 0.804 and 0.788, respectively. The AUCs of the combined model in the training group and the validation group were 0.833 and 0.799, respectively. The AUCs of the clinical model in training group and validation group were 0.677 and 0.572, respectively. The sensitivities of the radiomics model, combined model, and clinical model were 0.646, 0.691, and 0.765, respectively. The specificities of the radiomics model, combined model, and clinical model were 0.791, 0.828, and 0.590, respectively. There was no significant difference in AUC between the radiomics model and the combined model for predicting RAP (p = 0.067). The AUCs of the radiomics model and combined model were greater than those of the clinical model (p = 0.008 and p = 0.007, respectively).ConclusionsRadiomics features based on magnetic resonance T2WI could be used as biomarkers to predict the recurrence of AP, and radiomics model and combined model can provide new directions for predicting recurrence of acute pancreatitis.

Project description:ObjectivesThe aim of this study was to develop and verify a method to obtain good temporal resolution T2-weighted 4-dimensional (4D-T2w) magnetic resonance imaging (MRI) by using motion information from T1-weighted 4D (4D-T1w) MRI, to support treatment planning in MR-guided radiotherapy.Materials and methodsTen patients with primary non-small cell lung cancer were scanned at 1.5 T axially with a volumetric T2-weighted turbo spin echo sequence gated to exhalation and a volumetric T1-weighted stack-of-stars spoiled gradient echo sequence with golden angle spacing acquired in free breathing. From the latter, 20 respiratory phases were reconstructed using the recently developed 4D joint MoCo-HDTV algorithm based on the self-gating signal obtained from the k-space center. Motion vector fields describing the respiratory cycle were obtained by deformable image registration between the respiratory phases and projected onto the T2-weighted image volume. The resulting 4D-T2w volumes were verified against the 4D-T1w volumes: an edge-detection method was used to measure the diaphragm positions; the locations of anatomical landmarks delineated by a radiation oncologist were compared and normalized mutual information was calculated to evaluate volumetric image similarity.ResultsHigh-resolution 4D-T2w MRI was obtained. Respiratory motion was preserved on calculated 4D-T2w MRI, with median diaphragm positions being consistent with less than 6.6 mm (2 voxels) for all patients and less than 3.3 mm (1 voxel) for 9 of 10 patients. Geometrical positions were coherent between 4D-T1w and 4D-T2w MRI as Euclidean distances between all corresponding anatomical landmarks agreed to within 7.6 mm (Euclidean distance of 2 voxels) and were below 3.8 mm (Euclidean distance of 1 voxel) for 355 of 470 pairs of anatomical landmarks. Volumetric image similarity was commensurate between 4D-T1w and 4D-T2w MRI, as mean percentage differences in normalized mutual information (calculated over all respiratory phases and patients), between corresponding respiratory phases of 4D-T1w and 4D-T2w MRI and the tie-phase of 4D-T1w and 3-dimensional T2w MRI, were consistent to 0.41% ± 0.37%. Four-dimensional T2w MRI displayed tumor extent, structure, and position more clearly than corresponding 4D-T1w MRI, especially when mobile tumor sites were adjacent to organs at risk.ConclusionsA methodology to obtain 4D-T2w MRI that retrospectively applies the motion information from 4D-T1w MRI to 3-dimensional T2w MRI was developed and verified. Four-dimensional T2w MRI can assist clinicians in delineating mobile lesions that are difficult to define on 4D-T1w MRI, because of poor tumor-tissue contrast.

Project description:Background: Parkinson's disease (PD) is a neurodegenerative disease in which the neostriatum, including the caudate nucleus (CN) and putamen (PU), has an important role in the pathophysiology. However, conventional magnetic resonance imaging (MRI) lacks sufficient specificity to diagnose PD. Therefore, the study's aim was to investigate the feasibility of using a radiomics approach to distinguish PD patients from healthy controls on T2-weighted images of the neostriatum and provide a basis for the clinical diagnosis of PD. Methods: T2-weighted images from 69 PD patients and 69 age- and sex-matched healthy controls were obtained on the same 3.0T MRI scanner. Regions of interest (ROIs) were manually placed at the CN and PU on the slices showing the largest respective sizes of the CN and PU. We extracted 274 texture features from each ROI and then used the least absolute shrinkage and selection operator regression to perform feature selection and radiomics signature building to identify the CN and PU radiomics signatures consisting of optimal features. We used a receiver operating characteristic curve analysis to assess the diagnostic performance of two radiomics signatures in a training group and estimate the generalization performance in the test group. Results: There were no significant differences in the demographic and clinical characteristics between the PD patients and healthy controls. The CN and PU radiomics signatures were built using 12 and 7 optimal features, respectively. The performance of the two radiomics signatures to distinguish PD patients from healthy controls was good. In the training and test groups, the AUCs of the CN radiomics signatures were 0.9410 (95% confidence interval [CI]: 0.8986-0.9833) and 0.7732 (95% CI: 0.6292-0.9173), respectively, and the AUCs of the PU radiomics signature were 0.8767 (95% CI: 0.8066-0.9469) and 0.7143 (95% CI: 0.5540-0.8746), respectively. Vertl_GlevNonU_R appeared simultaneously in both the CN and PU radiomics signatures as an optimal feature. A t-test analysis revealed significantly higher levels of texture values of the CN and PU in the PD patients than healthy controls (P < 0.05). Conclusion: Neostriatum radiomics signatures achieved good diagnostic performance for PD and potentially could serve as a basis for the clinical diagnosis of PD.

Project description:BackgroundMyocardial fibrosis is a common hallmark of many diseases of the heart. Late gadolinium enhanced MRI is a powerful tool to image replacement fibrosis after myocardial infarction (MI). Interstitial fibrosis can be assessed indirectly from an extracellular volume fraction measurement using contrast-enhanced T1 mapping. Detection of short T2* species resulting from fibrotic tissue may provide an attractive non-contrast-enhanced alternative to directly visualize the presence of both replacement and interstitial fibrosis.ObjectiveTo goal of this paper was to explore the use of a T2*-weighted radial sequence for the visualization of fibrosis in mouse heart.MethodsC57BL/6 mice were studied with MI (n = 20, replacement fibrosis), transverse aortic constriction (TAC) (n = 18, diffuse fibrosis), and as control (n = 10). 3D center-out radial T2*-weighted images with varying TE were acquired in vivo and ex vivo (TE = 21 ?s-4 ms). Ex vivo T2*-weighted signal decay with TE was analyzed using a 3-component model. Subtraction of short- and long-TE images was used to highlight fibrotic tissue with short T2*. The presence of fibrosis was validated using histology and correlated to MRI findings.ResultsDetailed ex vivo T2*-weighted signal analysis revealed a fast (T2*fast), slow (T2*slow) and lipid (T2*lipid) pool. T2*fast remained essentially constant. Infarct T2*slow decreased significantly, while a moderate decrease was observed in remote tissue in post-MI hearts and in TAC hearts. T2*slow correlated with the presence of diffuse fibrosis in TAC hearts (r = 0.82, P = 0.01). Ex vivo and in vivo subtraction images depicted a positive contrast in the infarct co-localizing with the scar. Infarct volumes from histology and subtraction images linearly correlated (r = 0.94, P<0.001). Region-of-interest analysis in the in vivo post-MI and TAC hearts revealed significant T2* shortening due to fibrosis, in agreement with the ex vivo results. However, in vivo contrast on subtraction images was rather poor, hampering a straightforward visual assessment of the spatial distribution of the fibrotic tissue.

Dataset Information

Acute pancreatitis with gradient echo T2*-weighted magnetic resonance imaging.

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Acute pancreatitis with gradient echo T2*-weighted magnetic resonance imaging.

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