Dataset Information

Short-term follow-up MRI after unplanned resection of malignant soft-tissue tumours; quantitative measurements on dynamic contrast enhanced and diffusion-weighted MR images.

ABSTRACT: To determine the diagnostic availability of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MR images for evaluating residual tumours at short-term follow-up after unplanned excision of malignant soft-tissue tumours.From January 2013 to September 2014, 38 patients underwent first follow-up MRI, including DCE and DW imaging (DWI), within 3 months of unplanned malignant soft-tissue tumour excision. The presence or absence of definite nodule formation, focal fluid/haematoma collection, oedema and fascial thickening around or at tumour beds were evaluated using conventional MR images. The volume transfer constant between blood plasma and extracellular/extravascular space (EES) (Ktrans), rate constant between EES and blood plasma (Kep), volume of EES space per unit volume of tissue and initial area under the concentration curve (iAUC) values with time-concentration curve (TCC) plots were obtained on DCE images, and apparent diffusion coefficient (ADC) values were measured on ADC maps. All data were statistically analyzed.Of the 21 patients who underwent re-excision, 12 patients had a residual tumor and 9 did not. All conventional MRI variables, except definite nodule formation, were insignificantly related to the presence of residual tumour. However, ADC values were found to be significantly associated with the presence of residual tumour, as were the DCE MRI variables, Ktrans, Kep and iAUC. In particular, TCC pattern and Kep were most significantly associated with residual tumour.Additional DCE images may be useful for determining the presence of residual tumours in tumour beds during short-term follow-up after inadequate malignant soft-tissue tumour excision.The addition of DCE MRI and quantitative analysis of the images obtained might be useful for determining the presence of residual tumour in a tumour bed during short-term follow-up after inadequate excision of a malignant soft-tissue tumour, although DWI was also found to be helpful.

SUBMITTER: Kim JI

PROVIDER: S-EPMC5124805 | biostudies-other | 2016 Oct

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Short-term follow-up MRI after unplanned resection of malignant soft-tissue tumours; quantitative measurements on dynamic contrast enhanced and diffusion-weighted MR images.

Kim Jeung Il JI Lee In Sook IS Song You Seon YS Park Se Kyoung SK Choi Kyung-Un KU Song Jong Woon JW

The British journal of radiology 20160726 1066

<h4>Objective</h4>To determine the diagnostic availability of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MR images for evaluating residual tumours at short-term follow-up after unplanned excision of malignant soft-tissue tumours.<h4>Methods</h4>From January 2013 to September 2014, 38 patients underwent first follow-up MRI, including DCE and DW imaging (DWI), within 3 months of unplanned malignant soft-tissue tumour excision. The presence or absence of definite nodule formation, ...[more]

PMID: 27459249

Similar Datasets

Project description:PurposeThe purpose of this study was to evaluate the agreement between paraspinal muscle composition measurements obtained from fat-water images using % fat-signal fraction (%FSF) in comparison to those obtained from T2-weighted magnetic resonance images (MRI) using a thresholding method.MethodsA sample of 35 subjects (19 females, 16 males; 40.26 ± 11.3 years old) was selected from a cohort of patients with chronic low back pain (LBP). Axial T2-weighted and IDEAL (Lava-Flex, 2 echo sequence) fat and water MR images were obtained using a 3.0 Tesla GE scanner. Multifidus, erector spinae, and psoas major muscle composition measurements were acquired bilaterally at L4-L5 and L5-S1 using both imaging sequences and related measurement methods. All measurements were obtained by the same rater, with a minimum of 7 days between each method. Intra-class correlation coefficients (ICCs) were calculated to assess intra-rater reliability. Pearson Correlation and Bland-Altman 95% limits of agreement were used to assess the agreement between both measurement methods.ResultsThe intra-rater reliability was excellent for all measurements with ICCs varying between 0.851 and 0.997. Strong positive correlations indicating a strong relationship between composition measurements were obtained from fat-water and T2-weighted images for bilateral multifidus and erector spinae muscles at both spinal levels and the right psoas major muscle at L4-L5, with correlation coefficient r ranging between 0.67 and 0.92. Bland-Altman plots for bilateral multifidus and erector spinae muscles at both levels revealed excellent agreement between the two methods, however, systematic differences between both methods were evident for psoas major fat measurements.ConclusionOur findings suggest that utilizing fat-water and T2-weighted MR images are comparable for quantifying multifidus and erector spinae muscle composition but not of the psoas major. While this suggests that both methods could be used interchangeably for the multifidus and erector spinae, further evaluation is required to expand and confirm our findings to other spinal levels.

Project description:The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. In this paper, we adapt generative adversarial networks (GAN) to a new application: longitudinal image prediction of structural MRI in the first year of life. In contrast to existing medical image-to-image translation applications of GANs, where inputs and outputs share a very close anatomical structure, our task is more challenging as brain size, shape and tissue contrast vary significantly between the input data and the predicted data. Several improvements over existing GAN approaches are proposed to address these challenges in our task. To enhance the realism, crispness, and accuracy of the predicted images, we incorporate both a traditional voxel-wise reconstruction loss as well as a perceptual loss term into the adversarial learning scheme. As the differing contrast changes in T1w and T2w MR images in the first year of life, we incorporate multi-contrast images leading to our proposed 3D multi-contrast perceptual adversarial network (MPGAN). Extensive evaluations are performed to assess the qualityand fidelity of the predicted images, including qualitative and quantitative assessments of the image appearance, as well as quantitative assessment on two segmentation tasks. Our experimental results show that our MPGAN is an effective solution for longitudinal MR image data imputation in the infant brain. We further apply our predicted/imputed images to two practical tasks, a regression task and a classification task, in order to highlight the enhanced task-related performance following image imputation. The results show that the model performance in both tasks is improved by including the additional imputed data, demonstrating the usability of the predicted images generated from our approach.

Dataset Information

Short-term follow-up MRI after unplanned resection of malignant soft-tissue tumours; quantitative measurements on dynamic contrast enhanced and diffusion-weighted MR images.

Publications

Short-term follow-up MRI after unplanned resection of malignant soft-tissue tumours; quantitative measurements on dynamic contrast enhanced and diffusion-weighted MR images.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets