Dataset Information

Texture analysis of routine T2 weighted fat-saturated images can identify head and neck paragangliomas - A pilot study.

ABSTRACT: Purpose:To evaluate the role of the first and second-order texture parameters obtained from T2-weighted fat-saturated DIXON images in differentiating paragangliomas from other neck masses, and to develop a statistical model to classify them. Method:We retrospectively evaluated 38 paragangliomas, 18 nerve-sheath tumours and 14 other miscellaneous neck lesions obtained from an IRB approved study conducted between January 2016 and June 2019; using a composite gold standard of histopathology, cytology and DOTANOC PET CT (A total of 70 lesions in 63 patients). Fat-suppressed T2weighted-DIXON axial images were used. First and second-order texture-parameters were calculated from the original and filtered images. Feature selection using F-statistics and collinearity analysis provided 14 texture parameters for further analysis. Mann-Whitney-U test was used to compare between the groups and p-values were adjusted for multiple comparisons. ROC curve analysis was used to obtain optimal cut-offs. Results:A total of ten texture features were found to be significantly different between paragangliomas and non-paraganglioma lesions. Minimum from the histogram of grey levels was lower in paragangliomas with a cut off of ?113.462 obtaining 62.9 % sensitivity and 77.27 % specificity in differentiating paragangliomas from non-paragangliomas. Logistic regression model was trained (n-49) using forward feature selection, which when evaluated on the validation set(n-21)- obtained an AUC of 0.855(95 %CI, 0.633 to 0.968) with a positive likelihood ratio of 4.545 (95 %CI, 1.298-15.923) in differentiating paragangliomas from non-paragangliomas. Conclusion:Texture analysis of a routine imaging sequence can identify paragangliomas with high accuracy. Further development of texture analysis would enable better imaging workflow, resource utilisation and imaging cost reductions.

SUBMITTER: Ghosh A

PROVIDER: S-EPMC7498758 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Texture analysis of routine T2 weighted fat-saturated images can identify head and neck paragangliomas - A pilot study.

Ghosh Adarsh A Malla Soumya Ranjan SR Bhalla Ashu Seith AS Manchanda Smita S Kandasamy Devasenathipathy D Kumar Rakesh R

European journal of radiology open 20200913

<h4>Purpose</h4>To evaluate the role of the first and second-order texture parameters obtained from T2-weighted fat-saturated DIXON images in differentiating paragangliomas from other neck masses, and to develop a statistical model to classify them.<h4>Method</h4>We retrospectively evaluated 38 paragangliomas, 18 nerve-sheath tumours and 14 other miscellaneous neck lesions obtained from an IRB approved study conducted between January 2016 and June 2019; using a composite gold standard of histopa ...[more]

PMID: 32984446

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:PurposeThe use of magnetic resonance imaging (MRI) in radiotherapy treatment planning has rapidly increased due to its ability to evaluate patient's anatomy without the use of ionizing radiation and due to its high soft tissue contrast. For these reasons, MRI has become the modality of choice for longitudinal and adaptive treatment studies. Automatic segmentation could offer many benefits for these studies. In this work, we describe a T2-weighted MRI dataset of head and neck cancer patients that can be used to evaluate the accuracy of head and neck normal tissue auto-segmentation systems through comparisons to available expert manual segmentations.Acquisition and validation methodsT2-weighted MRI images were acquired for 55 head and neck cancer patients. These scans were collected after radiotherapy computed tomography (CT) simulation scans using a thermoplastic mask to replicate patient treatment position. All scans were acquired on a single 1.5 T Siemens MAGNETOM Aera MRI with two large four-channel flex phased-array coils. The scans covered the region encompassing the nasopharynx region cranially and supraclavicular lymph node region caudally, when possible, in the superior-inferior direction. Manual contours were created for the left/right submandibular gland, left/right parotids, left/right lymph node level II, and left/right lymph node level III. These contours underwent quality assurance to ensure adherence to predefined guidelines, and were corrected if edits were necessary.Data format and usage notesThe T2-weighted images and RTSTRUCT files are available in DICOM format. The regions of interest are named based on AAPM's Task Group 263 nomenclature recommendations (Glnd_Submand_L, Glnd_Submand_R, LN_Neck_II_L, Parotid_L, Parotid_R, LN_Neck_II_R, LN_Neck_III_L, LN_Neck_III_R). This dataset is available on The Cancer Imaging Archive (TCIA) by the National Cancer Institute under the collection "AAPM RT-MAC Grand Challenge 2019" (https://doi.org/10.7937/tcia.2019.bcfjqfqb).Potential applicationsThis dataset provides head and neck patient MRI scans to evaluate auto-segmentation systems on T2-weighted images. Additional anatomies could be provided at a later time to enhance the existing library of contours.

Dataset Information

Texture analysis of routine T2 weighted fat-saturated images can identify head and neck paragangliomas - A pilot study.

Publications

Texture analysis of routine T2 weighted fat-saturated images can identify head and neck paragangliomas - A pilot study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets