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- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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- Bouget, D., et al.
(author)
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Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting
- 2022
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In: Frontiers in Neurology. - : Frontiers Media SA. - 1664-2295. ; 13
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Journal article (peer-reviewed)abstract
- For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports.
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- Dellenmark-Blom, Michaela, 1983, et al.
(author)
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Establishment of a condition-specific quality-of-life questionnaire for children born with esophageal atresia aged 2-7 across 14 countries
- 2023
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In: Frontiers in Pediatrics. - 2296-2360. ; 11
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Journal article (peer-reviewed)abstract
- BackgroundEsophageal atresia (EA) is a rare congenital anomaly characterized by a discontinuity of the esophagus. Following surgical repair, survival rates have improved dramatically the past decenniums and today exceed 90%, but the children commonly present with esophageal and respiratory morbidity. In 2018, a condition-specific quality-of-life questionnaire for children with esophageal atresia (EA) aged 2-7 in Sweden-Germany was finalized (The EA-QOL questionnaire). The study aim was to describe the evaluation of the new translations across 12 new countries in Europe, Asia, Africa, Central-and North America.MethodsFollowing forward-backward translation into the new languages, the 17-item EA-QOL questionnaire was tested in cognitive debriefing interviews with parents of children with EA aged 2-7. Parents rated if each item was easy to understand (clarity) and sensitive to answer (interference with personal integrity). They could skip responding to a non-applicable/problematic item and give open comments. Predefined psychometric criteria were used; item clarity >= 80%/item sensitive to answer <= 20%/item feasibility <= 5% missing item responses. The decision to modify the translation was based on native expert, patient stakeholder, and instrument developer review, and the need for harmonization between translations.ResultsSimilar to findings in the Swedish-German cognitive debriefing, the cross-cultural analysis of input from 116 parents from 12 new countries (4-14 parents, median 9 parents/country) showed that all items in the EA-QOL questionnaire fulfilled the criteria for item clarity >= 80% and sensitive to answer (ranging from 1%-4.5%), although results varied between countries. Four items had missing responses between 5.2% and 13.4%, three within the same domain and were in line with parents' explanations. Poor translations and feasibility were improved.ConclusionsBased on parent input, the collaboration between native experts, patient stakeholders, and instrument developers, a linguistic version of the EA-QOL questionnaire for children aged 2-7 for use in and across 14 countries has been established. These efforts have set the conditions for a cross-cultural field test of the EA-QOL questionnaire and will open the doors for a new chapter in outcome research, registries, and clinical practice concerning children with EA. In the long-term, this will help increase knowledge of the disease's burden, promote patient-centeredness, exchange of information between nations, and strengthen evidence-based treatments for children born with EA.
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- Emblem, Kyrre E, et al.
(author)
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Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps.
- 2008
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In: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 247:3, s. 808-17
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Journal article (peer-reviewed)abstract
- PURPOSE: To retrospectively compare the diagnostic accuracy of an alternative method used to grade gliomas that is based on histogram analysis of normalized cerebral blood volume (CBV) values from the entire tumor volume (obtained with the histogram method) with that of the hot-spot method, with histologic analysis as the reference standard.MATERIALS AND METHODS: The medical ethics committee approved this study, and all patients provided informed consent. Fifty-three patients (24 female, 29 male; mean age, 48 years; age range, 14-76 years) with histologically confirmed gliomas were examined with dynamic contrast material-enhanced 1.5-T magnetic resonance (MR) imaging. CBV maps were created and normalized to unaffected white matter (normalized CBV maps). Four neuroradiologists independently measured the distribution of whole-tumor normalized CBVs and analyzed this distribution by classifying the values into area-normalized bins. Glioma grading was performed by assessing the normalized peak height of the histogram distributions. Logistic regression analysis and interobserver agreement were used to compare the proposed method with a hot-spot method in which only the maximum normalized CBV was used.RESULTS: For the histogram method, diagnostic accuracy was independent of the observer. Interobserver agreement was almost perfect for the histogram method (kappa = 0.923) and moderate for the hot-spot method (kappa = 0.559). For all observers, sensitivity was higher with the histogram method (90%) than with the hot-spot method (55%-76%).CONCLUSION: Glioma grading based on histogram analysis of normalized CBV heterogeneity is an alternative to the established hot-spot method, as it offers increased diagnostic accuracy and interobserver agreement.
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