ArticleAcademic radiology2018
Volumetric MRI Analysis of Plexiform Neurofibromas in Neurofibromatosis Type 1: Comparison of Two Methods.
Article in Academic radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 22 citations in OpenAlex.
- Adult-onset multifocal retroperitoneal plexiform neurofibromas: a case report.Journal of medical case reports · 2026Article
- Neurofibromatosis type 1-plexiform neurofibromas: Integrating treatment across pediatric and adult populations.Neuro-oncology · 2026Review
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- Article
- Diagnosis and management of neurofibromatosis type 1 in Arabian Gulf Cooperation Council Region: challenges and recommendations.Frontiers in oncology · 2024Review
- Developing Semiautomated Methods to Measure Pre- and Postoperative Syrinx Volumes.Journal of clinical medicine · 2023Article
- Clinical Characteristics and Management of Children and Adults with Neurofibromatosis Type 1 and Plexiform Neurofibromas in Denmark: A Nationwide Study.Oncology and therapy · 2023Article
- Management of neurofibromatosis type 1-associated plexiform neurofibromas.Neuro-oncology · 2022Review
- Efficacy and Safety of Trametinib in Neurofibromatosis Type 1-Associated Plexiform Neurofibroma and Low-Grade Glioma: A Systematic Review and Meta-Analysis.Pharmaceuticals (Basel, Switzerland) · 2022Review
- [Progress in diagnosis and treatment of neurofibromatosis in children].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2022Review
- DINs: Deep Interactive Networks for Neurofibroma Segmentation in Neurofibromatosis Type 1 on Whole-Body MRI.IEEE journal of biomedical and health informatics · 2022Article
- Neurofibromatosis in the Era of Precision Medicine: Development of MEK Inhibitors and Recent Successes with Selumetinib.Current oncology reports · 2021Review
- Current status of MEK inhibitors in the treatment of plexiform neurofibromas.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2020Review
- MRI based volumetric measurements of vestibular schwannomas in patients with neurofibromatosis type 2: comparison of three different software tools.Scientific reports · 2020Article
- Tumor volume features predict survival outcomes for patients diagnosed with diffuse intrinsic pontine glioma.Neuro-oncology advancesArticle
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesPlexiform neurofibromas (PNs) are complex, histologically benign peripheral nerve sheath tumors that are challenging to measure by simple line measurements. Computer-aided volumetric segmentation of PN has become the recommended method to assess response in clinical trials directed at PN. Different methods for volumetric analysis of PN have been developed. The goal of this study is to test the level of agreement in volume measurements and in interval changes using two separate methods of volumetric magnetic resonance imaging analysis.
methodsThree independent volume measurements were performed on 15 PN imaged at three time-points using 3DQI software at Massachusetts General Hospital (MGH) and National Cancer Institute (NCI) and MEDx software at NCI.
resultsMedian volume differences at each time-point comparing MGH-3DQI and NCI-3DQI were -0.5, -4.2, and -19.9 mL; comparing NCI-3DQI and NCI-MEDx were -21.0, -47.0, and -21.0 mL; comparing MGH-3DQI and NCI-MEDx were -10.0, -70.3, and -29.9 mL. Median differences in percentage change over time comparing MGH-3DQI and NCI-3DQI were -1.7, 1.1, and -1.0%; comparing NCI-3DQI and NCI-MEDx were -2.3, 3.3, and -1.1%; comparing MGH-3DQI and NCI-MEDx were -0.4, 2.0, and -1.5%. Volume differences were <20% of the mean of the two measurements in 117 of 135 comparisons (86.7%). Difference in interval change was <20% in 120 of the 135 comparisons (88.9%), while disease status classification was concordant in 115 of 135 comparisons (85.2%).
conclusionsThe volumes, interval changes, and progression status classifications were in good agreement. The comparison of two volumetric analysis methods suggests no systematic differences in tumor assessment. A prospective comparison of the two methods is planned.
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