Monitoring of plexiform neurofibroma in children and adolescents with neurofibromatosis type 1 by [<sup>18</sup>F]FDG‐PET imaging. Is it of value in asymptomatic patients?

Azizi, Amedeo A.; Slavc, Irene; Theisen, Benjamin E.; Rausch, Ivo; Weber, Michael; Happak, Wolfgang; Hojreh, Azadeh; Peyrl, Andreas; Amann, Gabriele; Benkoe, Thomas; Wadsak, Wolfgang; Kasprian, Gregor; Staudenherz, Anton; Hacker, Marcus; Traub‐Weidinger, Tatjana

doi:10.1002/pbc.26733

Cited by 39 publications

(34 citation statements)

References 52 publications

(107 reference statements)

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“…The ADC value has been widely used as a marker in soft tissue imaging, and its usage in MRI could represent cellularity in tissues and signify malignancy (18,20). Consistent with this, a study demonstrated serial whole-body 18 F-FDG-PET/CT as an efficient screening tool for the detection of early-stage MPNST in NF1 patients (21). Additionally, these whole-body imaging tools present doctors with information for surgeries.…”

Section: Discussionmentioning

confidence: 66%

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

et al. 2020

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Background: Because neurofibromatosis type I (NF1) is a cancer predisposition disease, it is important to distinguish between benign and malignant lesions, especially in the craniofacial area. Purpose: The purpose of this study is to improve effectiveness in the diagnostic performance in discriminating malignant from benign craniofacial lesions based on computed tomography (CT) using a Keras-based machine-learning model. Methods: The Keras-based machine learning technique, a neural network package in the Python language, was used to train the diagnostic model on CT datasets. Fifty NF1 patients with benign craniofacial neurofibromas and six NF1 patients with malignant peripheral nerve sheath tumors (MPNSTs) were selected as the training set. Three validation cohorts were used: validation cohort 1 (random selection of 90% of the patients in the training cohort), validation cohort 2 (an independent cohort of 9 NF1 patients with benign craniofacial neurofibromas and 11 NF1 patients with MPNST), and validation cohort 3 (eight NF1 patients with MPNST, not restricted to the craniofacial area). Sensitivity and specificity were tested using validation cohorts 1 and 2, and generalizability was evaluated using validation cohort 3. Results: A total of 59 NF1 patients with benign neurofibroma and 23 NF1 patients with MPNST were included. A Keras-based machine-learning model was successfully established using the training cohort. The accuracy was 96.99 and 100% in validation cohorts 1 and 2, respectively, discriminating NF1-related benign and malignant craniofacial lesions. However, the accuracy of this model was significantly reduced to 51.72% in the identification of MPNSTs in different body regions. Wei et al. AI Assists CT-Based NF1 Diagnosis Conclusion: The Keras-based machine learning technique showed the potential of robust diagnostic performance in the differentiation of craniofacial MPNSTs and benign neurofibromas in NF1 patients using CT images. However, the model has limited generalizability when applied to other body areas. With more clinical data accumulating in the model, this system may support clinical doctors in the primary screening of true MPNSTs from benign lesions in NF1 patients.

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Section: Discussionmentioning

confidence: 66%

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

et al. 2020

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“…Azizi et al [ 19 ] recently published a study comprising data on symptomatic and asymptomatic NF1 patients showing the value of FDG PET in the work-up of NF1 patients.…”

Section: Discussionmentioning

confidence: 99%

Does elevated glucose metabolism correlate with higher cell density in Neurofibromatosis type 1 associated peripheral nerve sheath tumors?

et al. 2017

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PurposeTo investigate whether elevated glucose metabolism in neurofibroma, determined by [F18]-FDG-PET, is correlated with cell density in MRI, as expressed through the apparent diffusion coefficient.Materials and methodsPatients diagnosed with neurofibromatosis type 1 and peripheral nerve sheath tumors (PNST) were enrolled in this prospective, IRB-approved study. After a single [F18]-FDG injection, patients consecutively underwent [F18]-FDG-PET/CT and [F18]-FDG-PET/MRI on the same day. Maximum and mean standardized uptake values (SUVmax, SUVmean) on [F18]-FDG-PET/CT and [F18]-FDG-PET/MRI were compared, and correlated with minimum and mean apparent diffusion coefficients (ADCmean, ADCmin).ResultsA total of 12 (6 male/6 female, mean age was 16.2 ± 5.2 years) patients were prospectively included and analyzed on a per-lesion (n = 39) basis. The SUVmean of examined PNST showed a moderate negative correlation with the ADCmean (r = -.441) and ADCmin (r = -.477), which proved to be statistically significant (p = .005 and p = .002). The SUVmax of the respective lesions, however, showed a weaker negative correlation for ADCmean (r: -.311) and ADCmin (r: -.300) and did not reach statistical significance (p = .054 and p = .057).Lesion-based correlation between [F18]-FDG-PET/MRI and [F18]-FDG-PET/CT showed a moderate correlation for SUVmax (r = .353; p = .027) and a strong one for SUVmean (r = .879; p = .001)). Patient-based liver uptake (SUVmax and mean) of [F18]-FDG-PET/MRI and [F18]-FDG-PET/CT were strongly positively correlated (r = .827; p < .001 and r = .721; p < .001) but differed significantly (p < .001).ConclusionsWe found a statistically significant, negative correlation between glucose metabolism and cell density in PNST. Thus, ADCmean and ADCmin could possibly add complimentary information to the SUVmax and SUVmean and may serve as a potential determinant of malignant transformation of PNST.

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“…FDG-PET/CT-guided percutaneous biopsy is an effective procedure and the most dependable approach for untimely detection of NF1-associated MPNST (16,17). Benign PNFs demonstrate low fludeoxyglucose (FDG) uptake, whereas MPNSTs depict moderate to high FDG accumulation.…”

Section: Imaging Evaluation Of Pnsts -Differentiation Of Benign and Mmentioning

confidence: 99%

New Frontiers in Therapy of Peripheral Nerve Sheath Tumors in Patients With Neurofibromatosis Type 1: Latest Evidence and Clinical Implications

et al. 2020

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Almost all individuals with neurofibromatosis type 1 (NF1) develop peripheral nerve sheath tumors (PNSTs), mainly benign neurofibromas, however about 10% of PNSTs will undergo transformation to malignant peripheral nerve sheath tumors (MPNSTs). Surgical treatment of PNSTs has traditionally been regarded as a standard approach. The availability of new agents that target specific molecular pathways involved in the pathogenesis of PNST has led to a number of clinical trials, which resulted in increased chances for better survival and quality of life. This review presents the latest evidence and clinical implications for new therapies of PNSTs in patients with NF1 emphasizing the potential benefit from the use of Ras/MAPK pathway inhibitors, immunotherapy, chemotherapy or radiation therapy. We present evaluation of current knowledge on available treatment modalities. Neurofibromatosis type 1 (NF1) is an autosomal dominant neurocutaneous disease affecting about 1 in 3500 people worldwide (1). The hallmark clinical features of NF1 include multiple café-au-lait macules, neurofibromas, intertriginous freckling, osseous lesions, Lisch nodules and optic pathway gliomas. The disorder is typified by the presence of multisystem tumors, which carries a high risk of malignant transformation (2, 3). Nearly 100% of individuals with NF1 develop benign peripheral nerve sheath tumors (BPNSTs) and in approximately 30-50% of them atypical and plexiform neurofibromas (PNFs) are found. In about 10% of NF1 patients, neurofibromas may undergo transformation to malignant peripheral nerve sheath tumors (MPNSTs), which are highly aggressive. The differentiation between atypical neurofibroma and low grade MPNST is probably the most challenging issue in the pathology of peripheral nerve sheath tumors (PNSTs), particularly in NF1 patients. Clinically, atypical tumors often develop as extensive, slowly growing neoplasms, and pain can be a characteristic feature (4, 5). The poor response to currently available therapies underlines the need for more effective, targeted treatment methods for NF1-associated PNSTs (6, 7). In this review, we analyzed the latest evidence and clinical implications of new therapies of PNSTs in patients with NF1 emphasizing the importance of patient risk stratification to identify those who are likely to benefit from the use of Ras/MAPK pathway inhibitors, immunotherapy, chemotherapy or radiotherapy. We also analyzed the limitations of administering these therapies to all individuals with NF1-associated PNSTs together with future perspectives. Methodology PubMed searches were performed to identify potentially clinically relevant English-language studies published in the last 15 years. The searches were based on a combination of indexed terms and free text terms ("peripheral nerve sheath tumors"

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Monitoring of plexiform neurofibroma in children and adolescents with neurofibromatosis type 1 by [¹⁸F]FDG‐PET imaging. Is it of value in asymptomatic patients?

Cited by 39 publications

References 52 publications

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

Does elevated glucose metabolism correlate with higher cell density in Neurofibromatosis type 1 associated peripheral nerve sheath tumors?

New Frontiers in Therapy of Peripheral Nerve Sheath Tumors in Patients With Neurofibromatosis Type 1: Latest Evidence and Clinical Implications

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Monitoring of plexiform neurofibroma in children and adolescents with neurofibromatosis type 1 by [18F]FDG‐PET imaging. Is it of value in asymptomatic patients?

Cited by 39 publications

References 52 publications

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

Computed Tomography–Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

Does elevated glucose metabolism correlate with higher cell density in Neurofibromatosis type 1 associated peripheral nerve sheath tumors?

New Frontiers in Therapy of Peripheral Nerve Sheath Tumors in Patients With Neurofibromatosis Type 1: Latest Evidence and Clinical Implications

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Monitoring of plexiform neurofibroma in children and adolescents with neurofibromatosis type 1 by [¹⁸F]FDG‐PET imaging. Is it of value in asymptomatic patients?