OBJECTIVE: This study aimed to define a set of clinicoradiological parameters with a high specificity for the diagnosis of intraneural perineurioma, obviating the need for operative tissue diagnosis. METHODS: The authors retrospectively reviewed MR images obtained in a large cohort of patients who underwent targeted fascicular biopsy and included only those patients for whom the biopsy yielded a diagnosis. Clinical and radiological findings were then tested for their ability to predict a tissue diagnosis of intraneural perineurioma. The authors propose a new set of diagnostic criteria, referred to as the Perineurioma Diagnostic Criteria. The sensitivity, specificity, positive predictive value, and negative predictive value of several clinicoradiological methods of diagnosis were compared. RESULTS: A total of 195 patients who underwent targeted fascicular biopsy were included in the cohort, of whom 51 had a tissue diagnosis of intraneural perineurioma. When the clinicoradiological methods used in this study were compared, the highest sensitivity (0.86), negative predictive value (0.95), and F1 score (0.88) were observed for the decision trees generated in C5.0 and rPart, whereas the highest specificity (1.0) and positive predictive value (1.0) were observed for the Perineurioma Diagnostic Criteria. CONCLUSIONS: This study identified clinical and radiological features that are associated with a diagnosis of perineurioma. The Perineurioma Diagnostic Criteria were determined to be the following: 1) no cancer history, 2) unifocal disease, 3) moderate to severe hyperintensity on T2-weighted MR images, 4) moderate to severe contrast enhancement, 5) homogeneous contrast enhancement, 6) fusiform shape, 7) enlargement of the involved nerves, and 8) age ≤ 40 years. Use of the Perineurioma Diagnostic Criteria obviates the need for tissue diagnosis when all of the criteria are satisfied.
OBJECTIVE: This study aimed to define a set of clinicoradiological parameters with a high specificity for the diagnosis of intraneural perineurioma, obviating the need for operative tissue diagnosis. METHODS: The authors retrospectively reviewed MR images obtained in a large cohort of patients who underwent targeted fascicular biopsy and included only those patients for whom the biopsy yielded a diagnosis. Clinical and radiological findings were then tested for their ability to predict a tissue diagnosis of intraneural perineurioma. The authors propose a new set of diagnostic criteria, referred to as the Perineurioma Diagnostic Criteria. The sensitivity, specificity, positive predictive value, and negative predictive value of several clinicoradiological methods of diagnosis were compared. RESULTS: A total of 195 patients who underwent targeted fascicular biopsy were included in the cohort, of whom 51 had a tissue diagnosis of intraneural perineurioma. When the clinicoradiological methods used in this study were compared, the highest sensitivity (0.86), negative predictive value (0.95), and F1 score (0.88) were observed for the decision trees generated in C5.0 and rPart, whereas the highest specificity (1.0) and positive predictive value (1.0) were observed for the Perineurioma Diagnostic Criteria. CONCLUSIONS: This study identified clinical and radiological features that are associated with a diagnosis of perineurioma. The Perineurioma Diagnostic Criteria were determined to be the following: 1) no cancer history, 2) unifocal disease, 3) moderate to severe hyperintensity on T2-weighted MR images, 4) moderate to severe contrast enhancement, 5) homogeneous contrast enhancement, 6) fusiform shape, 7) enlargement of the involved nerves, and 8) age ≤ 40 years. Use of the Perineurioma Diagnostic Criteria obviates the need for tissue diagnosis when all of the criteria are satisfied.
Authors: Michael Zhang; Elizabeth Tong; Sam Wong; Forrest Hamrick; Maryam Mohammadzadeh; Vaishnavi Rao; Courtney Pendleton; Brandon W Smith; Nicholas F Hug; Sandip Biswal; Jayne Seekins; Sandy Napel; Robert J Spinner; Mark A Mahan; Kristen W Yeom; Thomas J Wilson Journal: Neuro Oncol Date: 2022-04-01 Impact factor: 13.029
Authors: Avneesh Chhabra; Swati D Deshmukh; Amelie M Lutz; Jan Fritz; Darryl B Sneag; Bayan Mogharrabi; Mina Guirguis; Gustav Andreisek; Yin Xi; Shivani Ahlawat Journal: Skeletal Radiol Date: 2022-04-27 Impact factor: 2.128