Stewart, Shelby

With improved medical treatments, the prognosis for many malignancies has improved, and more patients are presenting for transplant evaluation with a history of treated cancer. Solid organ transplant (SOT) recipients with a prior malignancy are at higher risk of posttransplant recurrence or de novo malignancy, and they may require a cancer surveillance program that is individualized to their specific needs. There is a dearth of literature on optimal surveillance strategies specific to SOT recipients. A working group of transplant physicians and cancer-specific specialists met to provide expert opinion recommendations on optimal cancer surveillance after transplantation for patients with a history of malignancy. Surveillance strategies provided are mainly based on general population recurrence risk data, immunosuppression effects, and limited transplant-specific data and should be considered expert opinion based on current knowledge. Prospective studies of cancer-specific surveillance models in SOT recipients should be supported to inform posttransplant management of this high-risk population.

OBJECTIVEThis 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.METHODSThe 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.RESULTSA 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.CONCLUSIONSThis 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.