MRI versus bone scintigraphy. Evaluation for diagnosis and grading of stress injuries.

AIM: This study was set up to determine the value of magnetic resonance imaging (MRI) and bone scintigraphy (BS) for the diagnosis of stress injuries in athletes, and furthermore to assess reliability and prediction of healing time. PATIENTS, METHODS: Imaging data was analyzed retrospectively from 28 athletes who had received MRI and BS examinations for suspected stress injuries. MRI- and BS-data were rated by three specialists each in a blinded read, using a 5-point score (i.e. 0-4: inconspicuous to high-grade stress fracture). An interdisciplinary expert truth-panel set the reference standard. Standard statistical parameters, Fleiss' kappa (κ), and group comparisons were calculated. RESULTS: The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) for detection of stress injuries were 71.4%, 85.7%, 78.6%, 83.3% and, 75.0%, for MRI and 92.9%, 73.8%, 83.3%, 78.0% and, 91.2% for BS, respectively. Interobserver reliability for the diagnosis of a stress injury was κ = 0.9 for BS and κ = 0.85 for MRI. Mean healing times of mild (grades 1 and 2) and severe (grades 3 and 4) stress injuries were 88 days (d) versus 142d for BS and 57d versus 116d for MRI. No significant difference in healing time could be shown. CONCLUSIONS: MRI and BS reliably detect stress injuries. MRI is to be recommended as the primary imaging modality due to its potential for assessment of differential diagnoses and the lack of radiation exposure, the value of BS lies in the exclusion of stress fractures after inconclusive MRI examinations.

Gene profiling identifies genes specific for well-differentiated epithelial thyroid tumors.

Thyroid nodules are common. It would very helpful if genetic markers that can diagnose malignancy from fine needle aspiration samples were available. Few such markers has been thus identified and none are specific. Large panels of potential markers can be screened by microarray technology. Studies done to date have concentrated on single tumor types and thus provide no help in identifying tumor subtype specific markers. To that end we have studied gene profiles of 5 types of benign and malignant thyroid nodular tissue (multinodular goiter, follicular adenoma, papillary and follicular carcinomas). We have identified 195 genes whose differential expression clustered into clinically relevant groups. Twenty-eight genes were selected for further confirmation using real time quantitative polymerase chain reaction. Despite the differences in the microarray panels used, we confirmed the differential regulation of 12 genes previously reported in thyroid cancer, although we found the expression of several genes to be regulated in other histological tumor subtypes than originally described. We found, PCSK2, TRIB1, RAP1 GA1 to be specifically overexpressed in follicular cancer and S100A4 and GK2 in papillary carcinoma. SERP1, RNASE 2 and STATA5 were suppressed in papillary thyroid cancer. We have thus identified new potential markers specific to malignant thyroid tumors. It is apparent that a range of nodular thyroid tissue using large tumor sample numbers is necessary to establish robust markers for malignancy and to categorize tumors on the basis of small tumor samples.