Imaging of spinal chordoma and benign notochordal cell tumor (BNCT) with radiologic pathologic correlation.

Benign notochordal cell tumor (BNCT) and chordoma are neoplasms of notochordal differentiation. BNCT represents notochordal rests, commonly an incidental lesion present in the spine in 19% of cadaveric specimens. BNCTs are often radiographically occult. CT of BNCT frequently reveals patchy sclerosis between areas of maintained underlying trabeculae. BNCT demonstrates marrow replacement on T1-weighted MR images with high signal intensity on T2-weighting. BNCTs are frequently smaller than 35 mm and lack significant enhancement, bone destruction, cortical permeation, or soft tissue components. Biopsy or surgical resection of BNCT is usually not warranted, although imaging surveillance may be indicated. Chordoma is a rare low-grade locally aggressive malignancy representing 1-4% of primary malignant bone tumors. Chordoma is most frequent between the ages of 50-60 years with a male predilection. Clinical symptoms, while nonspecific and location dependent, include back pain, numbness, myelopathy, and bowel/bladder incontinence. Unfortunately, lesions are often large at presentation owing to diagnosis delay. Imaging of chordoma shows variable mixtures of bone destruction and sclerosis, calcification (50-70% at CT) and large soft tissue components. MR imaging of chordoma reveals multilobulated areas of marrow replacement on T1-weighting and high signal intensity on T2-weighting reflecting the myxoid component within the lesion and areas of hemorrhage seen histologically. Treatment of chordoma is primarily surgical with prognosis related to resection extent. Unfortunately, complete resection is often not possible (21-75%) resulting in high local recurrence incidence (19-75%) and a 5-year survival rate of 45-86%. This article reviews and illustrates the clinical characteristics, pathologic features, imaging appearance spectrum, treatment, and prognosis of BNCT and spinal chordoma.

Improving Radiology Report Quality by Rapidly Notifying Radiologist of Report Errors.

Radiology report errors occur for many reasons including the use of pre-filled report templates, wrong-word substitution, nonsensical phrases, and missing words. Reports may also contain clinical errors that are not specific to the speech recognition including wrong laterality and gender-specific discrepancies. Our goal was to create a custom algorithm to detect potential gender and laterality mismatch errors and to notify the interpreting radiologists for rapid correction. A JavaScript algorithm was devised to flag gender and laterality mismatch errors by searching the text of the report for keywords and comparing them to parameters within the study's HL7 metadata (i.e., procedure type, patient sex). The error detection algorithm was retrospectively applied to 82,353 reports 4 months prior to its development and then prospectively to 309,304 reports 15 months after implementation. Flagged reports were reviewed individually by two radiologists for a true gender or laterality error and to determine if the errors were ultimately corrected. There was significant improvement in the number of flagged reports (pre, 198/82,353 [0.24%]; post, 628/309,304 [0.20%]; P = 0.04) and reports containing confirmed gender or laterality errors (pre, 116/82,353 [0.014%]; post, 285/309,304 [0.09%]; P < 0.0001) after implementing our error notification system. The number of flagged reports containing an error that were ultimately corrected improved dramatically after implementing the notification system (pre, 17/116 [15%]; post, 239/285 [84%]; P < 0.0001). We developed a successful automated tool for detecting and notifying radiologists of potential gender and laterality errors, allowing for rapid report correction and reducing the overall rate of report errors.