Soft-copy mammographic readings with different computer-assisted detection cuing environments: preliminary findings.

PURPOSE: To assess the performance of radiologists in the detection of masses and microcalcification clusters on digitized mammograms by using different computer-assisted detection (CAD) cuing environments. MATERIALS AND METHODS: Two hundred nine digitized mammograms depicting 57 verified masses and 38 microcalcification clusters in 85 positive and 35 negative cases were interpreted independently by seven radiologists using five display modes. Except for the first mode, for which no CAD results were provided, suspicious regions identified with a CAD scheme were cued in all the other modes by using a combination of two cuing sensitivities (90% and 50%) and two false-positive rates (0.5 and 2.0 per image). A receiver operating characteristic study was performed by using soft-copy images. RESULTS: CAD cuing at 90% sensitivity and a rate of 0.5 false-positive region per image improved observer performance levels significantly (P < .01). As accuracy of CAD cuing decreased so did observer performances (P < .01). Cuing specificity affected mass detection more significantly, while cuing sensitivity affected detection of microcalcification clusters more significantly (P < .01). Reduction of cuing sensitivity and specificity significantly increased false-negative rates in noncued areas (P < .05). Trends were consistent for all observers. CONCLUSION: CAD systems have the potential to significantly improve diagnostic performance in mammography. However, poorly performing schemes could adversely affect observer performance in both cued and noncued areas.

Knowledge-based computer-aided detection of masses on digitized mammograms: a preliminary assessment.

The purpose of this work was to develop and evaluate a computer-aided detection (CAD) scheme for the improvement of mass identification on digitized mammograms using a knowledge-based approach. Three hundred pathologically verified masses and 300 negative, but suspicious, regions, as initially identified by a rule-based CAD scheme, were randomly selected from a large clinical database for development purposes. In addition, 500 different positive and 500 negative regions were used to test the scheme. This suspicious region pruning scheme includes a learning process to establish a knowledge base that is then used to determine whether a previously identified suspicious region is likely to depict a true mass. This is accomplished by quantitatively characterizing the set of known masses, measuring "similarity" between a suspicious region and a "known" mass, then deriving a composite "likelihood" measure based on all "known" masses to determine the state of the suspicious region. To assess the performance of this method, receiver-operating characteristic (ROC) analyses were employed. Using a leave-one-out validation method with the development set of 600 regions, the knowledge-based CAD scheme achieved an area under the ROC curve of 0.83. Fifty-one percent of the previously identified false-positive regions were eliminated, while maintaining 90% sensitivity. During testing of the 1,000 independent regions, an area under the ROC curve as high as 0.80 was achieved. Knowledge-based approaches can yield a significant reduction in false-positive detections while maintaining reasonable sensitivity. This approach has the potential of improving the performance of other rule-based CAD schemes.

The ability of helical CT to preoperatively stage endometrial carcinoma.

OBJECTIVE: This study evaluated helical CT as an imaging modality for preoperative staging of endometrial carcinoma. MATERIALS AND METHODS: Three radiologists retrospectively and independently reviewed the preoperative helical CT scans of 25 consecutive patients with endometrial carcinoma. The presence or absence of deep myometrial invasion and the presence or absence of cervical involvement were evaluated on helical CT and compared with pathologic findings at hysterectomy. RESULTS: Helical CT has a sensitivity of 83% and a specificity of 42% for the detection of deep myometrial invasion (stage IC). Helical CT has a sensitivity of 25% and a specificity of 70% for the detection of cervical involvement (state II). These results compare poorly with those of MR imaging (sensitivity 92%, specificity 90% for the detection of deep myometrial invasion; sensitivity 86%, specificity 97% for the detection of cervical involvement). CONCLUSION: Helical CT is insensitive and nonspecific compared with MR imaging for the preoperative staging of endometrial carcinoma. MR imaging remains the imaging modality of choice.

Use of preoperative MR imaging in the management of endometrial carcinoma: cost analysis.

PURPOSE: To compare the cost of magnetic resonance (MR) imaging and its ability to direct the use of lymph node dissection with the cost and ability of conventional surgery for the staging of endometrial carcinoma. MATERIALS AND METHODS: Preoperative MR images of 25 patients who underwent hysterectomy for endometrial carcinoma were retrospectively evaluated. MR imaging results were compared with those of intraoperative gross dissection of the uterus and final histopathologic examination. Medicare reimbursements for two scenarios were compared in each patient. In the MR imaging scenario, the necessity for lymph node dissection was based on MR imaging results and histologic findings at biopsy. In the actual scenario, lymph node dissection was performed at the surgeon's discretion on the basis of findings at gross dissection of the uterus and histologic examination at biopsy. RESULTS: The cost of the MR imaging scenario, as defined by Medicare reimbursements, was 1% ($1, 265/$148,500) less than that of the actual scenario. In the MR imaging scenario, all patients who required lymph node dissection received it, and 86% of the lymph node dissections performed were necessary. In the actual scenario, one necessary lymph node dissection was not performed, and only 31% of the lymph node dissections performed were necessary. CONCLUSION: Staging with MR imaging has costs and accuracy similar to those of the current method of staging with intraoperative gross dissection of the uterus. In addition, MR imaging decreases the number of unnecessary lymph node dissections.

Renal medullary cystic disease: assessment by MRI.

Medullary cystic disease is an important cause of renal failure in adolescent patients. Imaging plays a primary role in the diagnosis of this entity as cysts are characteristically seen in the renal medulla and corticomedullary junction with normal to small sized kidneys. Imaging studies that do not use intravenous contrast or ionizing radiation are particularly useful given the young age of these patients and presence of renal failure. In this case, we demonstrate the imaging findings of medullary cystic disease by MRI.