Improved detection of metastatic melanoma by T2*-weighted imaging.

BACKGROUND AND PURPOSE: The imaging features of metastatic melanomas are distinctive due to the presence of melanin and the propensity for hemorrhage. Both hemorrhage and melanin can produce T1-weighted hyperintensity and T2*-weighted signal intensity loss. We hypothesized that T2*-weighted images would improve detection of metastatic melanoma. METHODS: The T2* and T1 characteristics of 120 newly detected metastatic brain lesions from 31 patients with malignant melanoma were compared with those of 120 brain metastases from 23 patients with lung cancer. RESULTS: Melanoma metastases were 5 times more likely to demonstrate prominent T2*-related signal intensity loss (susceptibility effect) than were lung metastases (42% vs 8%; P < .01), and 4.5 times more likely to demonstrate T1 hyperintensity (55% vs 12%; P < .01). Patients with melanoma had lesions that were either hypointense on T2*-weighted images, hyperintense on T1 images, or both, in 71% (85/120), compared with 19% (23/120) of lung carcinoma metastases (P < .01). Melanoma lesions were 16 times more likely than lung cancer lesions to show combined T2* related signal intensity loss and T1 hyperintensity (P < .01). Remarkably, 8 melanoma lesions (7%) in 3 patients were detectable principally on the T2*-weighted sequences, whereas no lung cancer lesion was detected solely on susceptibility images. We found a direct correlation between melanin content and T1 hyperintensity but no correlation between T2* intensity and melanin. CONCLUSION: T2*-weighted images improve lesion detection in patients with melanoma metastases, and in conjunction with T1-weighted sequences, can suggest melanoma as the etiology of an intracranial mass. This sequence should be employed for evaluation of possible brain metastasis in patients without a known primary malignancy and in studies for melanoma staging.

Right-side aortic arch with aneurysm of aberrant left subclavian artery: MR imaging appearance.

Reports of aneurysms of the subclavian artery in both normal and anomalous aortic arches have been rare. The authors describe a patient with a right-side aortic arch and an aneurysm of the aberrant left subclavian artery, which, to the authors' knowledge, is a previously unreported association. At presentation, the aneurysm appeared as a calcified left superior mediastinal mass. Magnetic resonance imaging enabled preoperative diagnosis and guided surgical planning.

Three-dimensional image reconstruction for planning of a complex cardiovascular procedure.

A rare left subclavian artery aneurysm associated with a congenital arch anomaly was difficult to visualize using standard radiographic techniques. Three-dimensional computer imaging produced a clear depiction of this unusual anatomy and simplified the preoperative planning.

The impact of thoracic computed tomography in clinically staged T1, N0, M0 chest lesions.

We assessed the impact of thoracic computed tomography (CT) in 38 patients considered for thoracotomy for solitary pulmonary lesions characterized as T1, N0, M0 by clinical and roentgenographic staging. False-positive lymph nodes were identified by CT in four patients prompting additional surgical staging procedures in two cases. Two of three patients with false-negative clinical, roentgenographic, and CT findings had successful complete resections. The CT scan did not correctly advance the stage of, or alter the plan for, these lesions in any patient. We conclude that CT is not helpful in patients considered for diagnostic and therapeutic thoracotomy for clinical and roentgenographic T1, N0, M0 lesions.

Radiographic evaluation of chest-wall lesions.

Multiple imaging modalities are available today for the evaluation of the wide variety of pathologic processes that affect the chest wall. However, the evaluation of nearly all abnormalities still begins with conventional radiographs. Careful analysis of these films, along with the judicious use of chest fluoroscopy and conventional tomography, frequently can lead to the correct diagnosis without resorting to the more expensive modalities. However, the precise anatomic location and characterization of many lesions requires the cross-sectional imaging capabilities of CT or MRI. In the appropriate clinical settings, these newer modalities often yield important information that leads to a specific diagnosis or demonstrates the full extent of a disease process. They may also be helpful in providing anatomic localization of lesions for percutaneous biopsy or surgical planning.

Use of artificial intelligence for the preoperative diagnosis of pulmonary lesions.

The relatively new field of artificial intelligence has spawned a variety of techniques associated with computer-assisted diagnosis. These techniques have been applied to the diagnosis of pulmonary lesions, but previous reports have focused on medical rather than surgical populations and the results have been evaluated using only retrospective patient surveys. We used a Bayesian algorithm to develop a diagnostic computer model for prospectively evaluating patients undergoing thoracotomy for suspected pulmonary malignancy. Patients who had a preoperative diagnosis were not included. Preoperative clinical and radiographic parameters for 100 consecutive patients were prospectively entered into the diagnostic model, which then categorized the lesion as benign or malignant. The computer predictions agreed with the final histological diagnosis in 95 of the 100 patients. The sensitivity was 96% and the specificity was 89% for this prospective series. These results indicate that the computer-assisted diagnosis of pulmonary lesions may have a role in this clinical setting.

Leukemic infiltrates of the heart: CT findings.

Although primary cardiac tumors are rare, metastatic disease to the heart is not uncommon. This is particularly true of the leukemias. Because of increased patient survival, cardiac leukemic infiltrates may assume a larger role in the gamut of leukemic complications. We present a case of massive cardiac leukemic infiltrates in which CT was instrumental in diagnosis and patient management. Relevant pathologic and radiologic features are reviewed.

Bayesian statistical theory in the preoperative diagnosis of pulmonary lesions.

We used a computerized Bayesian algorithm to assist in the preoperative diagnosis of pulmonary lesions. One hundred consecutive patients who were undergoing exploratory thoracotomy for newly discovered pulmonary lesions were prospectively evaluated. The Bayesian model used a total of 44 preoperative clinical and roentgenographic factors to categorize the lesions as benign or malignant. The Bayesian algorithm correctly categorized 96 of the 100 lesions, thereby providing an accuracy of 96 percent. The sensitivity of the model was 98 percent and the specificity was 87 percent. All but two of the 85 malignant lesions were correctly categorized and 13 of the 15 benign lesions were correctly analyzed by the model. These results indicate that computer-assisted diagnosis using the Theorem of Bayes may provide valuable preoperative information for the management of selected patients.

Fiberoptic bronchoscopy combined with selective bronchography. A simplified technique.

Since bronchography is helpful in certain clinical settings, we describe a simplified method for performing selective bronchography in conjunction with fiberoptic bronchoscopy. Selected cases are presented which illustrate that this technique is easily performed, has minimal risk, and produces bronchograms of high quality.