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Biomedical subjects

L W Nunes

Publications and source records attributed to L W Nunes.

12 recordsLinked to original sources
PubMed2001

Half-Fourier acquisition single-shot turbo spin echo imaging in the diagnosis of Morgagni hernia.

Magnetic resonance (MR) imaging with multi-planar, gated Half-Fourier Acquisition Single-Shot Turbo Spin-Echo (HASTE) imaging was performed to evaluate a woman with dysrhythmia. MR examination for right ventricular dysplasia revealed a Morgagni hernia. The HASTE images depicted well the diaphragmatic defect and the organs involved, yielding valuable diagnostic and pre-operative information. HASTE imaging may be beneficial in the evaluation of Morgagni hernia.

Female↗
PubMed2001

Diagnostic performance of trauma US in identifying abdominal or pelvic free fluid and serious abdominal or pelvic injury.

RATIONALE AND OBJECTIVES: This study assessed the ability of a six-point trauma ultrasound (US) evaluation (a) to identify the presence of free fluid in the abdomen or pelvis, with computed tomography (CT) and laparotomy used as diagnostic standards and (b) to predict the presence of abdominal or pelvic injury, particularly injury requiring surgical intervention. MATERIALS AND METHODS: Of 156 patients who underwent US evaluation for free fluid after sustaining blunt and penetrating trauma, 147 were entered into the prospective study and underwent follow-up CT and/or laparotomy (n = 79), in-hospital observation, or outpatient examination. RESULTS: The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of US for identifying abdominal or pelvic free fluid were 69%, 100%, 100%, 95%, and 95%, respectively. The corresponding values for predicting abdominal and pelvic injury on the basis of free fluid status alone were 57%, 99%, 80%, 96%, and 95%, respectively. Performing repeated US examinations in patients with deteriorating clinical status decreased the false-negative rate by 50%, increasing the sensitivity for free fluid detection to 85% and the negative predictive value to 97%. Similarly, the sensitivity and negative predictive value for detection of injury increased to 71% and 97%, respectively. A learning curve was also observed, with 67% of the false-negative findings occurring in the first 3 months of the 19-month study. CONCLUSION: A six-point trauma US evaluation can reliably identify abdominal and pelvic free fluid, which can be a reliable indicator of abdominal or pelvic injury. Scanning conditions must be optimized, and the approach to clinical management must be cautious.

Abdominal Injuries↗
PubMed2001

A combined architectural and kinetic interpretation model for breast MR images.

RATIONALE AND OBJECTIVES: The purpose of this study was to integrate contrast material kinetic and architectural data from magnetic resonance (MR) images and to assess the improvement in diagnostic accuracy. MATERIALS AND METHODS: MR imaging data from a diagnostic cohort of 100 patients (50 malignant and 50 benign cases) were analyzed. RESULTS: Qualitative classification of the enhancement curve was the most predictive kinetic feature. Receiver operating characteristic (ROC) curves were calculated for the architectural model alone and for the architectural model combined with the qualitative kinetic classification. The results demonstrated a statistically significant increase in ROC area (P = .03) of the combined model compared with that of the architectural model alone. CONCLUSION: The addition of qualitative classification of the time-signal intensity curve to an architectural interpretation model results in significant improvement in model performance as measured by the area under the ROC curve.

Breast Neoplasms↗
PubMed2001

Feasibility and profitability of a radiology department providing trauma US as part of a trauma alert team.

RATIONALE AND OBJECTIVES: The purpose of this study was to assess the feasibility and profitability of a radiology department providing a six-point trauma ultrasound (US) examination for abdominal or pelvic free fluid as part of a trauma alert team. MATERIALS AND METHODS: The study included 191 trauma alerts, which generated 156 US examinations. A radiologist and a departmental technologist carried beepers and responded to level I and II traumas. A departmental secretary or technologist recorded when the responding technologist exited and re-entered the department and if US was performed. If performed, the US examination evaluated the four abdominal and pelvic quadrants and the suprapubic and subxiphoid regions. For 64 patients, the responding technologist recorded the times of the trauma alert, emergency room arrival, US start and finish, and return to the radiology department. RESULTS: Median response, wait, scan duration, and return times were 2, 8, 5, and 7 minutes, respectively. Median costs for the technician, physician, archiving, transcription, and equipment were $8.17, $30.85, $0.97, $4.80, and $41.22, respectively. Reimbursement per examination averaged $110.60. Sensitivity analyses that varied the time spent (median vs mean), US non-use rate (10%-18%), and years of depreciation (5-7 years) yielded net results ranging from a $36.60 profit to a $6.12 loss per examination. CONCLUSION: A radiology department can profitably respond to trauma alerts and provide a six-point trauma US examination for free fluid.

Abdominal Injuries↗
PubMed2001

Update of breast MR imaging architectural interpretation model.

PURPOSE: To (a) validate a breast magnetic resonance (MR) interpretation model, (b) expand the tree-shaped prediction model to increase specificity without decreasing sensitivity, and (c) reevaluate the model's diagnostic performance. MATERIALS AND METHODS: Two hundred sixty-two new patients with palpable or mammographic abnormalities underwent MR imaging, and pathologic evaluation was performed. They were entered prospectively into the model, which yielded 454 patients in the construction (training) and validation (test) phases. Predictive values for previously published terminal nodes or branch points of the model were compared between the training and test data sets. Ductal enhancement morphology, regional enhancement micronodularity, regional enhancement degree, and focal mass T2 signal intensity were evaluated for model expansion. Diagnostic performance characteristics of the model were recalculated. RESULTS: For previously published nodes, absence of a lesion visible at MR imaging, smooth masses, lobulated masses with nonenhancing internal septations, and lobulated masses with minimal or no enhancement had negative predictive values (NPVs) for malignancy similar in both data sets (96% vs 99%, 100% vs 93%, 100% vs 98%, and 100% vs 100%). Irregular masses with internal septations (100% vs 0%) and spiculated masses with no or minimal enhancement (100% vs 50%) did not. Nonseptated enhancing lobulated masses with low T2 signal intensity were added as a benign terminal node (NPV, 100%). Mild regional enhancement (NPV, 92%) was added but not considered a terminal node. Sensitivity, specificity, NPV, positive predictive value, and accuracy of the expanded model were 96%, 80%, 96%, 78%, and 87%, respectively. CONCLUSION: Additional investigation yielded a slightly modified model, but the diagnostic performance characteristics remain high, similar to those originally published.

Adult↗
PubMed2001

Architectural-based interpretations of breast MR imaging.

Architectural features extracted from high spatial resolution MR images of the breast can help distinguish malignant from benign breast abnormalities and can help predict specific histopathologic diagnoses. Various breast pathologies consistently display certain MR architectural features. Individual architectural features have been incorporated into interpretation models that can improve the diagnostic performance of MR imaging over the use of individual features alone.

Breast Neoplasms↗
PubMed2000

Embolic stroke secondary to an aortic arch tumor--a case report.

An acute stroke from an aortic arch tumor is reported. These tumors are rare and have to be differentiated from atheromas. Aortic atheromas commonly present with embolic phenomena and occasionally as masses. Aortic tumors are more likely to produce obstructive phenomena, presenting as a coarctation or dissection. Magnetic resonance imaging with gadolinium can facilitate the diagnosis. A literature review of aortic masses and their diagnosis and treatment are presented.

Aorta, Thoracic↗
PubMed1997

Breast MR imaging: interpretation model.

PURPOSE: To develop an interpretation model based on architectural features of suspicious breast findings on magnetic resonance (MR) images. MATERIALS AND METHODS: One hundred ninety-two patients with mammographically visible or palpable findings underwent T1- and fat-saturated T2-weighted spin-echo and contrast agent-enhanced fat-saturated gradient-echo MR imaging. Patients underwent subsequent excisional biopsy for histopathologic confirmation. An interpretation model was constructed by using 98 cases and was tested prospectively and expanded by using 94 different cases. Sensitivity, specificity, predictive values, and receiver operating characteristic curves were computed for all models. RESULTS: Individual features with high predictive values were MR visibility, enhancement degree and pattern, focal mass border characteristics, and focal mass internal septations. Feature combinations with high negative predictive values for malignancy were absence of an MR-visible abnormality, focal masses with smooth borders, lobulated or irregular masses with nonenhancing internal septations, and focal masses with no (or minimal) enhancement. The validated- and revised-model performance characteristics were, respectively, as follows: sensitivity, 100% and 96%; specificity, 69% and 79%; positive predictive value, 75% and 76%; negative predictive value, 100% and 97%; and overall accuracy, 83% and 86%. CONCLUSION: An interpretation model that incorporates breast MR architectural features can achieve high sensitivity and improve specificity for diagnosing breast cancer.

Adult↗
PubMed1997

Diagnostic performance characteristics of architectural features revealed by high spatial-resolution MR imaging of the breast.

OBJECTIVE: Our objective was twofold: to determine which architectural features revealed by high spatial-resolution MR imaging of the breast contribute to diagnostic accuracy and to evaluate the diagnostic performance characteristics of those architectural features. MATERIALS AND METHODS: Eligible patients with suspicious mammographic or palpable findings or both underwent MR imaging. Ninety-three patients whose MR images revealed lesions that corresponded to the mammographically visible or palpable findings were included in the study. Patients were examined with sagittal T1-weighted spin-echo MR imaging, fat-saturated T2-weighted fast spin-echo MR imaging, and dynamically enhanced fat-saturated fast gradient-echo MR imaging. All patients underwent subsequent excisional biopsy or cyst aspiration. Lesions were identified initially by an experienced radiologist who was aware of the patient's clinical or mammographic information. Two radiologists who were unaware of the patients' histories and who had less experience in MR imaging of the breast then independently evaluated each lesion for the architectural-features and predicted each lesion's potential for malignancy. RESULTS: Architectural features that were highly predictive of benign disease included smooth or lobulated borders (97-100%), the absence of mass enhancement (100%), and enhancement that was less than the enhancement of surrounding breast fibroglandular tissue (93-100%). Nonenhancing internal septations were specific for the diagnosis of fibroadenoma. Architectural features that were highly predictive of malignant disease included spiculated borders (76-88%) and peripheral rim enhancement in the presence of central lesion enhancement (79-92%). CONCLUSION: Architectural features revealed by high spatial-resolution MR imaging of the breast can help distinguish benign from malignant disease.

Adult↗
PubMed1995

The normal prostate and periprostatic structures: correlation between MR images made with an endorectal coil and cadaveric microtome sections.

This pictorial essay illustrates the normal prostate and periprostatic structures seen on MR images obtained with an endorectal coil and correlates them with anatomic structures identified on serial microtome sections of a frozen human cadaver. The correlation shows that high-resolution MR imaging allows detailed visualization of normal anatomic structures. The ability to identify the normal anatomy and to recognize pathologic alterations provides valuable information concerning clinical decision making for both benign and malignant prostatic disease.

Aged↗
PubMedDate not supplied

Correlation of lesion appearance and histologic findings for the nodes of a breast MR imaging interpretation model.

An interpretation model for evaluating magnetic resonance (MR) images of the breast was constructed that allowed differentiation of benign from malignant palpable or mammographically visible abnormalities. Architectural features define each node of the model. Investigation was subsequently made of the histologic findings in individuals within each node and of the frequency with which each histologic finding manifested as a particular architectural feature to determine whether nodal location and specific histologic findings are mutually predictive. The strongest associations were found between fibrocystic change and smooth masses, fibroadenoma and lobulated masses with nonenhancing internal septations, invasive ductal carcinoma (with or without ductal carcinoma in situ [DCIS]) and enhancing irregular or spiculated masses, invasive tubular carcinoma or radial scar and spiculated masses, medullary or colloid carcinoma and enhancing lobulated masses, invasive lobular carcinoma and the absence of a focal mass, DCIS and ductal enhancement, and DCIS (with or without invasive ductal carcinoma) and regional enhancement. Nodal location and histologic findings proved to be mutually predictive within the model; that is, the nodal location of MR imaging features within the model can be used to predict histologic findings and vice versa.

Biopsy↗