Cause Of False-negative Findings Research Articles

Why treatment efficacy on breathlessness in laboratory but not daily life trials? The importance of standardized exertion.

Treatments for chronic breathlessness, including opioids and oxygen, have shown efficacy in the controlled laboratory setting, whereas effects have been inconsistent or absent in trials in daily life. This review discusses the lack of standardized exertion as a potential cause of false negative findings for breathlessness in daily life. The level of breathlessness can be modified by patients by changing their level of physical activity. Effects of opioids and oxygen have been shown at standardized level of exertion (iso-time) but not at the end of symptom-limited (peak) exertion. Trials in daily life reporting no effects on breathlessness did not standardize the exertion or employed insensitive methods, such as the 6-min walk test that should not be used for measuring breathlessness. Novel tests - the 3-min walk and stepping tests have been validated in chronic obstructive pulmonary disease and are responsive for measuring change in breathlessness. Breathlessness should be measured at standardized exertion, otherwise treatment effects may be biased or overlooked. Tests for valid measurement of breathlessness in clinical practice and daily life are available and emerging.

The predictive value of Cardiodynamicsgram in myocardial perfusion abnormalities.

Myocardial perfusion abnormalities are the first sign of the ischemic cascade in the development of coronary artery disease (CAD). Thus, the early detection of myocardial perfusion abnormalities is significant for the prevention of CAD. Recently, a novel noninvasive method named Cardiodynamicsgram (CDG) has been proposed for early detection of CAD. This study aims to evaluate the predictive value of CDG in myocardial perfusion abnormalities for suspected ischemic heart disease. In the study, 86 suspected patients were enrolled. Standard 12-lead ECG and CDG were performed simultaneously before single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Diagnostic accuracy of CDG for myocardial perfusion abnormalities detection is assessed using SPECT MPI as the reference standard. Of these 86 suspected patients, 37 patients were positive in CDG, 49 patients were negative in CDG. Diagnostic accuracy of CDG at presentation for myocardial perfusion abnormalities was 84.9%, sensitivity 84.0%, and specificity 89.4%. Furthermore, of the 10 patients whose SPECT MPI results are reverse redistribution, 9 patients were positive in CDG. Underlying causes of false positive CDG findings included the factors that can change the stability of cardiac electrical conduction and measurement noise. Myocardial remodeling in patients with old myocardial infarction might be the major cause of false negative findings. Results show a good consistency between the CDG and SPECT MPI in evaluating myocardial perfusion abnormalities. It suggests that CDG might be used as a cost-effective tool for assessing the myocardial perfusion abnormalities in the clinic.

Diagnostic accuracy of 18F-2-deoxy-fluoro-D-glucose positron emission tomography for pn2 lymph nodes in patients with lung cancer

The accuracy of (18)F-2-deoxy-fluoro-D-glucose positron emission tomography (FDG-PET) for diagnosing nodal status in patients with lung cancer was initially reported as excellent, but, with increasing experience, the problem of false-positive and false-negative assessments has been observed. To evaluate the accuracy of FDG-PET for diagnosing nodal status in lung cancer patients with pathologically proven N2 lymph nodes and compare it with that of computed tomography (CT). Nineteen pN2 patients (13 males and six females) with primary lung cancer undergoing preoperative CT and FDG-PET were investigated. Lymph nodes were considered to be positive when uptake higher than the surrounding mediastinal level was visually observed. Slight symmetrical mediastinal uptake was considered to be negative, representing benign physiological accumulation. Radiological and pathological correlation was investigated, and the association between FDG accumulation and the size of metastatic lymph nodes and metastatic lesions was evaluated. Of the 19 patients, nodal stage determined by using FDG-PET was cN0 in four (21%) cases, cN1 in three (16%), cN2 in nine (47%), and cN3 in three (16%). On CT, nodal stage was cN0 in three (16%) cases, cN1 in seven (37%), cN2 in eight (42%), and cN3 in one (5%). Thus, FDG-PET provided correct N-staging in 47%, under-staging in 37%, and overstaging in 16%. CT staging was correct in 42%, underestimated in 53%, and overestimated in 5%. The maximum area of metastatic foci was 15.8 +/-21.3 mm(2) (mean +/- SD) in false-negative nodes and 75.0+/-56.3 mm(2) in true-positive nodes (P<0.0001). Diagnostic accuracy of FDG-PET (47%) was low and similar to that of CT (42%). The possibility of false-negative as well as false-positive findings should be recognized in interpreting PET images. Micrometastasis appeared to be the greatest cause of false-negative findings.

Computer-aided detection of architectural distortion in prior mammograms of interval cancer.

Architectural distortion is an important sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. This paper presents methods for the detection of architectural distortion in mammograms of interval cancer cases taken prior to the detection of breast cancer using Gabor filters, phase portrait analysis, fractal analysis, and texture analysis. The methods were used to detect initial candidates for sites of architectural distortion in prior mammograms of interval cancer and also normal control cases. A total of 4,224 regions of interest (ROIs) were automatically obtained from 106 prior mammograms of 56 interval cancer cases, including 301 ROIs related to architectural distortion, and from 52 prior mammograms of 13 normal cases. For each ROI, the fractal dimension and Haralick's texture features were computed. Feature selection was performed separately using stepwise logistic regression and stepwise regression. The best results achieved, in terms of the area under the receiver operating characteristics curve, with the features selected by stepwise logistic regression are 0.76 with the Bayesian classifier, 0.73 with Fisher linear discriminant analysis, 0.77 with an artificial neural network based on radial basis functions, and 0.77 with a support vector machine. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.80 at 7.6 false positives per image. The methods have good potential in detecting architectural distortion in mammograms of interval cancer cases.

Novel method for detecting mammographic architectural distortion based on concentration of mammary gland

Architectural distortion is a common cause of false-negative findings on screening mammograms because of its subtlety and potential for malignancy. We have developed the detection algorithm for distorted area with focal retraction around skinline in order to aid physicians with diagnosis. The purpose of our study is to suggest the automated detection method for another architectural distortion within mammary gland. The distributions of mammary gland are approximated to linear structures. Those directions are toward the nipple within normal breast, whereas those within abnormal breast are toward the suspect area. First, the linear structures of mammary gland are extracted by the mean curvature. The suspect area is then determined by concentration index. Finally, the false positives are reduced by the discriminant analysis by using size, mean isotropy index, mean pixel value, contrast, and four features calculated by the power spectrum. Our image database consists of 41 cases with architectural distortions within mammary glands. As a result, the sensitivity was 80% with 0.9 false positives per image. It was concluded that our detection method would be effective.

Localized form of bronchioloalveolar carcinoma: FDG PET findings.

The aim of our study was to describe 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) findings of a localized form of bronchioloalveolar carcinoma and to compare those findings with other cell types of lung cancer. FDG PET was performed in 48 patients with lung cancer. The patients had carcinomas of various cell types: bronchioloalveolar carcinoma (n = 9), squamous cell carcinoma (n = 11), adenocarcinoma (n = 22), and other cell types (n = 6). Using FDG PET, we compared peak standardized uptake values among the various cell types of lung cancer. CT and pathologic findings for patients with bronchioloalveolar carcinoma were also reviewed. Overall, 48 malignant tumors showed a mean peak standardized uptake value of 8.0 +/- 4.1. The mean peak standardized uptake value was 3.5 +/- 2.2 for bronchioloalveolar carcinoma, 10.8 +/- 4.4 for squamous cell carcinoma, and 8.8 +/- 3.2 for adenocarcinoma. The mean peak standardized uptake value for bronchioloalveolar carcinoma was significantly lower than that for adenocarcinoma and squamous cell carcinoma (p < .001). On high-resolution CT scans, bronchioloalveolar carcinomas appeared as areas of ground-glass opacity (n = 4), as nodules (n = 2), as masses (n = 2), and as a ground-glass opacity plus consolidation (n = 1). On pathologic examination, bronchioloalveolar carcinomas were well differentiated, having moderate degrees of nuclear atypism, mild degrees of mitotic figure, desmoplasia, and necrosis. The localized form of bronchioloalveolar carcinoma shows significantly lower peak standardized uptake values than do other lung carcinomas. Thus, bronchioloalveolar carcinoma can be a potential cause of false-negative findings of malignancy on FDG PET scans. When bronchioloalveolar carcinoma is suggested, FDG PET results should be interpreted in combination with high-resolution CT findings.

Reducing false negatives in clinical practice: The role of neural network technology

The fact that some cervical smears result in false-negative findings is an unavoidable and unpredictable consequence of the conventional (manual microscopic) method of screening. Errors in the detection and interpretation of abnormality are cited as leading causes of false-negative cytology findings; these are random errors that are not known to correlate with any patient risk factor, which makes the false-negative findings a “silent” threat that is difficult to prevent. Described by many as a labor-intensive procedure, the microscopic evaluation of a cervical smear involves a detailed search among hundreds of thousands of cells on each smear for a possible few that may indicate abnormality. Investigations into causes of false-negative findings preceding the discovery of high-grade lesions found that many smears had very few diagnostic cells that were often very small in size. These small cells were initially overlooked or misinterpreted and repeatedly missed on rescreening. PAPNET testing is designed to supplement conventional screening by detecting abnormal cells that initially may have been missed by microscopic examination. This interactive system uses neural networks, a type of artificial intelligence well suited for pattern recognition, to automate the arduous search for abnormality. The instrument focuses the review of suspicious cells by a trained cytologist. Clinical studies indicate that PAPNET testing is sensitive to abnormality typically missed by conventional screening and that its use as a supplemental test improves the accuracy of screening. (Am J Obstet Gynecol 1996;175:1114-9.)