Diagnostic evaluation of three cardiac software packages using a consecutive group of patients

Purpose: The aim of this study was to compare the diagnostic performance of the three software packages 4DMSPECT (4DM), Emory Cardiac Toolbox (ECTb), and Cedars Quantitative Perfusion SPECT (QPS) for quantification of myocardial perfusion scintigram (MPS) using a large group of consecutive patients. Methods: We studied 1,052 consecutive patients who underwent 2-day stress/rest 99mTc-sestamibi MPS studies. The reference/gold-standard classifications for the MPS studies were obtained from three physicians, with more than 25 years each of experience in nuclear cardiology, who re-evaluated all MPS images. Automatic processing was carried out using 4DM, ECTb, and QPS software packages. Total stress defect extent (TDE) and summed stress score (SSS) based on a 17-segment model were obtained from the software packages. Receiver-operating characteristic (ROC) analysis was performed. Results: A total of 734 patients were classified as normal and the remaining 318 were classified as having infarction and/or ischemia. The performance of the software packages calculated as the area under the SSS ROC curve were 0.87 for 4DM, 0.80 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.03; other differences p < 0.0001). The area under the TDE ROC curve were 0.87 for 4DM, 0.82 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.0005; other differences p < 0.0001). Conclusion: There are considerable differences in performance between the three software packages with 4DM showing the best performance and ECTb the worst. These differences in performance should be taken in consideration when software packages are used in clinical routine or in clinical studies

Area of ischemia assessed by physicians and software packages from myocardial perfusion scintigrams.

The European Society of Cardiology recommends that patients with >10% area of ischemia should receive revascularization. We investigated inter-observer variability for the extent of ischemic defects reported by different physicians and by different software tools, and if inter-observer variability was reduced when the physicians were provided with a computerized suggestion of the defects

Automated interpretation of gated-SPECT. A new approach to integrate the analysis of left ventricular perfusion and function

The general aim of the thesis was to develop and validate an automated decision support system for the interpretation of gated-SPECT myocardial perfusion images. Myocardial perfusion scintigraphy is a widely used method for the diagnosis and evaluation of patients with suspected or known coronary artery disease. The interpretation of these images can be difficult, and errors in interpretation may lead to serious mistakes in the treatment of patients. Thus, tools have been developed to assist physicians with the aim of improving accuracy and reducing variability between readers.The cornerstones of our decision support system are image processing techniques, artificial neural networks and databases of classified diagnostic images. We developed a new image processing method for quantification of cardiac function, denoted CAFU, which is based on the active shape algorithm and a heart-shaped model. Artificial neural networks that were inspired by the structure and function of biological neural networks such as the human brain were used to interpret the images based on CAFU measurements of left ventricular perfusion and function. The image processing and artificial neural network techniques are data-driven, i.e. they rely on a large number of relevant examples. Thus, large databases of myocardial perfusion images were developed.The decision support system was evaluated in a hospital separate from the location at which it was trained, and compared with an automated quantification software package. The system showed a performance regarding detection of myocardial infarction, measured as areas under receiver operating characteristics curves, of between 91% and 99% in the test material. The system also showed significantly higher specificities (95%) than the quantification software package (50% and 74%, respectively), compared at a sensitivity of 91%.In conclusion, our decision support system presents interpretations more similar to those of experienced clinicians than to those of a conventional automated quantification software package. This study shows the feasibility of disseminating the expertise of experienced clinicians to less experienced physicians by the use of artificial neural networks

Relation between pain and skeletal metastasis in patients with prostate or breast cancer.

The aim of this study was to examine the relation between pain and bone metastases in a group of patients with prostate or breast cancer that had been referred for bone scintigraphy. Whole-body bone scans, anterior and posterior views obtained with a dual detector gamma camera were studied from 101 consecutive patients who had undergone scintigraphy (600 MBq Tc-99m MDP) because of suspected bone metastatic disease. At the time of the examination, all patients were asked whether they felt any pain or had recently a trauma. This information was correlated with the classifications regarding the presence or absence of bone metastases made by a group of three experienced physicians. In patients with prostate cancer, we found metastases in 47% (18/38) of the patients with pain, but only in 12% (2/17) of the patients without pain (p = 0·01). In patients with breast cancer, on the other hand, metastases were more common in patients without pain (71%; 10/14) than in patients with pain (34%; 11/32) (p = 0·02). In conclusion, a significant relation between pain and skeletal metastases could be found in patients with prostate cancer and a reverse relation in patients with breast cancer

Computer-aided diagnosis system outperforms scoring analysis in myocardial perfusion imaging

The aim of this myocardial perfusion imaging (MPI) study was to compare the diagnostic performance of two computer-aided diagnosis (CAD) systems, EXINI Heart(TM) (EXINI), and PERFEXTM (PERFEX) Emory Cardiac Toolbox (ECT), and the summed stress score (SSS) values from both software packages. We studied 1,052 consecutive patients who underwent 2-day stress/rest Tc-99m-sestamibi MPI studies. The reference standard classifications for the MPI studies were obtained from three experienced physicians who separately classified all cases regarding the presence or absence of ischemia and/or infarction. Automatic processing was carried out using EXINI and PERFEX to obtain CAD results and SSS values based on the 17-segment model. The three experts' classifications showed ischemia in 257 patients and abnormal studies, i.e., either ischemia or infarction or both, in 318 patients. Accuracy was significantly higher in EXINI than in PERFEX, regarding both the detection of ischemia (87.4 vs 77.6%; P < 0.0001) and the detection of abnormal studies (91.6 vs 67.9%; P < 0.0001). EXINI's CAD system showed a higher specificity than its SSS values (86.8 vs 73.6%; P < 0.0001) at the same level of sensitivity. EXINI demonstrated greater diagnostic accuracy for detection of ischemia and abnormal studies than did PERFEX. EXINI CAD also outperformed its SSS analysis

Clinical data do not improve artificial neural network interpretation of myocardial perfusion scintigraphy.

Artificial neural networks interpretation of myocardial perfusion scintigraphy (MPS) has so far been based on image data alone. Physicians reporting MPS often combine image and clinical data. The aim was to evaluate whether neural network interpretation would be improved by adding clinical data to image data. Four hundred and eighteen patients were used for training and 532 patients for testing the neural networks. First, the network was trained with image data alone and thereafter with image data in combination with clinical parameters (age, gender, previous infarction, percutaneous coronary intervention, coronary artery bypass grafting, typical chest pain, present smoker, hypertension, hyperlipidaemia, diabetes, peripheral vascular disease and positive family history). Expert interpretation was used as gold standard. Receiver operating characteristic (ROC) curves were calculated, and the ROC areas for the networks trained with and without clinical data were compared for the diagnosis of myocardial infarction and ischaemia. There was no statistically significant difference in ROC area for the diagnosis of myocardial infarction between the neural network trained with the combination of clinical and image data (95·8%) and with image data alone (95·2%). For the diagnosis of ischaemia, there was no statistically significant difference in ROC area between the neural network trained with the combination of clinical and image data (87·9%) and with image data alone (88·0%). Neural network interpretation of MPS is not improved when clinical data are added to perfusion and functional data. One reason for this could be that experts base their interpretations of MPS mainly on the images and to a lesser degree on clinical data

Progression of bone metastases in patients with prostate cancer - automated detection of new lesions and calculation of bone scan index

BACKGROUND: The objective of this study was firstly to develop and evaluate an automated method for the detection of new lesions and changes in bone scan index (BSI) in serial bone scans and secondly to evaluate the prognostic value of the method in a group of patients receiving chemotherapy.METHODS: The automated method for detection of new lesions was evaluated in a group of 266 patients using the classifications by three experienced bone scan readers as a gold standard. The prognostic value of the method was assessed in a group of 31 metastatic hormone-refractory prostate cancer patients who were receiving docetaxel. Cox proportional hazards were used to investigate the association between percentage change in BSI, number of new lesions and overall survival. Kaplan-Meier estimates of the survival function were used to indicate a significant difference between patients with an increase/decrease in BSI or those with two or more new lesions or less than two new lesions.RESULTS: The automated method detected progression defined as two or more new lesions with a sensitivity of 93% and a specificity of 87%. In the treatment group, both BSI changes and the number of new metastases were significantly associated with survival. Two-year survival for patients with increasing and decreasing BSI from baseline to follow-up scans were 18% and 57% (p = 0.03), respectively. Two-year survival for patients fulfilling and not fulfilling the criterion of two or more new lesions was 35% and 38% (n.s.), respectively.CONCLUSIONS: An automated method can be used to calculate the number of new lesions and changes in BSI in serial bone scans. These imaging biomarkers contained prognostic information in a small group of patients with prostate cancer receiving chemotherapy

Bone Scan Index: A prognostic imaging biomarker for high-risk prostate cancer patients receiving primary hormonal therapy

Background: The objective of this study was to explore the prognostic value of the Bone Scan Index (BSI) obtained at the time of diagnosis in a group of high-risk prostate cancer patients receiving primary hormonal therapy. Methods: This was a retrospective study based on 130 consecutive prostate cancer patients at high risk, based on clinical stage (T2c/T3/T4), Gleason score (8 to 10) and prostate-specific antigen (PSA) (> 20 ng/mL), who had undergone whole-body bone scans 5. Conclusions: BSI can be used as a complement to PSA to risk-stratify high-risk prostate cancer patients at the time of diagnosis. This imaging biomarker, reflecting the extent of metastatic disease, can be of value both in clinical trials and in patient management when deciding on treatment