Direct intramyocardial plasmid vascular endothelial growth factor-A165gene therapy in patients with stable severe angina pectoris A randomized double-blind placebo-controlled study: The Euroinject One trial

ObjectivesIn the Euroinject One phase II randomized double-blind trial, therapeutic angiogenesis of percutaneous intramyocardial plasmid gene transfer of vascular endothelial growth factor (phVEGF-A165) on myocardial perfusion, left ventricular function, and clinical symptoms was assessed.BackgroundEvidence for safety and treatment efficacy have been presented in phase I therapeutic angiogenesis trials.MethodsEighty “no-option” patients with severe stable ischemic heart disease, Canadian Cardiovascular Society functional class 3 to 4, were assigned randomly to receive, via the NOGA-MyoStar system (Cordis Corp., Miami Lakes, Florida), either 0.5 mg of phVEGF-A165(n = 40) or placebo plasmid (n = 40) in the myocardial region showing stress-induced myocardial perfusion defects on 99mTc sestamibi/tetrofosmin single-photon emission computed tomography.ResultsNo differences among the groups were recorded at baseline with respect to clinical, perfusion, and wall motion characteristics. After three months, myocardial stress perfusion defects did not differ significantly between the VEGF gene transfer and placebo groups (38 ± 3% and 44 ± 2%, respectively). Similarly, semiquantitative analysis of the change in perfusion in the treated region of interest did not differ significantly between the two groups. Compared with placebo, VEGF gene transfer improved the local wall motion disturbances, assessed both by NOGA (p = 0.04) and contrast ventriculography (p = 0.03). Canadian Cardiovascular Society functional class classification of angina pectoris improved significantly in both groups but without difference between the groups. No phVEGF-A165-related adverse events were observed; however, NOGA procedure-related adverse events occurred in five patients.ConclusionsThe VEGF gene transfer did not significantly improve stress-induced myocardial perfusion abnormalities compared with placebo; however, improved regional wall motion, as assessed both by NOGA and by ventriculography, may indicate a favorable anti-ischemic effect. This result should encourage more studies within the field. Transient VEGF overexpression seems to be safe

Improved Interpretation of Myocardial Perfusion Images by Artificial Neural Networks

Correct interpretation of medical imaging is based upon the interpreter’s experience and image quality. Depending on the report given the clinician decides how to use the result of the study. For many years a large number of image technologies including myocardial perfusion scintigraphy (MPS) have been acquired in digital format and the development of the imaging modalities are progressing rapidly. The need for software tools facilitating correct interpretation and assuring quality therefore also grows. In this thesis different ways were studied when and where a decision support system (DSS) can be used to improve the interpretation of MPS, mainly looking at two issues: a) The quality of the DSS. We studied how the performance of the DSS is influenced by the size of databases in relation to tracers used and possible image differences between genders (paper I). In paper III we studied the use of artificial neural networks for quality assurance of routine image interpretations. b) The influence of a DSS on the performance of interpreters with different experience levels (paper II) using both MPS stress and rest images. In paper IV we examined how often a rest study could be skipped to save resources and radiation. The results of paper I showed only a minor importance of the database being constructed with patients investigated using the same or different gender or tracers respectively. A large mixed database might even be superior to a smaller tracer-specific database. Some influence was seen for gender specific vs. mixed female-male databases regarding reversible defects and size of databases. We found that a DSS could be used to increase the quality of a DSS in an efficient way (paper III). In paper II it was demonstrated that the DSS improved physicians’ interpretations of reversible defects from a combined stress-rest MPS. For less experienced physicians DSS could make a difference. In paper IV stress-only MPS interpretation regarding the need of getting a rest image was improved. The conclusions in this thesis including the value of a DSS as a diagnostic advice are obviously not limited for MPS interpretation: DSS can be applied to many other types of medical images. The use of tools for supporting the interpretation of medical images will undoubtedly increase in the near future in relation to the rapid development of the imaging modalities

3-year follow-up of 215 fracture patients from a prospective and consecutive osteoporosis screening program. Fracture patients care!

BACKGROUND AND PURPOSE: Fractures can be prevented if osteoporosis is identified and treated. Starting in 2002, we have been using a screening program in which patients between 50 and 75 years of age with a wrist, shoulder, vertebral, or hip fracture are assessed by DEXA of the hip and spine and if osteoporotic or osteopenic, they are encouraged to see a doctor of their own choice. The patients receive documents containing information, the results of DEXA, and a letter to present to their doctor with suggestions regarding blood tests and treatment. Here we report the 3-year follow-up regarding compliance to the recommended treatment. METHODS: A questionnaire was sent to fracture patients who participated in the initial screening study from November 2002 through November 2003. Questions included whether they had seen a doctor, whether treatment had been initiated, and their opinions about osteoporosis. RESULTS: 215 of the 236 patients answered the questionnaire, with a mean follow-up of 39 months. 76/87 of those with osteoporosis, 70/99 of those with osteopenia, and 11/29 of those with normal BMD had seen a doctor. Anti-resorptive treatment was prescribed to two-thirds of the osteoporotic patients, to one-sixth of the osteopenic patients, and to none of the patients with normal bone density. Calcium-vitamin D supplementation as monotherapy was given to one-third of the osteoporotic patients, to half of the osteopenic patients, and to half of the normal patients. Only a few osteoporotic patients, one-third of the osteopenic patients, and half of the normal patients received no treatment. Compliance to treatment was 80% over 3 years in those treated. Most patients felt that they could influence their skeletal health. INTERPRETATION: Screening of fracture patients for osteoporosis effectively identifies patients with low bone mineral density and the patient can be trusted to seek appropriate medical advice for treatment of osteoporosis. Based on the bone scan diagnosis, the treatment that these patients received reflects current treatment guidelines well

Use of neural networks to improve quality control of interpretations in myocardial perfusion imaging

Background: The aim of this study was to explore the feasibility of using a technique based on artificial neural networks for quality assurance of image reporting. The networks were used to identify potentially suboptimal or erroneous interpretations of myocardial perfusion scintigrams (MPS). Methods: Reversible perfusion defects (ischaemia) in each of five myocardial regions, as interpreted by one experienced nuclear medicine physician during his daily routine of clinical reporting, were assessed by artificial neural networks in 316 consecutive patients undergoing stress/rest 99mTc-sestamibi myocardial perfusion scintigraphy. After a training process, the networks were used to select the 20 cases in each region that were more likely to have a false clinical interpretation. These cases, together with 20 control cases in which the networks detected no likelihood of false clinical interpretation, were presented in random order to a group of three experienced physicians for a consensus re-interpretation; no information regarding clinical or neural network interpretations was provided to the re-evaluation panel. Results: The clinical interpretation and the re-evaluation differed in 53 of the 200 cases. Forty-six of the 53 cases (87%) came from the group selected by the neural networks, and only seven (13%) were control cases (P < 0.001). The disagreements between clinical routine interpretation by an experienced nuclear medicine expert and artificial networks were related to small and mild perfusion defects and localization of defects. Conclusion: The results demonstrate that artificial neural networks can identify those myocardial perfusion scintigrams that may have suboptimal image interpretations. This is a potentially highly cost-effective technique, which could be of great value, both in daily practice as a clinical decision support tool and as a tool in quality assurance

An independent evaluation of a new method for automated interpretation of lung scintigrams using artificial neural networks

The purpose of this study was to evaluate a new automated method for the interpretation of lung perfusion scintigrams using patients from a hospital other than that where the method was developed, and then to compare the performance of the technique against that of experienced physicians. A total of 1,087 scintigrams from patients with suspected pulmonary embolism comprised the training group. The test group consisted of scintigrams from 140 patients collected in a hospital different to that from which the training group had been drawn. An artificial neural network was trained using 18 automatically obtained features from each set of perfusion scintigrams. The image processing techniques included alignment to templates, construction of quotient images based on the perfusion/template images, and finally calculation of features describing segmental perfusion defects in the quotient images. The templates represented lungs of normal size and shape without any pathological changes. The performance of the neural network was compared with that of three experienced physicians who read the same test scintigrams according to the modified PIOPED criteria using, in addition to perfusion images, ventilation images when available and chest radiographs for all patients. Performances were measured as area under the receiver operating characteristic curve. The performance of the neural network evaluated in the test group was 0.88 (95% confidence limits 0.81–0.94). The performance of the three experienced experts was in the range 0.87–0.93 when using the perfusion images, chest radiographs and ventilation images when available. Perfusion scintigrams can be interpreted regarding the diagnosis of pulmonary embolism by the use of an automated method also in a hospital other than that where it was developed. The performance of this method is similar to that of experienced physicians even though the physicians, in addition to perfusion images, also had access to ventilation images for most patients and chest radiographs for all patients. These results show the high potential for the method as a clinical decision support system

Patient gender and radiopharmaceutical tracer is of minor importance for the interpretation of myocardial perfusion images using an artificial neural network.

The purpose of this study was to assess the influence of patient gender and choice of perfusion tracer on computer-based interpretation of myocardial perfusion images. For the image interpretation, an automated method was used based on image processing and artificial neural network techniques. A total of 1000 patients were studied, all referred to the Royal Brompton Hospital in London for myocardial perfusion scintigraphy over a period of 1 year. The patients were randomized to receive either thallium or one of the two technetium tracers, methoxyisobutylisonitrile or tetrofosmin. Artificial neural networks were trained with either mixed gender or gender-specific and mixed tracer or tracer-specific training sets of different sizes. The performance of the networks was assessed in separate test sets, with the interpretation of experienced physicians regarding the presence or absence of fixed or reversible defects in the images as the gold standard. The neural networks trained with large mixed gender training sets were as good as the networks trained with gender-specific data sets. In addition, the neural networks trained with large mixed tracer training sets were as good as or better than the networks trained with tracer-specific data sets. Our results indicate that the influence of patient gender and perfusion tracer are of minor importance for the computer-based interpretation of the myocardial perfusion images. The differences that occur can be compensated for by larger training sets