The diagnostic utility of the Heston index in gated SPECT to detect multi-vessel coronary artery disease

Abstract

The Heston index is simple and achieves higher diagnostic value in the detection of multi-vessel CAD, compared with conventional analysis alone.

A flow-limiting stenosis is the major determinant of exercise-induced myocardial stunning in patients with coronary artery disease

“…All of the patients were in sinus rhythm during the image acquisition. SPECT images were reconstructed from the data using a data Odyssey VP processor (Picker) combined with a Butterworth filter (order 8; cut-off frequency 0.25 cycle/cm) and a ramp filter [10].…”

Important parameters in the detection of left main trunk disease using stress myocardial perfusion imaging

“…Image acquisition was commenced 30 min after the last exercise session. In the remaining 58 patients, adenosine triphosphate disodium (ATP) (0.16 mg/(kg min)) was administered intravenously for 6 min [17,18], and 3 min later 99m Tc-sestamibi (777 MBq) was given intravenously. Image acquisition was started 30 min later.…”

“…The total scores for all the segments on the initial images and delayed images were designated the summed stress score and the summed rest score , respectively. The summed difference score was defined as the summed stress score minus the summed rest score [18,21].…”

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography

“…Various approaches have, however, demonstrated moderate performance at best, not qualifying them as robust and reliable markers in clinical routine for the detection of diffusely impaired myocardial perfusion. [10][11][12] By contrast, the concept of radiomics as a novel supportive approach for image analysis in cardiac nuclear imaging is promising in this regard, as it allows assessing a multitude of subtle image features, which are imperceptible to the naked human eye and may potentially be more beneficial than previously addressed markers. Radiomics and machine learning applications in cardiology and cardiovascular imaging are now quite common in research 13 and a number of studies have already demonstrated a potential clinical value of radiomics in nuclear medicine and radiology, including cardiac CT. 14,15 However, the literature on its potential value specifically in SPECT MPI remains scarce.…”