Radionuclide ventriculography phase analysis for risk stratification of patients undergoing cardiotoxic cancer therapy

Abstract Background Accurate diagnostic tools to identify patients at risk of cancer therapy-related cardiac dysfunction (CTRCD) are critical. For patients undergoing cardiotoxic cancer therapy, ejection fraction assessment using radionuclide ventriculography (RNVG) is commonly used for serial assessment of left ventricular (LV) function. Methods In this retrospective study, approximate entropy (ApEn), synchrony, entropy, and standard deviation from the phase histogram (phase SD) were investigated as potential early markers of LV dysfunction to predict CTRCD. These phase parameters were calculated from the baseline RNVG phase image for 177 breast cancer patients before commencing cardiotoxic therapy. Results Of the 177 patients, 11 had a decline in left ventricular ejection fraction (LVEF) of over 10% to an LVEF below 50% after treatment had commenced. This patient group had a significantly higher ApEn at baseline to those who maintained a normal LVEF throughout treatment. Of the parameters investigated, ApEn was superior for predicting the risk of CTRCD. Combining ApEn with the baseline LVEF further improved the discrimination between the groups. Conclusions The results suggest that RNVG phase analysis using approximate entropy may aid in the detection of sub-clinical LV contraction abnormalities, not detectable by baseline LVEF measurement, predicting a subsequent decline in LVEF.

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New Hybrid Method for Left Ventricular Ejection Fraction Assessment from Radionuclide Ventriculography Images

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405616666201118122509 ◽

2020 ◽

Vol 16 ◽

Author(s):

Halima Dziri ◽

Mohamed Ali Cherni ◽

Dorra Ben Sellem

Keyword(s):

Left Ventricular Ejection Fraction ◽

Left Ventricle ◽

Ejection Fraction ◽

Positive Predictive Value ◽

Roc Curve ◽

Radionuclide Ventriculography ◽

Left Ventricular ◽

The Other ◽

Left Ventricular Ejection ◽

Ventricular Ejection Fraction

Background: In this paper, we propose a new efficient method of radionuclide ventriculography image segmentation to estimate the left ventricular ejection fraction. This parameter is an important prognostic factor for diagnosing abnormal cardiac function. Methods: The proposed method combines the Chan-Vese and the mathematical morphology algorithms. It was applied to diastolic and systolic images obtained from the Nuclear Medicine Department of Salah AZAIEZ Institute.In order to validate our proposed method, we compare the obtained results to those of two methods of the literature. The first one is based on mathematical morphology, while the second one uses the basic Chan-Vese algorithm. To evaluate the quality of segmentation, we compute accuracy, positive predictive value and area under the ROC curve. We also compare the left ventricle ejection fraction estimated by our method to that of the reference given by the software of the gamma-camera and validated by the expert, using Pearson’s correlation coefficient, ANOVA test and linear regression. Results and conclusion: Static results show that the proposed method is very efficient in the detection of the left ventricle. The accuracy was 98.60%, higher than that of the other two methods (95.52% and 98.50%). Likewise, the positive predictive value was the highest (86.40% vs. 83.63% 71.82%). The area under the ROC curve was also the most important (0.998% vs. 0.926% 0.919%). On the other hand, Pearson's correlation coefficient was the highest (99% vs. 98% 37%). The correlation was significantly positive (p<0.001).

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