Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function

Mechanisms of artemether toxicity on single cardiomyocytes and protective effect of nanoencapsulation

BACKGROUND AND PURPOSE

The artemisinin derivative, artemether, has antimalarial activity with potential neurotoxic and cardiotoxic effects. Artemether in nanocapsules (NC-ATM) is more efficient than free artemether for reducing parasitaemia and increasing survival of Plasmodium berghei-infected mice. NCs also prevent prolongation of the QT interval of the ECG. Here, we assessed cellular cardiotoxicity of artemether and how this toxicity was prevented by nanoencapsulation.

EXPERIMENTAL APPROACH

Mice were treated with NC-ATM orally (120 mg·kg-1 twice daily) for 4 days. Other mice received free artemether, blank NCs, and vehicle for comparison. We measured single-cell contraction, intracellular Ca2+ transient using fluorescent Indo-1AM Ca2+ dye, and electrical activity using the patch-clamp technique in freshly isolated left ventricular myocytes. The acute effect of free artemether was also tested on cardiomyocytes of untreated animals.

KEY RESULTS

Artemether prolonged action potentials (AP) upon acute exposure (at 0.1, 1, and 10 μM) of cardiomyocytes from untreated mice or after in vivo treatment. This prolongation was unrelated to blockade of K+ currents, increased Ca2+ currents or promotion of a sustained Na+ current. AP lengthening was abolished by the NCX inhibitor SEA-0400. Artemether promoted irregular Ca2+ transients during pacing and spontaneous Ca2+ events during resting periods. NC-ATM prevented all effects. Blank NCs had no effects compared with vehicle.

CONCLUSION AND IMPLICATIONS

Artemether induced NCX-dependent AP lengthening (explaining QTc prolongation) and disrupted Ca2+ handling, both effects increasing pro-arrhythmogenic risks. NCs prevented these adverse effects, providing a safe alternative to the use of artemether alone, especially to treat malaria.

An Efficient Framework for Accurate Arterial Input Selection in DSC-MRI of Glioma Brain Tumors

INTRODUCTION

Automatic and accurate arterial input function (AIF) selection has an essential role for quantification of cerebral perfusion hemodynamic parameters using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). The purpose of this study is to develop an optimal automatic method for arterial input function determination in DSC-MRI of glioma brain tumors by using a new preprocessing method.

MATERIAL AND METHODS

For this study, DSC-MR images of 43 patients with glioma brain tumors were retrieved retrospectively. Our proposed AIF selection framework consisted an effcient pre-processing step, through which non-arterial curves such as tumorous, tissue, noisy and partial-volume affected curves were excluded, followed by AIF selection through agglomerative hierarchical (AH) clustering method. The performance of automatic AIF clustering was compared with manual AIF selection performed by an experienced radiologist, based on curve shape parameters, i.e. maximum peak (MP), full-width-at-half-maximum (FWHM), M (=MP/ (TTP × FWHM)) and root mean square error (RMSE).

RESULTS

Mean values of AIFs shape parameters were compared with those derived from manually selected AIFs by two-tailed paired t-test. The results showed statistically insignificant differences in MP, FWHM, and M parameters and lower RMSE, approving the resemblance of the selected AIF with the gold standard. The intraclass correlation coefficient and coefficients of variation percent showed a better agreement between manual AIF and our proposed AIF selection than previously proposed methods.

CONCLUSION

The results of current work suggest that by using efficient preprocessing steps, the accuracy of automatic AIF selection could be improved and this method appears promising for efficient and accurate clinical applications.

Automatic determination of the arterial input function in dynamic susceptibility contrast MRI: comparison of different reproducible clustering algorithms

Introduction

Arterial input function (AIF) plays an important role in the quantification of cerebral hemodynamics. The purpose of this study was to select the best reproducible clustering method for AIF detection by comparing three algorithms reported previously in terms of detection accuracy and computational complexity.

Methods

First, three reproducible clustering methods, normalized cut (Ncut), hierarchy (HIER), and fast affine propagation (FastAP), were applied independently to simulated data which contained the true AIF. Next, a clinical verification was performed where 42 subjects participated in dynamic susceptibility contrast MRI (DSC-MRI) scanning. The manual AIF and AIFs based on the different algorithms were obtained. The performance of each algorithm was evaluated based on shape parameters of the estimated AIFs and the true or manual AIF. Moreover, the execution time of each algorithm was recorded to determine the algorithm that operated more rapidly in clinical practice.

Results

In terms of the detection accuracy, Ncut and HIER method produced similar AIF detection results, which were closer to the expected AIF and more accurate than those obtained using FastAP method; in terms of the computational efficiency, the Ncut method required the shortest execution time.

Conclusion

Ncut clustering appears promising because it facilitates the automatic and robust determination of AIF with high accuracy and efficiency.