To validate a novel semi-automatic segmentation algorithm for MR-derived volume and function measurements by comparing it with the standard method of manual contour tracing. The new algorithms excludes papillary muscles and trabeculae from the blood pool, while the manual approach includes these objects in the blood pool. An epicardial contour served as input for both methods. Multiphase 2D steady-state free precession short axis images were acquired in 12 subjects with normal heart function and in a dynamic anthropomorphic heart phantom on a 1.5 T MR system. In the heart phantom, manually and semi-automatically measured cardiac parameters were compared to the true end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF). In the subjects, the semi-automatic method was compared to manual contouring in terms of difference in measured EDV, ESV, EF and myocardial volume (MV). For all measures, intra- and inter-observer agreement was determined. In the heart phantom, EDV and ESV were underestimated for both the semi-automatic. As the papillary muscles were excluded from the blood pool with the semi-automatic method, EDV and ESV were approximately 20 ml lower in the patients, whereas EF was approximately 16 % higher. Intra- and inter-observer agreement was overall improved with the semi-automatic method compared to the manual method. Correlation between manual and semi-automatic measurements was high (EDV: R = 0.99, ESV: R = 0.96; EF: R = 0.80, MV: R = 0.99). The semi-automatic method could exclude endoluminal muscular structures from the blood volume with significantly improved intra- and inter-observer variabilities in cardiac function measurements compared to the conventional, manual method, which includes endoluminal structures in the blood volume.

Due to specific structural organization at the molecular level, several biomolecules (e.g., collagen, myosin etc.) which are strong generators of second harmonic generation (SHG) signals, exhibit unique responses depending on the polarization of the excitation light. By using the polarization second harmonic generation (p-SHG) technique, the values of the second order susceptibility components can be used to differentiate the types of molecule, which cannot be done by the use of a standard SHG intensity image. In this report we discuss how to implement p-SHG on a commercial multiphoton microscope and overcome potential artifacts in susceptibility (χ) image. Furthermore we explore the potential of p-SHG microscopy by applying the technique to different types of tissue in order to determine corresponding reference values of the ratio of second-order χ tensor elements. These values may be used as a bio-marker to detect any structural alterations in pathological tissue for diagnostic purposes. The SHG intensity image (red) in (a) shows the distribution of collagen fibers in ovary tissue but cannot determine the type of collagen fiber. However, the histogram distribution (b) for the values of the χ tensor element ratio can be used to quantitatively identify the types of collagen fibers.

According to previous studies, the nonlinear susceptibility tensor ratio χ /χ obtained from polarization-resolved second harmonic generation (P-SHG) under the assumption of cylindrical symmetry can be used to distinguish between fibrillar collagen types. Discriminating between collagen fibrils of types I and II is important in tissue engineering of cartilage. However, cartilage has a random organization of collagen fibrils, and the assumption of cylindrical symmetry may be incorrect. In this study, we simulated the P-SHG response from different collagen organizations and demonstrated a possible method to exclude areas where cylindrical symmetry is not fulfilled and where fibrils are located in the imaging plane. The χ /χ -ratio for collagen type I in tendon and collagen type II in cartilage was estimated to be 1.33 and 1.36, respectively, using this method. These ratios are now much closer than what has been reported previously in the literature, and the larger reported differences between collagen types can be explained by variation in the structural organization.

Polarization-resolved second harmonic generation (P-SHG) microscopy has evolved as a promising technique to reveal subresolution information about the structure and orientation of ordered biological macromolecules. To extend the adoption of the technique, it should be easily integrated onto commercial laser scanning microscopes. Furthermore, procedures for easy calibration and assessment of measurement accuracy are essential, and measurements should be fully automated to allow for analysis of large quantities of samples. In this paper we present a setup for P-SHG which is readily incorporated on commercial multiphoton microscopes. The entire system is completely automated which allows for rapid calibration through the freely available software and for automated imaging for different polarization measurements, including linear and circular polarization of the excitation beam. The results show that calibration settings are highly system dependent. We also show that the accuracy of the polarization control is easily quantified and that it varies between systems. The accuracy can be tuned by iterative alignment of optics or a more fine-grained calibration procedure. Images of real samples show that the red accuracy of the results is easily visualized with the automated setup. Through this system we believe that P-SHG could develop a wider adoption in biomedical applications.

SHG represents a reliable quantitative approach to assess collagen deposition in laboratory engineered cartilage, and may be applied to improve currently established scoring systems.

No abstract

One of the main advantages of nonlinear microscopy is that it provides 3D imaging capability. Second harmonic generation is widely used to image the 3D structure of collagen fibers, and several works have highlighted the modification of the collagen fiber fabric in important diseases. By using an ellipsoidal specific fitting technique on the Fourier transformed image, we show, using both synthetic images and SHG images from cartilage, that the 3D direction of the collagen fibers can be robustly determined.