Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images

A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function

Implementation of a semiautomatic method to design patient-specific instruments for corrective osteotomy of the radius

\u3cp\u3ePurpose: 3D-printed patient-specific instruments (PSIs), such as surgical guides and implants, show great promise for accurate navigation in surgical correction of post-traumatic deformities of the distal radius. However, existing costs of computer-aided design and manufacturing process prevent everyday surgical use. In this paper, we propose an innovative semiautomatic methodology to streamline the PSIs design. Methods: The new method was implemented as an extension of our existing 3D planning software. It facilitates the design of a regular and smooth implant and a companion guide starting from a user-selected surface on the affected bone. We evaluated the software by designing PSIs starting from preoperative virtual 3D plans of five patients previously treated at our institute for corrective osteotomy. We repeated the design for the same cases also with commercially available software, with and without dedicated customization. We measured design time and tracked user activity during the design process of implants, guides and subsequent modifications. Results: All the designed shapes were considered valid. Median design times (t~) were reduced for implants ((t~ \u3csub\u3eI\u3c/sub\u3e) = 2.2 min) and guides ((t~ \u3csub\u3eG\u3c/sub\u3e) = 1.0 min) compared to the standard ((t~ \u3csub\u3eI\u3c/sub\u3e) = 13 min and (t~ \u3csub\u3eG\u3c/sub\u3e) = 8 min) and the partially customized ((t~ \u3csub\u3eI\u3c/sub\u3e) = 6.5 min and (t~ \u3csub\u3eG\u3c/sub\u3e) = 6.0 min) commercially available alternatives. Mouse and keyboard activities were reduced (median count of strokes and clicks during implant design ((s~ \u3csub\u3eI\u3c/sub\u3e) = 53, and guide design ((s~ \u3csub\u3eG\u3c/sub\u3e) = 27) compared to using standard software ((s~ \u3csub\u3eI\u3c/sub\u3e) = 559 and (s~ \u3csub\u3eG\u3c/sub\u3e) = 380) and customized commercial software ((s~ \u3csub\u3eI\u3c/sub\u3e) = 217 and (s~ \u3csub\u3eG\u3c/sub\u3e) = 180). Conclusion: Our software solution efficiently streamlines the design of PSIs for distal radius malunion. It represents a first step in making 3D-printed PSIs technology more accessible.\u3c/p\u3

Syllectometry : the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation

Syllectometry is a measuring method that is commonly used to assess red blood cell (RBC) aggregability. In syllectometry, light is incident on a layer of whole blood initially exposed to shear flow. The backscattered light is measured after abruptly stopping the driving mechanism. The resultant time-dependent intensity plot is called the syllectogram. Parameters that quantify RBC aggregability are obtained by analyzing the syllectogram. As we will show in this paper, the upstroke in the initial part of the syllectogram contains the information for measurement of RBC-shape recovery in whole blood as well. To estimate RBC-shape recovery, we extended the existing two-exponential mathematical representation of the syllectogram by a third exponent that describes the upstroke. To investigate the feasibility of RBC-shape recovery measurement from the upstroke, we derived an analytical model of the flow decay that follows after abruptly stopping the driving mechanism. The model reveals that for large gaps the flow decay may interfere with the true RBC-shape recovery process. These theoretical findings were confirmed by velocity measurements in a Couette-type aggregometer. Syllectograms obtained using large gaps differ in many respects from those obtained using small gaps. As predicted by our model large gaps show a prolonged apparent shape-recovery time-constant. Moreover, a delayed intensity peak, a reduced upstroke of the intensity peak and a considerable increase of the half-life parameter are observed. The aggregation indices for large gaps are lower than for small gaps. This paper yields a better understanding of the velocity and shear-rate decay following upon abruptly stopping the driving mechanism. A better mathematical representation of the syllectogram and recommendations for a maximum gap width enables both RBC-shape recovery and aggregation measurements in whole blood using syllectometry