Three-dimensional Imaging Research Articles

Long-term mesoscale imaging of 3D intercellular dynamics across a mammalian organ

A comprehensive understanding of physio-pathological processes necessitates non-invasive intravital three-dimensional (3D) imaging over varying spatial and temporal scales. However, huge data throughput, optical heterogeneity, surface irregularity, and phototoxicity pose great challenges, leading to an inevitable trade-off between volume size, resolution, speed, sample health, and system complexity. Here, we introduce a compact real-time, ultra-large-scale, high-resolution 3D mesoscope (RUSH3D), achieving uniform resolutions of 2.6×2.6×6μm3 across a volume of 8,000×6,000×400μm3 at 20Hz with low phototoxicity. Through the integration of multiple computational imaging techniques, RUSH3D facilitates a 13-fold improvement in data throughput and an orders-of-magnitude reduction in system size and cost. With these advantages, we observed premovement neural activity and cross-day visual representational drift across the mouse cortex, the formation and progression of multiple germinal centers in mouse inguinal lymph nodes, and heterogeneous immune responses following traumatic brain injury-all at single-cell resolution, opening up a horizon for intravital mesoscale study of large-scale intercellular interactions at the organ level.

Research on the Depth Image Reconstruction Algorithm Using the Two-Dimensional Kaniadakis Entropy Threshold.

The photon-counting light laser detection and ranging (LiDAR), especially the Geiger mode avalanche photon diode (Gm-APD) LiDAR, can obtain three-dimensional images of the scene, with the characteristics of single-photon sensitivity, but the background noise limits the imaging quality of the laser radar. In order to solve this problem, a depth image estimation method based on a two-dimensional (2D) Kaniadakis entropy thresholding method is proposed which transforms a weak signal extraction problem into a denoising problem for point cloud data. The characteristics of signal peak aggregation in the data and the spatio-temporal correlation features between target image elements in the point cloud-intensity data are exploited. Through adequate simulations and outdoor target-imaging experiments under different signal-to-background ratios (SBRs), the effectiveness of the method under low signal-to-background ratio conditions is demonstrated. When the SBR is 0.025, the proposed method reaches a target recovery rate of 91.7%, which is better than the existing typical methods, such as the Peak-picking method, Cross-Correlation method, and the sparse Poisson intensity reconstruction algorithm (SPIRAL), which achieve a target recovery rate of 15.7%, 7.0%, and 18.4%, respectively. Additionally, comparing with the SPIRAL, the reconstruction recovery ratio is improved by 73.3%. The proposed method greatly improves the integrity of the target under high-background-noise environments and finally provides a basis for feature extraction and target recognition.

Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine.

This study aimed to develop a graph neural network (GNN) for automated three-dimensional (3D) magnetic resonance imaging (MRI) visualization and Pfirrmann grading of intervertebral discs (IVDs), and benchmark it against manual classifications. Lumbar IVD MRI data from 300 patients were retrospectively analyzed. Two clinicians assessed the manual segmentation and grading for inter-rater reliability using Cohen's kappa. The IVDs were then processed and classified using an automated convolutional neural network (CNN)-GNN pipeline, and their performance was evaluated using F1 scores. Manual Pfirrmann grading exhibited moderate agreement (κ = 0.455-0.565) among the clinicians, with higher exact match frequencies at lower lumbar levels. Single-grade discrepancies were prevalent except at L5/S1. Automated segmentation of IVDs using a pretrained U-Net model achieved an F1 score of 0.85, with a precision and recall of 0.83 and 0.88, respectively. Following 3D reconstruction of the automatically segmented IVD into a 3D point-cloud representation of the target intervertebral disc, the GNN model demonstrated moderate performance in Pfirrmann classification. The highest precision (0.81) and F1 score (0.71) were observed at L2/3, whereas the overall metrics indicated moderate performance (precision: 0.46, recall: 0.47, and F1 score: 0.46), with variability across spinal levels. The integration of CNN and GNN offers a new perspective for automating IVD analysis in MRI. Although the current performance highlights the need for further refinement, the moderate accuracy of the model, combined with its 3D visualization capabilities, establishes a promising foundation for more advanced grading systems.

Effective and efficient coded aperture cone-beam computed tomography via generative adversarial U-Net

Coded aperture cone-beam computed tomography (CBCT) represents a crucial method for acquiring high-fidelity three-dimensional (3D) tomographic images while reducing radiation exposure. However, projections are non-uniformly and discontinuously sampled with the coded apertures placed in front of the x-ray source, leading to very small reconstruction scale and time-intensive iterations. In this study, an alternative approach to reconstruct coded aperture CBCT based on generative adversarial U-net is proposed to effectively and efficiently reconstruct large scale 3D CBCT images. Our method entails predicting complete and uniform projections from incomplete and non-uniform coded projections, enabling the requirement of continuity for the use of analytical algorithms in 3D image reconstruction. This novel technique effectively mitigates the traditional trade-off between image fidelity and computational complexity inherent in conventional coded aperture CBCT reconstruction methods. Our experimental results, conducted using clinical datasets comprising CBCT images from 102 patients at Nanjing Medical University, demonstrate that high-quality CBCT images with voxel dimensions of 400 × 400 × 400 can be reconstructed within 35 s, even when 95% of projections are blocked, yielding images with PSNR values exceeding 25dB and SSIM values surpassing 0.85.

Left Atrial Wall Thickness Estimated by Cardiac CT: Implications for Catheter Ablation of Atrial Fibrillation.

Atrial wall thickness (AWT) is a significant factor in understanding the pathological physiological substrate of atrial fibrillation, with a potentially substantial impact on the outcomes of catheter ablation procedures. Precise measurements of the AWT may provide valuable insights for categorising patients with AF and planning targeted interventions. Objectives: The purpose of this study was to evaluate the characteristics of the left atrium (LA) using non-invasive multidetector computed tomography (MDCT) scans and subsequent three-dimensional (3D) image post-processing using novel software designed to calculate atrial thickness dimensions and mass. Methods: We retrospectively analysed 128 consecutive patients (33.6% females; mean age 55.6 ± 11.2 years) referred for AF ablation (37 with persistent AF and 91 with paroxysmal AF) who underwent preprocedural MDCT. The images were post-processed and analysed using the ADAS software (Galgo Medical), automatically calculating the LA volume and regional wall thickness. In addition, the software employed a regional semi-automatic LA parcellation feature that divided the atrial wall into 12 segments, generating atrial wall thickness (AWT) maps per segment for each patient. Results: This study demonstrated considerable variability in the average thickness of LA walls, with the anterior segments being the thickest across the cohort. Distinct sex-specific differences were observed, with males exhibiting greater anterior and septal wall thickness than females. No significant associations were identified between the average AWT and body mass index, LA volume, or sphericity. Survival analysis conducted over 24 months revealed a meaningful relationship between mean anterior wall thickness and recurrence-free survival, with increased thickness associated with a lower likelihood of AF-free survival. No such relationship was observed for the indexed LA volume. Conclusions: The variability in AWT and its association with recurrence-free survival following AF ablation suggest that AWT should be considered when stratifying patients for AF management and ablation strategies. These findings underscore the need for personalised treatment approaches and further research on the interplay of the structural properties of the left atrium as factors that can serve as important prognostic markers in AF treatment.

Video frame interpolation neural network for 3D tomography across different length scales

Three-dimensional (3D) tomography is a powerful investigative tool for many scientific domains, going from materials science, to engineering, to medicine. Many factors may limit the 3D resolution, often spatially anisotropic, compromising the precision of the information retrievable. A neural network, designed for video-frame interpolation, is employed to enhance tomographic images, achieving cubic-voxel resolution. The method is applied to distinct domains: the investigation of the morphology of printed graphene nanosheets networks, obtained via focused ion beam-scanning electron microscope (FIB-SEM), magnetic resonance imaging of the human brain, and X-ray computed tomography scans of the abdomen. The accuracy of the 3D tomographic maps can be quantified through computer-vision metrics, but most importantly with the precision on the physical quantities retrievable from the reconstructions, in the case of FIB-SEM the porosity, tortuosity, and effective diffusivity. This work showcases a versatile image-augmentation strategy for optimizing 3D tomography acquisition conditions, while preserving the information content.

Time-to-brightness converter (TBC): measuring photon arrival time with conventional cameras.

We introduce a new, to our knowledge, method to measure the arrival time of photons with a sub-nanosecond precision using two conventional cameras. The method exploits the finite rise/fall time of the electro-optical global shutter implemented in modern complementary metal-oxide semiconductor (CMOS) cameras. By mapping the arrival time to the normalized brightness, the time of flight (ToF) can be determined with a precision better than 0.3 ns. The method can be implemented at the pixel level of a camera and thus simultaneously provides a high spatial resolution to achieve high-performing three-dimensional (3D) imaging.

An improved bridge reference network for 3-D SAR tomography based on regional growing strategy

ABSTRACT The utilization of synthetic aperture radar tomography (TomoSAR) technology for the three-dimensional imaging of urban areas has garnered significant attention. In the case of multi-pass spaceborne TomoSAR, eliminating the atmospheric phase screen (APS) is a critical step. At present, a two-tier network method is widely employed for APS removal from extensive regions. However, challenges persist in the construction of first-tier reference networks using the Delaunay triangulation and bridge reference network methods, such as low network coverage ratios and linear correlation problems associated with near-parallel bridges. Consequently, a notable portion of the inversion results for buildings or artificial structures are either absent or characterized by low accuracy. To fully harness the observational information from all small connecting networks, this study introduces an improved bridge reference network construction method based on a region-growing strategy. This method merges small subnetworks with surrounding reference networks using high-quality bridge connections to maximize the coverage of the largest reference network. To validate the feasibility and effectiveness of the proposed approach, 27 TerraSAR-X images, which were collected in Shenzhen, China were utilized to construct a reference network and estimate building heights. The results clearly indicate that the proposed method effectively overcomes the limitations of existing methods.

Association of open skill exercise and long-chain polyunsaturated fatty acid intake with brain volume changes among older community-dwelling Japanese individuals

Considering that a multifactorial lifestyle approach may prove more effective than a single factor approach to improve or maintain brain health, we evaluated the association of exercise (open skill exercise [OSE] or closed skill exercise [CSE]) combined with long-chain polyunsaturated fatty acid (LCPUFAs) (docosahexaenoic acid [C22:6n-3, DHA], eicosapentaenoic acid [C20:5n-3, EPA], and arachidonic acid [C20:4n-6, ARA]) intake with brain atrophy among older Japanese individuals (n = 795, aged 60–88 years) without a self-reported history of dementia based on the datasets of a two-year longitudinal study. Brain volumes were measured using three-dimensional T1-weighted brain magnetic resonance imaging for follow-up periods of two years. The associations between multivariate-adjusted changes in brain volumes and OSE or CSE frequency (≥ once/month and < once/month) along with LCPUFA intake (≥ median and < median) at the baseline were assessed using a general linear model. Subgroup analysis was performed by restricting DHA and EPA intakes (n = 263; median, 323 mg/d), which represented levels similar to those in countries with low fish consumption. Higher OSE frequencies, ARA intakes, and their combination were inversely associated with decreases in total gray matter and frontal cortex volumes. In subgroup analysis, a combination of higher OSE frequencies and DHA intakes was also associated with a smaller decrease in total gray matter volume. Overall, our findings suggest that regular OSE engagement and appropriate LCPUFA intake may contribute to preventing brain volume decreases in older individuals.

The Bony Nasal Cavity and Paranasal Sinuses of Big Felids and Domestic Cat: A Study Using Anatomical Techniques, Computed Tomographic Images Reconstructed in Maximum-Intensity Projection, Volume Rendering and 3D Printing Models.

This study aims to develop three-dimensional printing models of the bony nasal cavity and paranasal sinuses of big and domestic cats using reconstructed computed tomographic images. This work included an exhaustive study of the osseous nasal anatomy of the domestic cat carried out through dissections, bone trepanations and sectional anatomy. With the use of OsiriX viewer, the DICOM images were postprocessed to obtaining maximum-intensity projection and volume-rendering reconstructions, which allowed for the visualization of the nasal cavity structures and the paranasal sinuses, providing an improvement in the future anatomical studies and diagnosis of pathologies. DICOM images were also processed with AMIRA software to obtain three-dimensional images using semiautomatic segmentation application. These images were then exported using 3D Slicer software for three-dimensional printing. Molds were printed with the Stratasys 3D printer. In human medicine, three-dimensional printing is already of great importance in the clinical field; however, it has not yet been implemented in veterinary medicine and is a technique that will, in the future, in addition to facilitating the anatomical study and diagnosis of diseases, allow for the development of implants that will improve the treatment of pathologies and the survival of big felids.

Clinical study on improving the diagnostic accuracy of adult elbow joint cartilage injury by multisequence magnetic resonance imaging.

Due to frequent and high-risk sports activities, the elbow joint is susceptible to injury, especially to cartilage tissue, which can cause pain, limited movement and even loss of joint function. To evaluate magnetic resonance imaging (MRI) multisequence imaging for improving the diagnostic accuracy of adult elbow cartilage injury. A total of 60 patients diagnosed with elbow cartilage injury in our hospital from January 2020 to December 2021 were enrolled in this retrospective study. We analyzed the accuracy of conventional MRI sequences (T1-weighted imaging, T2-weighted imaging, proton density weighted imaging, and T2 star weighted image) and Three-Dimensional Coronary Imaging by Spiral Scanning (3D-CISS) in the diagnosis of elbow cartilage injury. Arthroscopy was used as the gold standard to evaluate the diagnostic effect of single and combination sequences in different injury degrees and the consistency with arthroscopy. The diagnostic accuracy of 3D-CISS sequence was 89.34% ± 4.98%, the sensitivity was 90%, and the specificity was 88.33%, which showed the best performance among all sequences (P < 0.05). The combined application of the whole sequence had the highest accuracy in all sequence combinations, the accuracy of mild injury was 91.30%, the accuracy of moderate injury was 96.15%, and the accuracy of severe injury was 93.33% (P < 0.05). Compared with arthroscopy, the combination of all MRI sequences had the highest consistency of 91.67%, and the kappa value reached 0.890 (P < 0.001). Combination of 3D-CISS and each sequence had significant advantages in improving MRI diagnostic accuracy of elbow cartilage injuries in adults. Multisequence MRI is recommended to ensure the best diagnosis and treatment.

A convenient archaeological ruins identification method through elevation information extraction from CORONA stereo pairs

Three-dimensional (3-D) stereo images can be generated via computer-based image processing of CORONA stereo pairs. To a certain extent, important terrain and surface feature data extracted from these stereo images can improve the survey of archaeological sites and the identification and mapping of major landscapes. In this study, we focused on the identification of the archaeological ruins of Liangzhu City. An optical stereo model (red/blue stereo image) of the Liangzhu site was created through computer-based mosaicking and processing of CORONA remote-sensing stereo pairs taken in the 1960s and 1970s. By importing the optical stereo model into mobile phones, tablet computers, and other mobile devices, the research team undertook real-time locating of ruins via human observation, on-site investigation, and image overlay during a field survey and identified several Liangzhu-period dams, some of which have been confirmed via archaeological field investigations. The research team later applied the same method to the identification of tombs at the site of the mausoleums of the six emperors of the Southern Song dynasty. The results further prove that this method is feasible and reliable and can be widely promoted and used for the identification of archaeological ruins.

Effect of Dialysis on Structural Brain Connectivity in Patients with End-Stage Renal Disease

Introduction: Patients with end-stage renal disease (ESRD) are known to have reduced structural and functional brain connectivity in the brain regions associated with cognitive function. However, the effect of dialysis on brain connectivity remains unclear. This study aimed to evaluate the effects of dialysis on structural brain connectivity in patients with ESRD. Methods: This prospective study included 20 patients with ESRD in the pre-dialysis stage and 35 healthy controls. The patients underwent T2-weighted and three-dimensional T1-weighted magnetic resonance imaging before and 3 months after dialysis initiation. Moreover, the cortical thickness was calculated. We applied graph theoretical analysis to calculate the structural covariance network based on cortical thickness. We compared the cortical thickness and structural covariance network of patients with ESRD in the pre-dialysis stage with those of healthy controls and with those of patients with ESRD in the post-dialysis stage. Results: The mean cortical thickness in both hemispheres was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (2.296 vs. 2.354, p = 0.030; 2.282 vs. 2.362, p = 0.004, respectively) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (2.333 vs. 2.296, p = 0.001; 2.322 vs. 2.282, p = 0.002, respectively). Analysis of the structural covariance network revealed that the assortative coefficient was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (−0.062 vs. −0.031, p = 0.029) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (−0.002 vs. −0.062, p = 0.042). Conclusion: We observed differences in the cortical thickness and structural covariance networks before and after dialysis in patients with ESRD. This indicates that dialysis affects structural brain connectivity, contributing to the understanding of the pathophysiological mechanism of cognitive function alterations resulting from dialysis in patients with ESRD.

Simultaneous Imaging of Temperature and Oxygen by Utilizing Thermally Activated Delayed Fluorescence and Phosphorescence of a Single Indicator.

Chemical gradients are essential in biological systems, affecting processes like microbial activity in soils and nutrient cycling. Traditional tools, such as microsensors, offer high-resolution data but are limited to one-dimensional measurements. Planar optodes allow for two-dimensional (2D) and three-dimensional (3D) chemical imaging but are often sensitive to temperature changes. This study presents an advanced dual-emission optical sensor that simultaneously measures temperature and oxygen using a modified platinum(II) meso-tetrakis(3,5-ditert-butylphenyl)-tetra(2-tert-butyl-1,4-naphthoquinono)porphyrin. The ratio between thermally activated delayed fluorescence and phosphorescence was optimized by modifying platinum(II) naphthoquinonoporphyrin with tert-butyl groups which simultaneously improved solubility in apolar solvents and polymer matrix (polystyrene). This dual-function sensor enables two-parameter chemical imaging with a consumer-grade RGB camera or a hyperspectral camera. We demonstrated 2D visualization of temperature and oxygen distribution in a model soil system. The RGB camera provided rapid and cost-effective imaging, while the hyperspectral camera offered more detailed spectral information despite some limitations. Our findings revealed the formation of a stable temperature gradient and oxygen depletion, driven by water content and temperature-sensitive microbial activity. This dual O2/T sensor, with further potential improvements, shows considerable promise for advanced multiparameter sensing in complex biological and environmental studies, providing deeper insights into dynamic microenvironments.

Evaluation of awareness, requirement, and clinical applications of guided endodontics among dental practitioners in North India – A cross-sectional study

ABSTRACT Aim: Guided endodontics (GE) represents a cutting-edge shift in dental practice, utilizing three-dimensional imaging to enhance treatment precision and safety in endodontics. Since its introduction in 2016, GE has shown promise in reducing complications by guiding dental procedures with minimal invasiveness. This study evaluates its acceptance and application among North India’s dental community, aiming to identify educational gaps and operational challenges. Methodology: An online survey, approved by ethical standards, was distributed to dental professionals in North India, collecting 265 responses on their familiarity, application, and training needs regarding GE. Results: Findings reveal a general awareness of GE among respondents, with a notable lack of specialized training. While GE’s benefits in various dental treatments were acknowledged, a significant interest in further training was expressed, underlining the necessity for enhanced educational programs. Conclusion: The research highlights a keen interest in GE among dentists, despite existing educational gaps. There is a clear call for integrating GE-focused training into dental curricula to equip practitioners with the skills needed for its effective use, potentially transforming patient care in endodontics.

Impact of three-dimensional imaging and printing on septal myectomy results-single centre's experience.

To assess changes in the results of septal myectomy (SM) following introduction of three-dimensional (3D) imaging and 3D printing in surgical interventions planning and performing in the single-centre settings. Between January 2007 and March 2022, 268 consecutive symptomatic patients with hypertrophic obstructive cardiomyopathy and peak pressure gradient at obstruction area ≥50 mmHg underwent conventional SM (n = 112) or SM with heart 3D modelling (n = 156). For comparative analysis, we used propensity score matching (PSM) by 14 variables and there were formed group 1PSM (conventional SM, n = 77) and group 2PSM (3D-modelled SM, n = 77). It was noted for group 2PSM: larger mean resected myocardium mass [10.0 (standard deviation 4.3) vs 5.2 (standard deviation 2.7) g], P < 0.001, no mitral valve replacement cases [0 vs 28 (36.4%), P < 0.001], no iatrogenic ventricular septal defects cases [0 vs 6 (7.8%), P = 0.028], lower rate of major complications [6 (7.8%) vs 17 (22.1%), P = 0.011], smaller residual peak systolic gradient at the obstruction level [7.0 (5.0-9.0) vs 11.0 (7.0-16.0) mmHg, P < 0.001]. During the long-term follow-up, it was noted for group 2PSM as compared to group 1PSM: lower 5-year cumulative incidence of major adverse cardiovascular events [3.8% (95% confidence interval 0.7-11.7%) vs 16.9% (9.5-26.1%), P = 0.007] and cardiac-related death [3.8% (95% confidence interval 0.7-11.7%) vs 13% (95% confidence interval 6.6-21.6%), P = 0.05]. SM based on 3D virtual and printed heart models is more effective than conventional SM.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Morphological changes in temporomandibular joint architecture in patients with temporomandibular disorders: systematic review protocol

ObjectiveThe review involves the assessment of morphological variations in the temporomandibular joint (TMJ) and its associated structures in patients with temporomandibular disorder.IntroductionTemporomandibular disorders (TMD) are debilitating conditions that affect the...

Changes in Skin Paddle Morphology after Autologous Breast Reconstruction

Background: Immediate autologous breast reconstruction (IABR) can provide favorable aesthetic outcomes after skin-sparing mastectomy. However, it is known that the morphology of the reconstructed breast changes over time. Therefore, it is necessary to be able to predict the likely amount of change preoperatively to reconstruct a symmetrical breast. In this study, we retrospectively examined the change in position and morphology of the skin paddle of the reconstructed breast over time. Methods: Thirty-five patients who underwent IABR after skin-sparing mastectomy for unilateral breast cancer were included. Three-dimensional images were obtained at 1 month and 12 months postoperatively to compare changes in the position and size of the skin paddle over time. Results: Significant increases were observed in the distance between the center of the skin paddle and the midpoint of the clavicle, the distance between the center of the skin paddle and the sternal notch, and projection. No significant change was observed in the distance between the inframammary fold and the center of the skin paddle. There was a significant increase in the area and short axis of the skin paddle. Conclusions: Our main findings were that the skin paddle shifts toward the outer caudal side after IABR and tends to become larger. When planning delayed nipple reconstruction with a local flap designed on a skin paddle, the paddle should be positioned slightly more mediocranially than the healthy nipple and should be narrower.

A 2D Ultrasonic Phased Array Optimization Framework Enabled by Reconfigurable Laser Induced Phased Arrays

Abstract Three-dimensional (3D) ultrasonic imaging enables the viewing of internal features in a more accurate way than cross-sectional imaging. 3D imaging requires two-dimensional (2D) ultrasonic phased arrays to resolve all three spatial dimensions through beamforming along azimuthal and elevation angles. 2D phased arrays pose a manufacturing and control challenge due to the requirement of large number of elements to satisfy the Nyquist sampling limit. This problem can be alleviated through the use of sparse ultrasonic array designs. The optimization process is critical, as this dictates the efficiency of suppression of grating lobes. The aim of this work is to establish a framework for design of optimized sparse 2D phased arrays. This is enabled by exploiting the reconfigurability of Laser Induced Phased Arrays (LIPAs). LIPAs are synthetic arrays produced by scanning one laser for ultrasound generation and another for ultrasound detection, independently of each other. The reconfigurability and decoupled ultrasonic generation and detection of this systems enables easy and fast implementation of any arbitrary array layout. The framework consists of an analytical model for parametric evaluation of designs. The model performs a parametric sweep on the generation and detection element positions for each array design in order to identify the optimal parameters, based on mean and maximum side-lobe level. In the presented framework, four array designs are utilized for the optimization process: matrix, random, Vernier and a novel array design the Rotated Array (RA).