Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.

Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

Holographic mixed reality for planning transcatheter aortic valve replacement.

BACKGROUND: Using three-dimensional (3D) modalities for optimal pre-procedure planning in transcatheter aortic valve replacement (TAVR) is critical for procedural success. However, current methods rely on visualizing images on a two-dimensional screen, using shading and colors to create the illusion of 3D, potentially impeding the accurate comprehension of the actual anatomy structures. In contrast, a new Mixed Reality (MxR) based software enables accurate 3D visualization, imaging manipulation, and quantification of measurements. AIMS: The study aims to evaluate the feasibility, reproducibility, and accuracy of dimensions of the aortic valve complex as measured with a new holographic MxR software (ARTICOR®, Artiness srl, Milano, Italy) compared to a widely used software for pre-operative sizing and planning (3mensio Medical Imaging BV, Bilthoven, The Netherlands) . METHODS: This retrospective, observational, double-center study enrolled 100 patients with severe aortic stenosis who underwent cardiac computed tomography (CCT) before TAVR. The CCT datasets of volumetric aortic valve images were analyzed using 3Mensio and newly introduced MxR-based software. RESULTS: 98% of the CCT datasets were successfully converted into holographic models. A higher level of agreement between the two software systems was observed for linear metrics (short, long, and average diameter). In comparison, agreement was lower for area, perimeter, and annulus-to-coronary ostia distance measurements. Notably, the annulus area, annular perimeter, LVOT area, and LVOT perimeter were significantly and consistently smaller with the MxR-based software compared to the 3Mensio. Excellent interobserver reliability was demonstrated for most measurements, especially for direct linear measurements. CONCLUSIONS: Linear Measurements of the aortic valve complex using MxR-based software are reproducible compared to the standard CCT dataset analyzed with 3Mensio. MxR-based software could represent an accurate tool for the pre-procedural planning of TAVR.

Automated workflows using Quantitative Colour Pattern Analysis (QCPA): a guide to batch processing and downstream data analysis.

Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers. However, its extensive array of user-defined image processing and analysis tools means image analysis is often time-consuming. This hinders the full use of analytical power provided by QCPA and its application to large datasets. Here, we offer a robust and comprehensive batch script, allowing users to automate many QCPA workflows. We also provide a complimentary set of useful R scripts for downstream data extraction and analysis. The presented batch processing extension will empower users to further utilise the analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for exploring colour pattern spaces and developing ever-richer frameworks for analysing organismal colouration accounting for visual perception in animals other than humans. These advances will, in turn, facilitate testing hypotheses on the function and evolution of vision and signals at quantitative and qualitative scales, which are otherwise computationally unfeasible. Supplementary Information: The online version contains supplementary material available at 10.1007/s10682-024-10291-7.

APIS: an updated parentage assignment software managing triploids induced from diploid parents.

In aquaculture, sterile triploids are commonly used for production as sterility gives them potential gains in growth, yields and quality. However, they cannot be reproduced, and DNA parentage assignment to their diploid or tetraploid parents is required to estimate breeding values for triploid phenotypes. No publicly available software has the ability to assign triploids to their parents. Here, we updated the R package APIS to support triploids induced from diploid parents. First, we created new exclusion and likelihood tables that account for the double allelic contribution of the dam and the recombination that can occur during female meiosis. As the effective recombination rate of each marker with the centromere is usually unknown, we set it at 0.5 and found that this value maximises the assignment rate even for markers with high or low recombination rates. The number of markers needed for a high true assignment rate did not strongly depend on the proportion of missing parental genotypes. The assignment power was however affected by the quality of the markers (minor allele frequency, call rate). Altogether, 96 to 192 SNPs were required to have a high parentage assignment rate in a real rainbow trout dataset of 1232 triploid progenies from 288 parents. The likelihood approach was more efficient than exclusion when the power of the marker set was limiting. When more markers were used, exclusion was more advantageous, with sensitivity reaching unity, very low False Discovery Rate (<0.01) and excellent specificity (0.96-0.99). Thus, APIS provides an efficient solution to assign triploids to their diploid parents.

BASSA: New software tool reveals hidden details in visualisation of low-frequency animal sounds.

The study of animal sounds in biology and ecology relies heavily upon time-frequency (TF) visualisation, most commonly using the short-time Fourier transform (STFT) spectrogram. This method, however, has inherent bias towards either temporal or spectral details that can lead to misinterpretation of complex animal sounds. An ideal TF visualisation should accurately convey the structure of the sound in terms of both frequency and time, however, the STFT often cannot meet this requirement. We evaluate the accuracy of four TF visualisation methods (superlet transform [SLT], continuous wavelet transform [CWT] and two STFTs) using a synthetic test signal. We then apply these methods to visualise sounds of the Chagos blue whale, Asian elephant, southern cassowary, eastern whipbird, mulloway fish and the American crocodile. We show that the SLT visualises the test signal with 18.48%-28.08% less error than the other methods. A comparison between our visualisations of animal sounds and their literature descriptions indicates that the STFT's bias may have caused misinterpretations in describing pygmy blue whale songs and elephant rumbles. We suggest that use of the SLT to visualise low-frequency animal sounds may prevent such misinterpretations. Finally, we employ the SLT to develop 'BASSA', an open-source, GUI software application that offers a no-code, user-friendly tool for analysing short-duration recordings of low-frequency animal sounds for the Windows platform. The SLT visualises low-frequency animal sounds with improved accuracy, in a user-friendly format, minimising the risk of misinterpretation while requiring less technical expertise than the STFT. Using this method could propel advances in acoustics-driven studies of animal communication, vocal production methods, phonation and species identification.

phoenix: an R package and Python module for calculating the Phoenix pediatric sepsis score and criteria.

Objectives: The publication of the Phoenix criteria for pediatric sepsis and septic shock initiates a new era in clinical care and research of pediatric sepsis. Tools to consistently and accurately apply the Phoenix criteria to electronic health records (EHRs) is one part of building a robust and internally consistent body of research across multiple research groups and datasets. Materials and Methods: We developed the phoenix R package and Python module to provide researchers with intuitive and simple functions to apply the Phoenix criteria to EHR data. Results: The phoenix R package and Python module enable researchers to apply the Phoenix criteria to EHR datasets and derive the relevant indicators, total scores, and sub-scores. Discussion: The transition to the Phoenix criteria marks a major change in the conceptual definition of pediatric sepsis. Applicable across differentially resourced settings, the Phoenix criteria should help improve clinical care and research. Conclusion: The phoenix R package and Python model are freely available on CRAN, PyPi, and GitHub. These tools enable the consistent and accurate application of the Phoenix criteria to EHR datasets.

Revisiting calculation of tilt angles for double-tilt sample holders in transmission electron microscopes.

We revisited the formula related to the overall tilt angle of a specimen using a side-entry double-tilt sample holder in a transmission electron microscope. Initially, we examined existing formulas in the literature for calculating the overall tilt angle. Subsequently, a new formula was derived, proven to better account for the actions of the double-tilt holder, thereby providing improved accuracy in the calculation. This newly derived formula has been implemented in the Landyne software suite. Furthermore, we demonstrated the accuracy of the new formula through examples. RESEARCH HIGHLIGHTS: A new formula has been derived to calculate overall tilt angles for side-entry double-tilt holders in TEM.

Self-designed portable dual-mode fluorescence device with custom python-based analysis software for rapid detection via dual-color FRET aptasensor with IoT capabilities.

An innovative aptasensor incorporating MoS2-modified bicolor quantum dots and a portable spectrometer, designed for the simultaneous detection of ochratoxin A (OTA) and aflatoxin B1 (AFB1) in corn was developed. Carbon dots and CdZnTe quantum dots were as nano-donors to label OTA and AFB1 aptamers, respectively. These labeled aptamers were subsequently attached to MoS2 receptors, enabling fluorescence resonance energy transfer (FRET). With targets, the labeled aptamers detached from the nano-donors, thereby disrupting the FRET process and resulting in fluorescence recovery. Furthermore, a portable dual-mode fluorescence detection system, complemented with customized python-based analysis software, was developed to facilitate rapid and convenient detection using this dual-color FRET aptasensor. The developed host program is connected to the spectrometer and transmits data to the cloud, enabling the device to have Internet of Things (IoT) characteristics. Connected to the cloud, this IoT-enabled device offers convenient and reliable fungal toxin detection for food safety.

CAS3D: 3D quantitative morphometry on Second Harmonic Generation image volumes from single skeletal muscle fibers.

The CAS3D image processing method intuitively applies a combination of Fourier space and real space 3D analysis algorithms to volumetric images of single skeletal muscle fiber Myosin II Second Harmonic Generation (SHG) XYZ image data. Our developed tool automatically quantifies the myofibrillar orientation in muscle samples by determining the cosine angle sum of intensity gradients in 3D (CAS3D) while determining the mean sarcomere length (SL) and sample orientation. The expected CAS3D values could be reproduced from ideal artificial data sets. Applied random noise in artificial images lowers the detected CAS3D value, and for noise levels below 20%, the correlation can be approximated by a linear function with a slope of -0.006 CAS3D/noise%. The deviations in SL and orientation detection were determined on ideal and noisy artificial data sets and were statistically indistinguishable from 0 (null hypothesis t-test P > 0.1). The software was applied to a previously published data set of single skeletal muscle fiber volumetric SHG image data from a rat intensive care unit (ICU) model of ventilator-induced diaphragm dysfunction (VIDD) with treatment regimens involving the small anti-inflammatory molecules BGP-15, vamorolone, or prednisolone. Our method reliably reproduced the results of the previous work and improved the standard deviation of the cosine angle sum detection in all sample groups from a mean of 0.03 to 0.008. This improvement is achieved by applying analysis algorithms to the whole volumetric images in 3D in contrast to the previously common method of slice-wise XY analysis.

A Virtual Testing Framework for Real-Time Validation of Automotive Software Systems Based on Hardware in the Loop and Fault Injection.

To validate safety-related automotive software systems, experimental tests are conducted at different stages of the V-model, which are referred as "X-in-the-loop (XIL) methods". However, these methods have significant drawbacks in terms of cost, time, effort and effectiveness. In this study, based on hardware-in-the-loop (HIL) simulation and real-time fault injection (FI), a novel testing framework has been developed to validate system performance under critical abnormal situations during the development process. The developed framework provides an approach for the real-time analysis of system behavior under single and simultaneous sensor/actuator-related faults during virtual test drives without modeling effort for fault mode simulations. Unlike traditional methods, the faults are injected programmatically and the system architecture is ensured without modification to meet the real-time constraints. Moreover, a virtual environment is modeled with various environmental conditions, such as weather, traffic and roads. The validation results demonstrate the effectiveness of the proposed framework in a variety of driving scenarios. The evaluation results demonstrate that the system behavior via HIL simulation has a high accuracy compared to the non-real-time simulation method with an average relative error of 2.52. The comparative study with the state-of-the-art methods indicates that the proposed approach exhibits superior accuracy and capability. This, in turn, provides a safe, reliable and realistic environment for the real-time validation of complex automotive systems at a low cost, with minimal time and effort.

Artificial Vision System on Digital Devices for Real-Time Head Tilt Control.

It is common to see cases in which, when performing tasks in close vision in front of a digital screen, the posture or position of the head is not adequate, especially in young people; it is essential to have a correct posture of the head to avoid visual, muscular, or joint problems. Most of the current systems to control head inclination require an external part attached to the subject's head. The aim of this study is the validation of a procedure that, through a detection algorithm and eye tracking, can control the correct position of the head in real time when subjects are in front of a digital device. The system only needs a digital device with a CCD receiver and downloadable software through which we can detect the inclination of the head, indicating if a bad posture is adopted due to a visual problem or simply inadequate visual-postural habits, alerting us to the postural anomaly to correct it.The system was evaluated in subjects with disparate interpupillary distances, at different working distances in front of the digital device, and at each distance, different tilt angles were evaluated. The system evaluated favorably in different lighting environments, correctly detecting the subjects' pupils. The results showed that for most of the variables, particularly good absolute and relative reliability values were found when measuring head tilt with lower accuracy than most of the existing systems. The evaluated results have been positive, making it a considerably inexpensive and easily affordable system for all users. It is the first application capable of measuring the head tilt of the subject at their working or reading distance in real time by tracking their eyes.

Per-Pixel Forest Attribute Mapping and Error Estimation: The Google Earth Engine and R dataDriven Tool.

Remote sensing products are typically assessed using a single accuracy estimate for the entire map, despite significant variations in accuracy across different map areas or classes. Estimating per-pixel uncertainty is a major challenge for enhancing the usability and potential of remote sensing products. This paper introduces the dataDriven open access tool, a novel statistical design-based approach that specifically addresses this issue by estimating per-pixel uncertainty through a bootstrap resampling procedure. Leveraging Sentinel-2 remote sensing data as auxiliary information, the capabilities of the Google Earth Engine cloud computing platform, and the R programming language, dataDriven can be applied in any world region and variables of interest. In this study, the dataDriven tool was tested in the Rincine forest estate study area-eastern Tuscany, Italy-focusing on volume density as the variable of interest. The average volume density was 0.042, corresponding to 420 m3 per hectare. The estimated pixel errors ranged between 93 m3 and 979 m3 per hectare and were 285 m3 per hectare on average. The ability to produce error estimates for each pixel in the map is a novel aspect in the context of the current advances in remote sensing and forest monitoring and assessment. It constitutes a significant support in forest management applications and also a powerful communication tool since it informs users about areas where map estimates are unreliable, at the same time highlighting the areas where the information provided via the map is more trustworthy. In light of this, the dataDriven tool aims to support researchers and practitioners in the spatially exhaustive use of remote sensing-derived products and map validation.

An Enhanced FGI-GSRx Software-Defined Receiver for the Execution of Long Datasets.

The Global Navigation Satellite System (GNSS) software-defined receivers offer greater flexibility, cost-effectiveness, customization, and integration capabilities compared to traditional hardware-based receivers, making them essential for a wide range of applications. The continuous evolution of GNSS research and the availability of new features require these software-defined receivers to upgrade continuously to facilitate the latest requirements. The Finnish Geospatial Research Institute (FGI) has been supporting the GNSS research community with its open-source implementations, such as a MATLAB-based GNSS software-defined receiver `FGI-GSRx' and a Python-based implementation `FGI-OSNMA' for utilizing Galileo's Open Service Navigation Message Authentication (OSNMA). In this context, longer datasets are crucial for GNSS software-defined receivers to support adaptation, optimization, and facilitate testing to investigate and develop future-proof receiver capabilities. In this paper, we present an updated version of FGI-GSRx, namely, FGI-GSRx-v2.0.0, which is also available as an open-source resource for the research community. FGI-GSRx-v2.0.0 offers improved performance as compared to its previous version, especially for the execution of long datasets. This is carried out by optimizing the receiver's functionality and offering a newly added parallel processing feature to ensure faster capabilities to process the raw GNSS data. This paper also presents an analysis of some key design aspects of previous and current versions of FGI-GSRx for a better insight into the receiver's functionalities. The results show that FGI-GSRx-v2.0.0 offers about a 40% run time execution improvement over FGI-GSRx-v1.0.0 in the case of the sequential processing mode and about a 59% improvement in the case of the parallel processing mode, with 17 GNSS satellites from GPS and Galileo. In addition, an attempt is made to execute v2.0.0 with MATLAB's own parallel computing toolbox. A detailed performance comparison reveals an improvement of about 43% in execution time over the v2.0.0 parallel processing mode for the same GNSS scenario.

Accuracy of Digital Imaging Software to Predict Soft Tissue Changes during Orthodontic Treatment.

This study aimed to evaluate the accuracy of the Digital Imaging software in the prediction of soft tissue changes following three types of orthodontic interventions: non-extraction, extraction, and orthognathic surgery treatments. Ninety-six patients were randomly selected from the records of three orthodontic interventions (32 subjects per group): (1) non-extraction, (2) extraction, and (3) orthodontic treatment combined with orthognathic surgery. The cephalometric analysis of soft tissue changes in both the actual post-treatment and the predicted treatment was performed using Dolphin Imaging software version 11.9. A paired t-test was utilized to assess the statistically significant differences between the predicted and actual treatment outcomes of the parameters (p < 0.05). In the non-extraction group, prediction errors were exhibited only in the lower lip parameters. In the extraction group, prediction errors were observed in both the upper and lower lip parameters. In the orthognathic surgery group, prediction errors were identified in chin thickness, facial contour angle, and upper and lower lip parameters (p < 0.05). Digital Imaging software exhibited inaccurate soft tissue prediction of 0.3-1.0 mm in some parameters of all treatment groups, which should be considered regarding the application of Dolphin Imaging software in orthodontic treatment planning.

Advances in 3D Inner Ear Reconstruction Software for Cochlear Implants: A Comprehensive Review.

Auditory impairment stands as a pervasive global issue, exerting significant effects on individuals' daily functioning and interpersonal engagements. Cochlear implants (CIs) have risen as a cutting-edge solution for severe to profound hearing loss, directly stimulating the auditory nerve with electrical signals. The success of CI procedures hinges on precise pre-operative planning and post-operative evaluation, highlighting the significance of advanced three-dimensional (3D) inner ear reconstruction software. Accurate pre-operative imaging is vital for identifying anatomical landmarks and assessing cochlear deformities. Tools like 3D Slicer, Amira and OTOPLAN provide detailed depictions of cochlear anatomy, aiding surgeons in simulating implantation scenarios and refining surgical approaches. Post-operative scans play a crucial role in detecting complications and ensuring CI longevity. Despite technological advancements, challenges such as standardization and optimization persist. This review explores the role of 3D inner ear reconstruction software in patient selection, surgical planning, and post-operative assessment, tracing its evolution and emphasizing features like image segmentation and virtual simulation. It addresses software limitations and proposes solutions, advocating for their integration into clinical practice. Ultimately, this review underscores the impact of 3D inner ear reconstruction software on cochlear implantation, connecting innovation with precision medicine.

Evaluation of novel open-source software for cardiac optical mapping.

KairoSight-3.0 is a recently released Python-based, open-source software for cardiac optical mapping analysis. Addressing challenges in high-resolution electrophysiological data analysis, KairoSight-3.0 facilitates comprehensive studies of cardiac conduction and excitation-contraction coupling. We compared its performance with ElectroMap, focusing on action potential duration and conduction velocity measurements in mouse heart models subjected to ischaemia and flecainide treatment. Our findings reveal that while both software are effective, inherent methodological differences impact measurement outcomes. KairoSight-3.0's robust analysis capabilities make it a valuable tool in cardiac research. Additionally, future directions for KairoSight-3.0 and other mapping analysis tools are explored. Statement of importance: Open-source methods for analysis of cardiac optical mapping are vital tools in electrophysiological research. Our work directly evaluates the latest version of KarioSight, recently published in JMCC plus, with ElectroMap, an established and widely used tool. Our results show both software are effective in analysis of changes in both conduction and repolarisation. Considering the new features of KairoSight-3.0 and python implementation, our study importantly demonstrates the effectiveness of the software, highlights potential discrepancies between it and ElectroMap, and provides a perspective on future directions for KairoSight-3.0 and other software.

SIPAS: A comprehensive susceptibility imaging process and analysis studio.

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Evaluation of the resection plane three-dimensional positional accuracy using a resection guide directional guidance slot; a randomized clinical trial.

AIM: The study was performed to compare the mandibular resection guide with a directional guidance slot with the conventional guide regarding three-dimensional positional accuracy. MATERIALS AND METHODS: Twenty-six patients with lateral segmental mandibular defects were selected, and randomly allocated into two groups. All defects were managed with preoperative virtual surgical planning. Resection in the test group was conducted using a resection guide with a directional guidance slot, while a conventional resection guide design was utilized in the control group. The linear and angular deviation of the osteotomy planes was analyzed for both groups, along with the accuracy of the insertion of the reconstruction bone block in the resected defect. Data were documented, absolute deviation was calculated, statistical analysis was performed and significance was set at the 5% level. RESULTS: The cases conducted with a directional guidance templet reported a statistically significant difference when compared to the conventional edge-cutting guide regarding the linear and angular spatial osteotomy plane position (P < 0.001). The defect span analysis reported excellent levels of agreement in both groups (ICC = 1.00, ICC = 0.995), however, the difference between the groups was statistically significant (P < 0.001). CONCLUSION: The study demonstrated the enhanced positional accuracy of the resection plane and reconstruction block placement when a directional slot is incorporated in the computer-generated resection guide.

Utilizing two different sustainable and green spectrophotometric approaches using derivative ratio spectra for the determination of a ternary severely overlapped mixture: application to veterinary formulation.

Mathematical manipulation technique has proven to be a very powerful tool for efficient processing and handling of highly overlapped spectra. This work introduced two green and sustainable approaches for the successful recovery of the ternary mixture, Tylosin tartarate (TYL), Sulfadimdine (SLD), and Trimethoprim (TRI). The approaches were constructed using three different methods, derivative ratio spectrum zero-crossing method (DRSZ), double divisor ratio spectra derivative method (DDRD), and factorized derivative ratio method coupled with spectrum subtraction (FDRM-SS). The two approaches succeeded in recovering the three drugs (Linearity range achieved were 0.5-5 µg/mL for TYL, 0.3-1.3 µg/mL for SLD, and 0.3-5 µg/mL for TRI), giving convenient standard deviations and satisfactory recovery percentages. The recommended methods have been verified in accordance with (ICH) guidelines. When the results were statistically compared to the official methods, no significant difference was found. Both AGREE-Analytical GREEnness Metric Approach and Software, and White Analytical Chemistry (WAC) RGB model gave scores of 0.93 and 97.2%, respectively, which proved that the approaches were eco-friendly and abiding by the sustainability principles.

Quality assurance of an established online adaptive radiotherapy program: patch and software upgrade.

Introduction: The ability to dynamically adjust target contours, derived Boolean structures, and ultimately, the optimized fluence is the end goal of online adaptive radiotherapy (ART). The purpose of this work is to describe the necessary tests to perform after a software patch installation and/or upgrade for an established online ART program. Methods: A patch upgrade on a low-field MR Linac system was evaluated for post-software upgrade quality assurance (QA) with current infrastructure of ART workflow on (1) the treatment planning system (TPS) during the initial planning stage and (2) the treatment delivery system (TDS), which is a TPS integrated into the delivery console for online ART planning. Online ART QA procedures recommended for post-software upgrade include: (1) user interface (UI) configuration; (2) TPS beam model consistency; (3) segmentation consistency; (4) dose calculation consistency; (5) optimizer robustness consistency; (6) CT density table consistency; and (7) end-to-end absolute ART dose and predicted dose measured including interruption testing. Differences of calculated doses were evaluated through DVH and/or 3D gamma comparisons. The measured dose was assessed using an MR-compatible A26 ionization chamber in a motion phantom. Segmentation differences were assessed through absolute volume and visual inspection. Results: (1) No UI configuration discrepancies were observed. (2) Dose differences on TPS pre-/post-software upgrade were within 1% for DVH metrics. (3) Differences in segmentation when observed were small in general, with the largest change noted for small-volume regions of interest (ROIs) due to partial volume impact. (4) Agreement between TPS and TDS calculated doses was 99.9% using a 2%/2-mm gamma criteria. (5) Comparison between TPS and online ART plans for a given patient plan showed agreement within 2% for targets and 0.6 cc for organs at risk. (6) Relative electron densities demonstrated comparable agreement between TPS and TDS. (7) ART absolute and predicted measured end-to-end doses were within 1% of calculated TDS. Discussion: An online ART QA program for post-software upgrade has been developed and implemented on an MR Linac system. Testing mechanics and their respective baselines may vary across institutions, but all necessary components for a post-software upgrade QA have been outlined and detailed. These outlined tests were demonstrated feasible for a low-field MR Linac system; however, the scope of this work may be applied and adapted more broadly to other online ART platforms.