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Purpose: Conventional computed tomography (CT) images are severely affected by metal artifacts in patients with intracranial coils. Monoenergetic images have been suggested to reduce metal artifacts.The aim of this study was to assess metal artifacts in virtual monoenergetic images (VMIs) reconstructed from spectral brain CT. Methods: Thirty-two consecutive patients with intracranial coils examined by spectral non contrast brain CT (NCCT) at our center between November 2017 and April 2019 were included. Attenuation and standard deviations were measured in regions of interest (ROIs) at predefined areas in artifact-free and artifact-affected areas. Measurements were performed in conventional polyenergetic images (CIs) and the corresponding data for VMIs were retrieved through spectral diagrams for the each ROI. Subjective analysis was performed by visual grading of CIs and specific VMIs by two neuroradiologists, independently. Results: In artefact-affected image areas distal from the metal objects, the attenuation values decreased with higher energy level VMIs. The same effect was not seen for artefact-affected image areas close to the metal.Subjective rating of the artefact severity was significantly better in VMIs at 50 keV for one of the two reviewers compared to the CIs. Overall image quality and tissue differentiation scores were significantly higher for both reviewers in VMIs at 60 and 70 keV compared to CIs. Conclusion: Our quantitative and qualitative image analysis shown that there is a small significant reduction of intracranial coils artifacts severity by all monoenergetic reconstructions from 50 to 200 keV with preserved or increased overall subjective image quality compared to conventional images.

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Purpose: To study the growth model, shape, and developmental relationship of lens and eyeball, we used two-dimensional Magnetic Resonance (MR) imaging to investigate gestationally age-related changes in the selected ocular parameters in vivo. Materials and methods: We retrospectively reviewed the MR images from 126 fetuses ranging from 21 to 39 weeks' gestation. Ocular parameters on MR imaging of transverse plane were measured including lens diameter (LD), anteroposterior lens diameter (APLD), lens surface area (LS), globe diameter (GD), anteroposterior globe diameter (APGD), globe surface area (GS). The growth model of each biometric against gestational age (GA), aspect ratio of lens and globe (LD/APLD and GD/APGD), and growing relationship between the ratio of lens and globe surface area (LS/GS) were studied by statistical analysis. Results: The growth model of most biometry for gestational age is logarithmic, except for the diameter of the ocular globe (GD and APGD) showing a quadratic growth pattern. Our study showed that the lens was consistently larger in the transverse than the anteroposterior diameters during 21-39 weeks(P < 0.001). Besides, the ratio of surface area (LS/GS) was not significantly changing with GA(P = 0.4908), while the increase of LS was significantly accorded with that of GS(P < 0.001). Conclusion: The lens shape throughout fetal life may take part in the process, shape changing from vertical ellipsoid, spherical to transversal ellipsoid, based on the logarithmically increased ratio of lens transverse and anteroposterior diameters. In the meanwhile, the aspect ratio of eyeball in late fetal life may imply a gradually spherical shape during gestation. Nomogram data from this study may provide appropriate information about morphological changes in the fetal lens and the synchronous relationship between lens and eyeball.

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Genome-scale studies of the bacterial regulatory network have been leveraged by declining sequencing cost and advances in ChIP (chromatin immunoprecipitation) methods. Of which, ChIP-exo has proven competent with its near-single base-pair resolution. While several algorithms and programs have been developed for different analytical steps in ChIP-exo data processing, there is a lack of effort in incorporating them into a convenient bioinformatics pipeline that is intuitive and publicly available. In this paper, we developed ChIP-exo Analysis Pipeline (ChEAP) that executes the one-step process, starting from trimming and aligning raw sequencing reads to visualization of ChIP-exo results. The pipeline was implemented on the interactive web-based Python development environment - Jupyter Notebook, which is compatible with the Google Colab cloud platform to facilitate the sharing of codes and collaboration among researchers. Additionally, users could exploit the free GPU and CPU resources allocated by Colab to carry out computing tasks regardless of the performance of their local machines. The utility of ChEAP was demonstrated with the ChIP-exo datasets of RpoN sigma factor in E. coli K-12 MG1655. To analyze two raw data files, ChEAP runtime was 2 min and 25 s. Subsequent analyses identified 113 RpoN binding sites showing a conserved RpoN binding pattern in the motif search. ChEAP application in ChIP-exo data analysis is extensive and flexible for the parallel processing of data from various organisms.

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Objective: To prospectively evaluate the image quality and diagnostic performance of a compact flat-panel detector (FD) scanner for thoracic diseases compared to a clinical CT scanner. Materials and methods: The institutional review board approved this single-center prospective study, and all participants provided informed consent. From December 2020 to May 2021, 30 patients (mean age, 67.1 ± 8.3 years) underwent two same-day low-dose chest CT scans using clinical state-of-art and compact FDCT scanners. Image quality was assessed visually and quantitatively. Two readers evaluated the diagnostic performance for nodules, parenchymal opacifications, bronchiectasis, linear opacities, and pleural abnormalities in 40 paired CT scans. The other 20 paired CT scans were used to examine the agreement of semi-quantitative CT scoring regarding bronchiectasis, bronchiolitis, nodules, airspace consolidations, and cavities. Results: FDCT images had significantly lower visual image quality than clinical CT images (all p < 0.001). The two CT image sets showed no significant differences in signal-to-noise and contrast-to-noise ratios (56.8 ± 12.5 vs. 57.3 ± 15.2; p = 0.985 and 62.9 ± 11.7 vs. 60.7 ± 16.9; p = 0.615). The pooled sensitivity was comparable for nodules, parenchymal opacifications, linear opacities, and pleural abnormalities (p = 0.065-0.625), whereas the sensitivity was significantly lower in FDCT images than in clinical CT images for micronodules (p = 0.007) and bronchiectasis (p = 0.004). The specificity was mostly 1.0. Semi-quantitative CT scores were similar between the CT image sets (p > 0.05), and intraclass correlation coefficients were around 0.950 or higher, except for bronchiectasis (0.869). Conclusion: Compact FDCT images provided lower image quality but comparable diagnostic performance to clinical CT images for nodules, parenchymal opacifications, linear opacities, and pleural abnormalities.

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Background and purpose: Diagnostic information about cell density variations and microscopic tissue anisotropy can be gained from tensor-valued diffusion magnetic resonance imaging (MRI). These properties of tissue microstructure have the potential to become novel imaging biomarkers for radiotherapy response. However, tensor-valued diffusion encoding is more demanding than conventional encoding, and its compatibility with MR scanners that are dedicated to radiotherapy has not been established. Thus, our aim was to investigate the feasibility of tensor-valued diffusion MRI with radiotherapy dedicated MR equipment. Material and methods: A tensor-valued diffusion protocol was implemented, and five healthy volunteers were scanned with different resolutions using conventional head coil and radiotherapy coil setup with fixation masks. Signal-to-noise-ratio (SNR) was evaluated to assess the risk of signal bias due to rectified noise floor. We also evaluated the repeatability and reproducibility of the microstructure parameters. One patient with brain metastasis was scanned to investigate the image quality and the transferability of the setup to diseased tissue. Results: A resolution of 3 × 3 × 3 mm3 provided images with SNR > 3 for 93 % of the voxels using radiotherapy coil setup. The parameter maps and repeatability characteristics were comparable to those observed with a conventional head coil. The patient evaluation demonstrated successful parameter analysis also in tumor tissue, with SNR > 3 for 93 % of the voxels. Conclusion: We demonstrate that tensor-valued diffusion MRI is compatible with radiotherapy fixation masks and coil setup for investigations of microstructure parameters. The reported reproducibility may be used to plan future investigations of imaging biomarkers in brain cancer radiotherapy.

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Purpose: Motion artifacts caused by breathing or involuntary motion of patients, which may lead to reduced image quality and a loss of diagnostic information, are a major problem in shoulder magnetic resonance imaging (MRI). The MultiVane (MV) technique decreases motion artifacts; however, it tends to prolong the acquisition time. As a parallel imaging technique, SENSitivity Encoding (SENSE) can be combined with the compressed sensing method to produce compressed SENSE (C-SENSE), resulting in a markedly reduced acquisition time. This study aimed to evaluate the use of C-SENSE MV for MRI of the shoulder joint. Methods: Thirty-one patients who were scheduled to undergo MRI of the shoulder were included. This prospective study was approved by our institution's medical ethics committee, and written informed consent was obtained from all 31 patients. Two sets of oblique coronal images derived from the standard protocol were acquired without (standard) or with C-SENSE MV: proton-density weighted imaging (PDWI), PDWI with C-SENSE MV, T2-weighted imaging (T2WI) with fat suppression (fs), and T2WI fs with C-SENSE MV. Two radiologists graded motion artifacts and the detectability of anatomical shoulder structures on a 4-point scale (3, no artifacts/excellent delineation; 0, severe artifacts/difficulty with delineation). The Wilcoxon signed-rank test was used to compare the data for the standard and C-SENSE MV images. Results: Motion artifacts were significantly reduced on the C-SENSE MV images (p < 0.001). Regarding the detectability of anatomical structures, the ratings for the C-SENSE MV sequences were significantly better (p < 0.001).In conclusion, in shoulder MRI the newly developed C-SENSE MV technique reduces motion artifacts and increases the detectability of anatomical structures compared with standard sequences.

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Significant advances in the past decade have enabled high-resolution structure determination of a vast variety of proteins by cryogenic electron microscopy single particle analysis. Despite improved sample preparation, next-generation imaging hardware, and advanced single particle analysis algorithms, small proteins remain elusive for reconstruction due to low signal-to-noise and lack of distinctive structural features. Multiple efforts have therefore been directed at the development of size-increase techniques for small proteins. Here we review the latest methods for increasing effective molecular weight of proteins <100 â€‹kDa through target protein binding or target protein fusion - specifically by using nanobody-based assemblies, fusion tags, and symmetric scaffolds. Finally, we summarize these state-of-the-art techniques into a decision-tree to facilitate the design of tailored future approaches, and thus for further exploration of ever-smaller proteins that make up the largest part of the human genome.

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This study presents a system-level optimization of spectroscopic photoacoustic (PA) imaging for prostate cancer (PCa) detection in three folds. First, we present a spectral unmixing model to segregate spectral system error (SSE). We constructed two noise models (NMs) for the laser spectrotemporal fluctuation and the ultrasound system noise. We used these NMs in linear spectral unmixing to denoise and to achieve high temporal resolution. Second, we employed a simulation-aided wavelength optimization to select the most effective subset of wavelengths. NMs again were considered so that selected wavelengths were not only robust to the collinearity of optical absorbance, but also to noise. Third, we quantified the effect of frame averaging on improving spectral unmixing accuracy through theoretical analysis and numerical validation. To validate the whole framework, we performed comprehensive studies in simulation and an in vivo experiment which evaluated prostate-specific membrane antigen (PSMA) expression in PCa on a mice model. Both simulation analysis and in vivo studies confirmed that the proposed framework significantly enhances image signal-to-noise ratio (SNR) and spectral unmixing accuracy. It enabled more sensitive and faster PCa detection. Moreover, the proposed framework can be generalized to other spectroscopic PA imaging studies for noise reduction, wavelength optimization, and higher temporal resolution.

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A new artificial intelligence (AI) supported T-Ray imaging system designed and implemented for non-invasive and non-ionizing screening for coronavirus-affected patients. The new system has the potential to replace the standard conventional X-Ray based imaging modality of virus detection. This research article reports the development of solid state room temperature terahertz source for thermograph study. Exposure time and radiation energy are optimized through several real-time experiments. During its incubation period, Coronavirus stays within the cell of the upper respiratory tract and its presence often causes an increased level of blood supply to the virus-affected cells/inter-cellular region that results in a localized increase of water content in those cells & tissues in comparison to its neighbouring normal cells. Under THz-radiation exposure, the incident energy gets absorbed more in virus-affected cells/inter-cellular region and gets heated; thus, the sharp temperature gradient is observed in the corresponding thermograph study. Additionally, structural changes in virus-affected zones make a significant contribution in getting better contrast in thermographs. Considering the effectiveness of the Artificial Intelligence (AI) analysis tool in various medical diagnoses, the authors have employed an explainable AI-assisted methodology to correctly identify and mark the affected pulmonary region for the developed imaging technique and thus validate the model. This AI-enabled non-ionizing THz-thermography method is expected to address the voids in early COVID diagnosis, at the onset of infection.

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Introduction: The prognosis for cervical cancer (CC) patients with lymph node metastasis (LNM) is extremely poor. Lipid droplets (LDs) have a pivotal role in promoting tumor metastasis. The crosstalk mechanism between LDs and LNM modulated in CC remains largely unknown. Objectives: This study aimed to construct a miRNA-dependent progonostic model for CC patients and investigate whether miR-532-5p has a biological impact on LNM by regualting LDs accumulation. Methods: LASSO-Cox regression was applied to establish a prognostic prediction model. miR-532-5p had the lowest P-value in RNA expression (P < 0.001) and prognostic prediction (P < 0.0001) and was selected for further study. The functional role of the prognostic miR-532-5p-correlated competing endogenous RNA (ceRNA) network was investigated to clarify the crosstalk between LDs and LNM. The underlying mechanism was determined using site-directed mutagenesis, dual luciferase reporter assays, RNA immunoprecipitation assays, and rescue experiments. A xenograft LNM model was established to evaluate the effect of miR-532-5p and orlistat combination therapy on tumor growth and LNM. Results: A novel 5-miRNAs prognostic signature was constructed to better predict the prognosis of CC patient. Further study demonstrated that miR-532-5p inhibited epithelial-mesenchymal transition and lymphangiogenesis by regulating LDs accumulation. Interestingly, we also found that LDs accumulation promoted cell metastasis in vitro. Mechanistically, we demonstrated a miR-532-5p-correlated ceRNA network in which LINC01410 was bound directly to miR-532-5p and effectively functioned as miR-532-5p sponge to disinhibit its target gene-fatty acid synthase (FASN). Combined therapy with miR-532-5p and FASN inhibitor-orlistat further inhibited tumor growth and LNM in vivo. Conclusion: Our findings highlight a LD accumulation-dependent mechanism of miR-532-5p-modulated LNM and support treatment with miR-532-5p/orlistat as novel strategy for treating patients with LNM in CC.

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Mass spectrometry imaging (MSI) has emerged as a rapidly expanding field in the MS community. The analysis of large spectral data is further complicated by the added spatial dimension of MSI. A plethora of resources exist for expert users to begin parsing MSI data in R, but there is a critical lack of guidance for absolute beginners. This tutorial is designed to serve as a one-stop guide to start using R with MSI data and describe the possibilities that data science can bring to MSI analysis.

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High-frequency hearing above 5000 Hz improves the detection and discrimination of high frequency phonemes. Improved access to high-frequency hearing may be particularly advantageous in unilaterally deafened listeners who experience reduced access to high frequency speech cues on their impaired side and decreased speech perception abilities in competing noise. This study aimed to investigate the effects of extended high-frequency bandwidth on speech perception in unilaterally deafened osseointegrated bone conduction hearing device recipients. To study the effect of extended high-frequency bandwidth, participants underwent aided testing in narrow bandwidth and extended high-frquency bandwidth BCD listening conditions. Aided word and phoneme recognition in quiet was assessed at soft and conversational speech levels with the better ear plugged. Aided thresholds and Ling 6 phoneme sounds were also assessed in quiet with the better ear plugged. Speech perception in noise was assessed at ± 90° and co-located at 0° using the adaptive Hearing in Noise Test. Findings demonstrate a significant improvement in speech perception outcomes when listening with extended high-frequency bandwidth. Extended high-frequency bandwidth significantly improved word and phoneme recognition for soft and average conversational speech. The largest effects were observed for voiceless phonemes. Results suggest use of bone conduction devices with extended high-frequency bandwidth result in improved hearing outcomes when compared with narrow bandwidth bone conduction devices.

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PURPOSE: Numerous brain MR imaging studies have been performed to understand radiation-induced cognitive decline. However, many of them focus on a single region of interest, e.g. cerebral cortex or hippocampus. In this study, we use deformation-based morphometry (DBM) and voxel-based morphometry (VBM) to measure the morphological changes in patients receiving fractionated photon RT, and relate these to the dose. Additionally, we study tissue specific volume changes in white matter (WM), grey matter (GM), cerebrospinal fluid and total intracranial volume (TIV). METHODS AND MATERIALS: From our database, we selected 28 patients with MRI of high quality available at baseline and 1 year after RT. Scans were rigidly registered to each other, and to the planning CT and dose file. We used DBM to study non-tissue-specific volumetric changes, and VBM to study volume loss in grey matter. Observed changes were then related to the applied radiation dose (in EQD2). Additionally, brain tissue was segmented into WM, GM and cerebrospinal fluid, and changes in these volumes and TIV were tested. RESULTS: Performing DBM resulted in clusters of dose-dependent volume loss 1 year after RT seen throughout the brain. Both WM and GM were affected; within the latter both cerebral cortex and subcortical nuclei show volume loss. Volume loss rates ranging from 5.3 to 15.3%/30 Gy were seen in the cerebral cortical regions in which more than 40% of voxels were affected. In VBM, similar loss rates were seen in the cortex and nuclei. The total volume of WM and GM significantly decreased with rates of 5.8% and 2.1%, while TIV remained unchanged as expected. CONCLUSIONS: Radiotherapy is associated with dose-dependent intracranial morphological changes throughout the entire brain. Therefore, we will consider to revise sparing of organs at risk based on future cognitive and neurofunctional data.

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PURPOSE: To prospectively compare artefacts and image quality in testicular stage I cancer patients using different combinations of breathing schemes and Multi-band (MB) in whole-body DWIBS at 1.5 T.Diffusion-Weighted whole-body Imaging with Background body signal Suppression (DWIBS) using inversion recovery (IR) fat saturation is a cornerstone in oncologic whole-body MRI, but implementation is restrained by long acquisition times. The new Multi-Band (MB) technique reduces scan time which can be reinvested in respiratory compensation. METHODS: Thirty testicular cancer stage I patients were included. Three variations of whole-body DWIBS were tested: Standard free Breathing (FB)-DWIBS, FB-MB-DWIBS and Respiratory triggered (RT)-MB-DWIBS. Artefacts and image quality of b = 800 s/mm2 images were evaluated using a Likert scale. No pathology was revealed. SNR was calculated in a healthy volunteer. RESULTS: RT-MB-DWIBS was rated significantly better than FB-DWIBS in the thorax (p < 0.001) and abdomen (p < 0.001), but not in the pelvis (p = 0.569). FB-MB-DWIBS was ranked significantly lower than both FB-DWIBS (p < 0.001) and RT-MB-DWIBS (p < 0.001) at all locations. However, FB-MB-DWIBS was scanned in half the time without being less than "satisfactory". Few artefacts were encountered. SNR was similar for low-intensity tissues, but the SNR in high-intensity and respiratory-prone tissue (spleen) was slightly lower for FB-DWIBS than the other sequences. CONCLUSION: Images produced by the sequences were similar. MB enables the use of respiratory trigger or can be used to produce very fast free-breathing DWI with acceptable image quality.

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Measuring neuroactivity underlying complex behaviors facilitates understanding the microcircuitry that supports these behaviors. We have developed a functional and molecular photoacoustic tomography (F/M-PAT) system which allows direct imaging of Fos-expressing neuronal ensembles in Fos-LacZ transgenic rats with a large field-of-view and high spatial resolution. F/M-PAT measures the beta-galactosidase catalyzed enzymatic product of exogenous chromophore X-gal within ensemble neurons. We used an ex vivo imaging method in the Wistar Fos-LacZ transgenic rat, to detect neuronal ensembles in medial prefrontal cortex (mPFC) following cocaine administration or a shock-tone paired stimulus. Robust and selective F/M-PAT signal was detected in mPFC neurons after both conditions (compare to naive controls) demonstrating successful and direct detection of Fos-expressing neuronal ensembles using this approach. The results of this study indicate that F/M-PAT can be used in conjunction with Fos-LacZ rats to monitor neuronal ensembles that underlie a range of behavioral processes, such as fear learning or addiction.

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The 18 kDa translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is predominately localized to the outer mitochondrial membrane in steroidogenic cells. Brain TSPO expression is relatively low under physiological conditions, but is upregulated in response to glial cell activation. As the primary index of neuroinflammation, TSPO is implicated in the pathogenesis and progression of numerous neuropsychiatric disorders and neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), multiple sclerosis (MS), major depressive disorder (MDD) and obsessive compulsive disorder (OCD). In this context, numerous TSPO-targeted positron emission tomography (PET) tracers have been developed. Among them, several radioligands have advanced to clinical research studies. In this review, we will overview the recent development of TSPO PET tracers, focusing on the radioligand design, radioisotope labeling, pharmacokinetics, and PET imaging evaluation. Additionally, we will consider current limitations, as well as translational potential for future application of TSPO radiopharmaceuticals. This review aims to not only present the challenges in current TSPO PET imaging, but to also provide a new perspective on TSPO targeted PET tracer discovery efforts. Addressing these challenges will facilitate the translation of TSPO in clinical studies of neuroinflammation associated with central nervous system diseases.

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PURPOSE: To evaluate the influence of body phased-array (BPA) receive coil setups on signal-to-noise ratio (SNR) and image quality (IQ) in prostate MRI. METHODS: This prospective study evaluated axial T2-weighted images (T2W-TSE) and DWI of the prostate in ten healthy volunteers with 18-channel (18CH), 30-channel and 60-channel (60CH) BPA receive coil setups. SNR and ADC values were assessed in the peripheral and transition zones (TZ). Two radiologists rated IQ features. Differences in qualitative and quantitative image features between BPA receive coil setups were compared. After correction for multiple comparisons, p-values <0.004 for quantitative and p-values <0.017 for qualitative image analysis were considered statistically significant. RESULTS: Significantly higher SNR was found in T2W-TSE images in the TZ using 60CH BPA compared to 18CH BPA coil setups (15.20 ± 4.22 vs. 7.68 ± 2.37; p = 0.001). There were no significant differences between all other quantitative (T2W-TSE, p = 0.007-0.308; DWI, p = 0.024-0.574) and qualitative image features (T2W-TSE, p = 0.083-1.0; DWI, p = 0.046-1.0). CONCLUSION: 60CH BPA receive coil setup showed marginal SNR improvement in T2W-TSE images. Good IQ could be achieved with 18CH BPA coil setups.

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Recent advances in dual-energy imaging techniques, dual-energy subtraction radiography (DESR) and dual-energy CT (DECT), offer new and useful additional information to conventional imaging, thus improving assessment of cardiothoracic abnormalities. DESR facilitates detection and characterization of pulmonary nodules. Other advantages of DESR include better depiction of pleural, lung parenchymal, airway and chest wall abnormalities, detection of foreign bodies and indwelling devices, improved visualization of cardiac and coronary artery calcifications helping in risk stratification of coronary artery disease, and diagnosing conditions like constrictive pericarditis and valvular stenosis. Commercially available DECT approaches are classified into emission based (dual rotation/spin, dual source, rapid kilovoltage switching and split beam) and detector-based (dual layer) systems. DECT provide several specialized image reconstructions. Virtual non-contrast images (VNC) allow for radiation dose reduction by obviating need for true non contrast images, low energy virtual mono-energetic images (VMI) boost contrast enhancement and help in salvaging otherwise non-diagnostic vascular studies, high energy VMI reduce beam hardening artifacts from metallic hardware or dense contrast material, and iodine density images allow quantitative and qualitative assessment of enhancement/iodine distribution. The large amount of data generated by DECT can affect interpreting physician efficiency but also limit clinical adoption of the technology. Optimization of the existing workflow and streamlining the integration between post-processing software and picture archiving and communication system (PACS) is therefore warranted.

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Purpose: Retinal toxicity resulting from hydroxychloroquine use manifests photoreceptor loss and disruption of the ellipsoid zone (EZ) reflectivity band detectable on spectral-domain (SD) OCT imaging. This study investigated whether an automatic deep learning-based algorithm can detect and quantitate EZ loss on SD OCT images with an accuracy comparable with that of human annotations. Design: Retrospective analysis of data acquired in a prospective, single-center, case-control study. Participants: Eighty-five patients (168 eyes) who were long-term hydroxychloroquine users (average exposure time, 14 ± 7.2 years). Methods: A mask region-based convolutional neural network (M-RCNN) was implemented and trained on individual OCT B-scans. Scan-by-scan detections were aggregated to produce an en face map of EZ loss per 3-dimensional SD OCT volume image. To improve the accuracy and robustness of the EZ loss map, a dual network architecture was proposed that learns to detect EZ loss in parallel using horizontal (horizontal mask region-based convolutional neural network [M-RCNNH]) and vertical (vertical mask region-based convolutional neural network [M-RCNNV]) B-scans independently. To quantify accuracy, 10-fold cross-validation was performed. Main Outcome Measures: Precision, recall, intersection over union (IOU), F1-score metrics, and measured total EZ loss area were compared against human grader annotations and with the determination of toxicity based on the recommended screening guidelines. Results: The combined projection network demonstrated the best overall performance: precision, 0.90 ± 0.09; recall, 0.88 ± 0.08; and F1 score, 0.89 ± 0.07. The combined model performed superiorly to the M-RCNNH only model (precision, 0.79 ± 0.17; recall, 0.96 ± 0.04; IOU, 0.78 ± 0.15; and F1 score, 0.86 ± 0.12) and M-RCNNV only model (precision, 0.71 ± 0.21; recall, 0.94 ± 0.06; IOU, 0.69 ± 0.21; and F1 score, 0.79 ± 0.16). The accuracy was comparable with the variability of human experts: precision, 0.85 ± 0.09; recall, 0.98 ± 0.01; IOU, 0.82 ± 0.12; and F1 score, 0.91 ± 0.06. Automatically generated en face EZ loss maps provide quantitative SD OCT metrics for accurate toxicity determination combined with other functional testing. Conclusions: The algorithm can provide a fast, objective, automatic method for measuring areas with EZ loss and can serve as a quantitative assistance tool to screen patients for the presence and extent of toxicity.

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Purpose: To assess the efficacy of an instrument-integrated OCT (iiOCT)-based distance sensor during robotic vitreoretinal surgery using the Preceyes Surgical System (PSS; Preceyes B.V.). Design: Single-center interventional study. Participants: Patients requiring vitreoretinal surgery. Methods: Five patients were enrolled. Standard preoperative OCT images were obtained. After vitrectomy, a predefined set of actions was performed using the iiOCT-based sensor. Images then were processed to assess the signal-to-noise ratio (SNR) at various angles to the retina and at different distances between the instrument tip and the retinal surface. Preoperative and intraoperative OCT images were compared qualitatively and quantitatively. Main Outcomes Measures: The feasibility in performing surgical tasks using the iiOCT-based sensor during vitreoretinal surgery, the SNR when imaging the retina, differences among intraoperative and preoperative OCT images, and characteristics of intraoperative retinal movements detected with the iiOCT-based probe. Results: Surgeons were able to perform all the tasks but one. The PSS was able to maintain a fixed distance. The SNR of the iiOCT-based sensor signal was adequate to determine the distance to the retina and to control the PSS. Analysis of iiOCT-based sensor A-scans identified 3 clearly distinguishable retinal layers, including the inner retinal boundary and the interface at the retinal pigment epithelium-Bruch's membrane. Thickness values differed by less than 5% from that measured by preoperative OCT, indicating its accuracy. The Fourier analysis of iiOCT-based sensor recordings identified anteroposterior retinal movements attributed to heartbeat and respiration. Conclusions: This iiOCT-based sensor was tested successfully and promises reliable use during robot-assisted surgery. An iiOCT-based sensor is a promising step toward OCT-guided robotic retinal surgery.