Purpose Manual segmentation of anatomical structures is the accepted “gold standard” for labeling structures in clinical images. However, the variability in manual segmentation of temporal bone structures in CBCT images of the temporal bone has not been systematically evaluated using multiple reviewers. Therefore, we evaluated the intravariability and intervariability of manual segmentation of inner ear structures in CBCT images of the temporal bone. Methods Preoperative CBCTs scans of the inner ear were obtained from 10 patients who had undergone cochlear implant surgery. The cochlea, facial nerve, chorda tympani, mid-modiolar (MM) axis, and round window (RW) were manually segmented by five reviewers in two separate sessions that were at least 1 month apart. Interreviewer and intrareviewer variabilities were assessed using the Dice coefficient (DICE), volume similarity, mean Hausdorff Distance metrics, and visual review. Results Manual segmentation of the cochlea was the most consistent within and across reviewers with a mean DICE of 0.91 (SD = 0.02) and 0.89 (SD = 0.01) respectively, followed by the facial nerve with a mean DICE of 0.83 (SD = 0.02) and 0.80 (SD = 0.03), respectively. The chorda tympani had the greatest amount of reviewer variability due to its thin size, and the location of the centroid of the RW and the MM axis were also quite variable between and within reviewers. Conclusions We observed significant variability in manual segmentation of some of the temporal bone structures across reviewers. This variability needs to be considered when interpreting the results in studies using one manual reviewer.

PURPOSE:This study utilized an automated segmentation algorithm to assess the cochlear implant electrode array within the cochlea and investigate its impact on audiologic outcomes as measured by post-operative speech perception scores. Furthermore, manual evaluations of electrode placement were compared to automatic segmentation methods to determine their accuracy in predicting post-operative audiologic outcomes.MATERIALS AND METHODS:This retrospective chart review was conducted at a tertiary care referral center involving adult post-lingually deafened cochlear implant recipients implanted from 2015 to 2019. Patients with appropriate postoperative imaging and speech testing were included. Patients were excluded if non-English speaking, had a cognitive deficit, or a labyrinthine malformation. Automated and manual methods were used to analyze computed tomography (CT) scans and correlate the findings with post-operative speech perception scores and detection of electrode translocation.RESULTS:Among the 47 patients who met inclusion criteria, 15 had electrode translocations confirmed by automatic segmentation methods. Controlling for CI usage and pre-operative AzBio scores, patients with translocation exhibited significantly lower consonant-nucleus consonant (CNC) and AzBio scores at 6-months post-implantation compared to patients with ST insertions. Moreover, the number of translocated electrode contacts was significantly associated with post-operative CNC scores. Manual evaluations of electrode location were predictive but less sensitive to electrode translocations when compared with automated 3D segmentation.CONCLUSIONS:Placement of CI electrode contacts within ST without translocation into SV, leads to improved audiologic outcomes. Manual assessment of electrode placement via temporal bone CT, without 3D reconstruction, provides a less sensitive method to determine electrode placement than automated methods.LEVEL OF EVIDENCE:Level 4.LAY SUMMARY:This study investigated the impact of electrode placement on speech outcomes for cochlear implant recipients. Using advanced imaging techniques, the researchers compared automated and manual methods for evaluating electrode position and examined the relationship between electrode translocation and audiologic outcomes. The findings revealed that proper placement within the cochlea without translocation into inappropriate compartments inside the cochlea improves speech understanding. Manual evaluations were somewhat accurate but less sensitive in detecting translocations compared to automated methods, which offer more precise predictions of patient outcomes. These results contribute to our understanding of factors influencing cochlear implant success and highlight the importance of optimizing electrode placement for improved speech outcomes.

OBJECTIVE:Patient-specific simulation allows the surgeon to plan and rehearse the surgical approach ahead of time. Preoperative clinical imaging for this purpose requires time-consuming manual processing and segmentation of landmarks such as the facial nerve. We aimed to evaluate an automated pipeline with minimal manual interaction for processing clinical cone-beam computed tomography (CBCT) temporal bone imaging for patient-specific virtual reality (VR) simulation.STUDY DESIGN:Prospective image processing of retrospective imaging series.SETTING:Academic hospital.METHODS:Eleven CBCTs were selected based on quality and used for validation of the processing pipeline. A larger naturalistic sample of 36 CBCTs were obtained to explore parameters for successful processing and feasibility for patient-specific VR simulation.Visual inspection and quantitative metrics were used to validate the accuracy of automated segmentation compared with manual segmentation. Range of acceptable rotational offsets and translation point selection variability were determined. Finally, feasibility in relation to image acquisition quality, processing time, and suitability for VR simulation was evaluated.RESULTS:The performance of automated segmentation was acceptable compared with manual segmentation as reflected in the quantitative metrics. Total time for processing for new data sets was on average 8.3 minutes per data set; of this, it was less than 30 seconds for manual steps. Two of the 36 data sets failed because of extreme rotational offset, but overall the registration routine was robust to rotation and manual selection of a translational reference point. Another seven data sets had successful automated segmentation but insufficient suitability for VR simulation.CONCLUSION:Automated processing of CBCT imaging has potential for preoperative VR simulation but requires further refinement.

PDF file, 46K, Quantification of color coded Ktrans and ve parametric images following DCE-MRI.

Objective Patient‐specific virtual reality (VR) simulation of cochlear implant (CI) surgery potentially enables preoperative rehearsal and planning. We aim to gather supporting validity evidence for patient‐specific simulation through the analysis of virtual performance and comparison with postoperative imaging. Methods Prospective, multi‐institutional study. Pre‐ and postoperative cone‐beam CT scans of CI surgical patients were obtained and processed for patient‐specific VR simulation. The virtual performances of five trainees and four attendings were recorded and (1) compared with volumes removed during actual surgery as determined in postoperative imaging, and (2) assessed using the Copenhagen Cochlear Implant Surgery Assessment Tool (CISAT) by two blinded raters. The volumes compared were cortical mastoidectomy, facial recess, and round window (RW) cochleostomy as well as violation of the facial nerve and chorda. Results Trainees drilled more volume in the cortical mastoidectomy and facial recess, whereas attendings drilled more volume for the RW cochleostomy and made more violations. Except for the cochleostomy, attendings removed volumes closer to that determined in postoperative imaging. Trainees achieved a higher CISAT performance score compared with attendings (22.0 vs. 18.4 points) most likely due to lack of certain visual cues. Conclusion We found that there were differences in performance of trainees and attendings in patient‐specific VR simulation of CI surgery as assessed by raters and in comparison with actual drilled volumes. The presented approach of volume comparison is novel and might be used for further validation of patient‐specific VR simulation before clinical implementation for preoperative rehearsal in temporal bone surgery. Level of Evidence n/a Laryngoscope , 134:1403–1409, 2024

Background Inherited retinal degeneration is a leading cause of incurable vision loss in the developed world. While autologous iPSC mediated photoreceptor cell replacement is theoretically possible, the lack of commercially available technologies designed to enable high throughput parallel production of patient specific therapeutics has hindered clinical translation. Methods In this study, we describe the use of the Cell X precision robotic cell culture platform to enable parallel production of clinical grade patient specific iPSCs. The Cell X is housed within an ISO Class 5 cGMP compliant closed aseptic isolator (Biospherix XVivo X2), where all procedures from fibroblast culture to iPSC generation, clonal expansion and retinal differentiation were performed. Results Patient iPSCs generated using the Cell X platform were determined to be pluripotent via score card analysis and genetically stable via karyotyping. As determined via immunostaining and confocal microscopy, iPSCs generated using the Cell X platform gave rise to retinal organoids that were indistinguishable from organoids derived from manually generated iPSCs. In addition, at 120 days post-differentiation, single-cell RNA sequencing analysis revealed that cells generated using the Cell X platform were comparable to those generated under manual conditions in a separate laboratory. Conclusion We have successfully developed a robotic iPSC generation platform and standard operating procedures for production of high-quality photoreceptor precursor cells that are compatible with current good manufacturing practices. This system will enable clinical grade production of iPSCs for autologous retinal cell replacement.

PDF file, 96K, HSV-1 immuno stained sections of subcutaneous and intracranial tumors treated with PBS or ATN-224 (0.7mg) by daily gavage.

Description of western blot methodology for supplemental Figure and sources of gene expression data.

PDF file, 304K, Effect of copper on virus therapy for glioma cells.

Supplemental Figure 1: The ability of 34.5ENVE to infect and replicate in DB-7 and Met-1 BC cells

Abstract Purpose: Copper in serum supports angiogenesis and inhibits replication of wild-type HSV-1. Copper chelation is currently being investigated as an antiangiogenic and antineoplastic agent in patients diagnosed with cancer. Herpes simplex virus–derived oncolytic viruses (oHSV) are being evaluated for safety and efficacy in patients, but several host barriers limit their efficacy. Here, we tested whether copper inhibits oHSV infection and replication and whether copper chelation would augment therapeutic efficacy of oHSV. Experimental Design: Subcutaneous and intracranial tumor-bearing mice were treated with oHSV ± ATN-224 to evaluate tumor burden and survival. Virus replication and cell killing was measured in the presence or absence of the copper chelating agent ATN-224 and in the presence or absence of copper in vitro. Microvessel density and changes in perfusion were evaluated by immunohistochemistry and dynamic contrast enhanced MRI (DCE-MRI). Serum stability of oHSV was measured in mice fed with ATN-224. Tumor-bearing mice were injected intravenously with oHSV; tumor burden and amount of virus in tumor tissue were evaluated. Results: Combination of systemic ATN-224 and oHSV significantly reduced tumor growth and prolonged animal survival. Immunohistochemistry and DCE-MRI imaging confirmed that ATN-224 reduced oHSV-induced blood vessel density and vascular leakage. Copper at physiologically relevant concentrations inhibited oHSV replication and glioma cell killing, and this effect was rescued by ATN-224. ATN-224 increased serum stability of oHSV and enhanced the efficacy of systemic delivery. Conclusion: This study shows that combining ATN-224 with oHSV significantly increased serum stability of oHSV and greatly enhanced its replication and antitumor efficacy. Clin Cancer Res; 18(18); 4931–41. ©2012 AACR.

PDF file, 157K, Ex vivo serum rescue assay.

PDF file, 65K, ATN-224 by itself does not affect glioma cell viability or oHSV efficacy in the absence of copper.

Human induced pluripotent stem cells (hiPSCs) have demonstrated great promise for a variety of applications that include cell therapy and regenerative medicine. Production of clinical grade hiPSCs requires reproducible manufacturing methods with stringent quality-controls such as those provided by image-controlled robotic processing systems. In this paper we present an automated image analysis method for identifying and picking hiPSC colonies for clonal expansion using the CellXTM robotic cell processing system. This method couples a light weight deep learning segmentation approach based on the U-Net architecture to automatically segment the hiPSC colonies in full field of view (FOV) high resolution phase contrast images with a standardized approach for suggesting pick locations. The utility of this method is demonstrated using images and data obtained from the CellXTM system where clinical grade hiPSCs were reprogrammed, clonally expanded, and differentiated into retinal organoids for use in treatment of patients with inherited retinal degenerative blindness.

Hypothesis: Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts. Background: Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation. Methods: Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications. Results: Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties. Conclusion: Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.

White Matter Hyperintensities (WMH) are the most common manifestation of cerebral small vessel disease (cSVD) on the brain MRI. Accurate WMH segmentation algorithms are important to determine cSVD burden and its clinical con-sequences. Most of existing WMH segmentation algorithms require both fluid attenuated inversion recovery (FLAIR) images and T1-weighted images as inputs. However, T1-weighted images are typically not part of standard clinical scans which are acquired for patients with acute stroke. In this paper, we propose a novel brain atlas guided attention U-Net (BAGAU-Net) that leverages only FLAIR images with a spatially-registered white matter (WM) brain atlas to yield competitive WMH segmentation performance. Specifically, we designed a dual-path segmentation model with two novel connecting mechanisms, namely multi-input attention module (MAM) and attention fusion module (AFM) to fuse the information from two paths for accurate results. Experiments on two publicly available datasets show the effectiveness of the proposed BAGAU-Net. With only FLAIR images and WM brain atlas, BAGAU-Net outperforms the state-of-the-art method with T1-weighted images, paving the way for effective development of WMH segmentation. Availability: https://github.com/Ericzhang1/BAGAU-Net.