Noctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery.

PURPOSE: A patient registration and real-time surgical navigation system and a novel device and method (Noctopus) is presented. With any tracking system technology and a patient/target-specific registration marker configuration, submillimetric target registration error (TRE), high-precise application accuracy for single or multiple anatomical targets in image-guided neurosurgery or ENT surgery is realized. METHODS: The system utilizes the advantages of marker-based registration technique and allows to perform automatized patient registration using on the device attached and with patient scanned four fiducial markers. The best possible sensor/marker positions around the patient's head are determined for single or multiple region(s) of interest (target/s) in the anatomy. Once brought at the predetermined positions the device can be operated with any tracking system for registration purposes. RESULTS: Targeting accuracy was evaluated quantitatively at various target positions on a phantom skull. The target registration error (TRE) was measured on individual targets using an electromagnetic tracking system. The overall averaged TRE was 0.22 ± 0.08 mm for intraoperative measurements. CONCLUSION: An automatized patient registration system using optimized patient-/target-specific marker configurations is proposed. High-precision and user-error-free intraoperative surgical navigation with minimum number of registration markers and sensors is realized. The targeting accuracy is significantly improved in minimally invasive neurosurgical and ENT interventions.

Radiomic Assessment of Radiation-Induced Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma within the Currently Clinically Defined Optimal Time Window for Salvage Surgery-A Pilot Study.

Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity modulation, the desired radiation-induced effects observed in HNSCC may also be observed as side effects in healthy tissue, e.g., the sternocleidomastoid muscle (SCM). These side effects (e.g., tissue fibrosis) depend on the interval between the completion of RCT and restaging CT. For salvage surgery, the optimal time window for surgery is currently clinically postulated at between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on clinical studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC patients are sparse. The present study quantified tissue alterations in the SCM and paravertebral musculature (PVM) after RCT, applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters, (1) volume, (2) mean positivity of pixels (MPP), and (3) uniformity, were extracted with mint LesionTM in the staging CTs and restaging CTs of 98 HNSCC patients. Of these, 25 were female, the mean age was 62 (±9.6) years, and 80.9% were UICC Stage IV. The mean restaging interval was 55 (±28; range 29-229) days. Only the mean volume significantly decreased after RCT, from 9.0 to 8.4 and 96.5 to 91.9 mL for the SCM and PVM, respectively (both p = 0.007, both Cohen's d = 0.28). In addition, the mean body mass index (BMI) decreased from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p < 0.001; Cohen's d = 0.9). The mean BMI decreased significantly and was correlated with the volume decrease for the SCM (r = 0.27; p = 0.007) and PVM (r = 0.41; p < 0.001). If t-test p-values were adjusted for the BMI decrease, no significant change in volumes for the SCM and PVM was observed (both p > 0.05). The present data support the clinically postulated optimal interval for salvage surgery of 6 to 12 weeks.

Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space.

To accurately explore the anatomical organization of neural circuits in the brain, it is crucial to map the experimental brain data onto a standardized system of coordinates. Studying 2D histological mouse brain slices remains the standard procedure in many laboratories. Mapping these 2D brain slices is challenging; due to deformations, artifacts, and tilted angles introduced during the standard preparation and slicing process. In addition, analysis of experimental mouse brain slices can be highly dependent on the level of expertise of the human operator. Here we propose a computational tool for Accurate Mouse Brain Image Analysis (AMBIA), to map 2D mouse brain slices on the 3D brain model with minimal human intervention. AMBIA has a modular design that comprises a localization module and a registration module. The localization module is a deep learning-based pipeline that localizes a single 2D slice in the 3D Allen Brain Atlas and generates a corresponding atlas plane. The registration module is built upon the Ardent python package that performs deformable 2D registration between the brain slice to its corresponding atlas. By comparing AMBIA's performance in localization and registration to human ratings, we demonstrate that it performs at a human expert level. AMBIA provides an intuitive and highly efficient way for accurate registration of experimental 2D mouse brain images to 3D digital mouse brain atlas. Our tool provides a graphical user interface and it is designed to be used by researchers with minimal programming knowledge.

Current Applications of Artificial Intelligence to Classify Cervical Lymph Nodes in Patients with Head and Neck Squamous Cell Carcinoma-A Systematic Review.

Locally-advanced head and neck squamous cell carcinoma (HNSCC) is mainly defined by the presence of pathologic cervical lymph nodes (LNs) with or without extracapsular spread (ECS). Current radiologic criteria to classify LNs as non-pathologic, pathologic, or pathologic with ECS are primarily shape-based. However, significantly more quantitative information is contained within imaging modalities. This quantitative information could be exploited for classification of LNs in patients with locally-advanced HNSCC by means of artificial intelligence (AI). Currently, various reviews exploring the role of AI in HNSCC are available. However, reviews specifically addressing the current role of AI to classify LN in HNSCC-patients are sparse. The present work systematically reviews original articles that specifically explore the role of AI to classify LNs in locally-advanced HNSCC applying Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and the Study Quality Assessment Tool of National Institute of Health (NIH). Between 2001 and 2022, out of 69 studies a total of 13 retrospective, mainly monocentric, studies were identified. The majority of the studies included patients with oropharyngeal and oral cavity (9 and 7 of 13 studies, respectively) HNSCC. Histopathologic findings were defined as reference in 9 of 13 studies. Machine learning was applied in 13 studies, 9 of them applying deep learning. The mean number of included patients was 75 (SD ± 72; range 10-258) and of LNs was 340 (SD ± 268; range 21-791). The mean diagnostic accuracy for the training sets was 86% (SD ± 14%; range: 43-99%) and for testing sets 86% (SD ± 5%; range 76-92%). Consequently, all of the identified studies concluded AI to be a potentially promising diagnostic support tool for LN-classification in HNSCC. However, adequately powered, prospective, and randomized control trials are urgently required to further assess AI's role in LN-classification in locally-advanced HNSCC.

Benchmarking Eliminative Radiomic Feature Selection for Head and Neck Lymph Node Classification.

In head and neck squamous cell carcinoma (HNSCC) pathologic cervical lymph nodes (LN) remain important negative predictors. Current criteria for LN-classification in contrast-enhanced computed-tomography scans (contrast-CT) are shape-based; contrast-CT imagery allows extraction of additional quantitative data ("features"). The data-driven technique to extract, process, and analyze features from contrast-CTs is termed "radiomics". Extracted features from contrast-CTs at various levels are typically redundant and correlated. Current sets of features for LN-classification are too complex for clinical application. Effective eliminative feature selection (EFS) is a crucial preprocessing step to reduce the complexity of sets identified. We aimed at exploring EFS-algorithms for their potential to identify sets of features, which were as small as feasible and yet retained as much accuracy as possible for LN-classification. In this retrospective cohort-study, which adhered to the STROBE guidelines, in total 252 LNs were classified as "non-pathologic" (n = 70), "pathologic" (n = 182) or "pathologic with extracapsular spread" (n = 52) by two experienced head-and-neck radiologists based on established criteria which served as a reference. The combination of sparse discriminant analysis and genetic optimization retained up to 90% of the classification accuracy with only 10% of the original numbers of features. From a clinical perspective, the selected features appeared plausible and potentially capable of correctly classifying LNs. Both the identified EFS-algorithm and the identified features need further exploration to assess their potential to prospectively classify LNs in HNSCC.

Novel microscope-based visual display and nasopharyngeal registration for auditory brainstem implantation: a feasibility study in an ex vivo model.

PURPOSE: An auditory brainstem implant (ABI) represents an alternative for patients with profound hearing loss who are constrained from receiving a cochlear implant. The positioning of the ABI electrode influences the patient's auditory capacity and, therefore, quality of life and is challenging even with available intraoperative electrophysiological monitoring. This work aims to provide and assess the feasibility of visual-spatial assistance for ABI positioning. METHODS: The pose of the forceps instrument that grasps the electrode was electromagnetically navigated and interactively projected in the eyepieces of a surgical microscope with respect to a target point. Intraoperative navigation was established with an experimental technique for automated nasopharyngeal patient registration. Two ABI procedures were completed in a human specimen head. RESULTS: An intraoperative usability study demonstrated lower localization error when using the proposed visual display versus standard cross-sectional views. The postoperative evaluations of the preclinical study showed that the center of the electrode was misplaced to the planned position by 1.58 mm and 3.16 mm for the left and the right ear procedure, respectively. CONCLUSION: The results indicate the potential to enhance intraoperative feedback during ABI positioning with the presented system. Further improvements consider estimating the pose of the electrode itself to allow for better orientation during placement.

Automated fiducial marker detection and localization in volumetric computed tomography images: a three-step hybrid approach with deep learning.

Purpose: Automating fiducial detection and localization in the patient's pre-operative images can lead to better registration accuracy, reduced human errors, and shorter intervention time. Most current approaches are optimized for a single marker type, mainly spherical adhesive markers. A fully automated algorithm is proposed and evaluated for screw and spherical titanium fiducials, typically used in high-accurate frameless surgical navigation. Approach: The algorithm builds on previous approaches with morphological functions and pose estimation algorithms. A 3D convolutional neural network (CNN) is proposed for the fiducial classification task and evaluated for both traditional closed-set and emerging open-set classifiers. A proposed digital ground-truth experiment, with cone-beam computed tomography (CBCT) imaging software, is performed to determine the localization accuracy of the algorithm. The localized fiducial positions in the CBCT images by the presented algorithm were compared to the actual known positions in the virtual phantom models. The difference represents the fiducial localization error (FLE). Results: A total of 241 screws, 151 spherical fiducials, and 1550 other structures are identified with the best true positive rate 95.9% for screw and 99.3% for spherical fiducials at 8.7% and 3.4% false positive rate, respectively. The best achieved FLE mean and its standard deviation for a screw and spherical marker are 58 (14) and 14 ( 6 ) µ m , respectively. Conclusions: Accurate marker detection and localization were achieved, with spherical fiducials being superior to screws. Large marker volume and smaller voxel size yield significantly smaller FLEs. Attenuating noise by mesh smoothing has a minor effect on FLE. Future work will focus on expanding the CNN for image segmentation.

Visual display for surgical targeting: concepts and usability study.

PURPOSE: Interactive image-guided surgery technologies enable accurate target localization while preserving critical nearby structures in many surgical interventions. Current state-of-the-art interfaces largely employ traditional anatomical cross-sectional views or augmented reality environments to present the actual spatial location of the surgical instrument in preoperatively acquired images. This work proposes an alternative, simple, minimalistic visual interface intended to assist during real-time surgical target localization. METHODS: The estimated 3D pose of the interventional instruments and their positional uncertainty are intuitively presented in a visual interface with respect to the target point. A usability study with multidisciplinary participants evaluates the proposed interface projected in surgical microscope oculars against cross-sectional views. The latter was presented on a screen both stand-alone and combined with the proposed interface. The instruments were electromagnetically navigated in phantoms. RESULTS: The usability study demonstrated that the participants were able to detect invisible targets marked in phantom imagery with significant enhancements for localization accuracy and duration time. Clinically experienced users reached the targets with shorter trajectories. The stand-alone and multi-modal versions of the proposed interface outperformed cross-sectional views-only navigation in both quantitative and qualitative evaluations. CONCLUSION: The results and participants' feedback indicate potential to accurately navigate users toward the target with less distraction and workload. An ongoing study evaluates the proposed system in a preclinical setting for auditory brainstem implantation.

Agreement between rhinomanometry and computed tomography-based computational fluid dynamics.

PURPOSE: Active anterior rhinomanometry (AAR) and computed tomography (CT) are standardized methods for the evaluation of nasal obstruction. Recent attempts to correlate AAR with CT-based computational fluid dynamics (CFD) have been controversial. We aimed to investigate this correlation and agreement based on an in-house developed procedure. METHODS: In a pilot study, we retrospectively examined five subjects scheduled for septoplasty, along with preoperative digital volume tomography and AAR. The simulation was performed with Sailfish CFD, a lattice Boltzmann code. We examined the correlation and agreement of pressure derived from AAR (RhinoPress) and simulation (SimPress) and these of resistance during inspiration by 150 Pa pressure drop derived from AAR (RhinoRes150) and simulation (SimRes150). For investigation of correlation between pressures and between resistances, a univariate analysis of variance and a Pearson's correlation were performed, respectively. For investigation of agreement, the Bland-Altman method was used. RESULTS: The correlation coefficient between RhinoPress and SimPress was r = 0.93 (p < 0.001). RhinoPress was similar to SimPress in the less obstructed nasal side and two times greater than SimPress in the more obstructed nasal side. A moderate correlation was found between RhinoRes150 and SimRes150 (r = 0.65; p = 0.041). CONCLUSION: The simulation of rhinomanometry pressure by CT-based CFD seems more feasible with the lattice Boltzmann code in the less obstructed nasal side. In the more obstructed nasal side, error rates of up to 100% were encountered. Our results imply that the pressure and resistance derived from CT-based CFD and AAR were similar, yet not same.

respiTrack: Patient-specific real-time respiratory tumor motion prediction using magnetic tracking.

PURPOSE: An intraoperative real-time respiratory tumor motion prediction system with magnetic tracking technology is presented. Based on respiratory movements in different body regions, it provides patient and single/multiple tumor-specific prediction that facilitates the guiding of treatments. METHODS: A custom-built phantom patient model replicates the respiratory cycles similar to a human body, while the custom-built sensor holder concept is applied on the patient's surface to find optimum sensor number and their best possible placement locations to use in real-time surgical navigation and motion prediction of internal tumors. Automatic marker localization applied to patient's 4D-CT data, feature selection and Gaussian process regression algorithms enable off-line prediction in the preoperative phase to increase the accuracy of real-time prediction. RESULTS: Two evaluation methods with three different registration patterns (at fully/half inhaled and fully exhaled positions) were used quantitatively at all internal target positions in phantom: The statical method evaluates the accuracy by stopping simulated breathing and dynamic with continued breathing patterns. The overall root mean square error (RMS) for both methods was between [Formula: see text] and [Formula: see text]. The overall registration RMS error was [Formula: see text]. The best prediction errors were observed by registrations at half inhaled positions with minimum [Formula: see text], maximum [Formula: see text]. The resulting accuracy satisfies most radiotherapy treatments or surgeries, e.g., for lung, liver, prostate and spine. CONCLUSION: The built system is proposed to predict respiratory motions of internal structures in the body while the patient is breathing freely during treatment. The custom-built sensor holders are compatible with magnetic tracking. Our presented approach reduces known technological and human limitations of commonly used methods for physicians and patients.

CIGuide: in situ augmented reality laser guidance.

PURPOSE : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools. METHODS : Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery. RESULTS : System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon. CONCLUSION : A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions.

Missed paranasal sinus compartments in sinus surgery with and without image-guidance systems: a pilot feasibility study.

PURPOSE: Image-guidance systems (IGS) have gained widespread use in endoscopic sinus surgery (ESS) and have been thoroughly analysed. In this study, we looked for a new parameter to determine if patients could directly benefit from the use of IGS during primary ESS. We questioned if IGS could improve the quality of ESS in chronic rhinosinusitis (CRS) patients via allowing a more comprehensive treatment of all involved sinus compartments. METHODS: In a pilot feasibility study, we evaluated uncomplicated CRS patients following primary ESS with and without IGS between January 2011 and June 2012 using preoperative and postoperative CT scans. The preoperative CT scans identified the sinus compartments requiring surgery. The postoperative CT scans were used to evaluate the treatment effect in these compartments. From these data, we calculated a missing ratio (missed compartments/compartments requiring surgery) for each patient. RESULTS: Of the 169 ESS patients who were treated, ten patients were retrospectively identified as complying with the inclusion and exclusion criteria following ESS with IGS. Ten patients treated without IGS were then randomly chosen. The median missing ratio for non-IGS patients was 36%, and for IGS patients, the median missing ratio was 0% (p = 0.046). However, the missing ratio was depended on the number of compartments requiring surgery. Stratification of the number of compartments requiring surgery resulted in an exact p value of 0.13. CONCLUSIONS: IGS could help the surgeon to more completely address diseased sinus compartments. For better scientific merit, a comparative study of ESS with and without IGS seems feasible, using the proposed failing score missed compartments/compartments requiring surgery as the primary outcome parameter.

Vector field analysis for surface registration in computer-assisted ENT surgery.

BACKGROUND: Manual paired-point registration for navigated ENT-surgery is prone to human errors; automatic surface registration is often caught in local minima. METHODS: Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is defined between the patient and operating room datasets; registration is facilitated through gradient-based vector field analysis optimization of an energy function. The method is validated exemplarily on patient surface data provided by a mechanically positioned A-mode ultrasound sensor. RESULTS: Successful registrations were achieved within the entire parameter space, as well as from positions of local minima that were found by the Gaussian fields algorithm for surface registration. Sub-millimetric registration error was measured in clinically relevant anatomical areas on the anterior skull and within the generally accepted margin of 1.5 mm for the entire head. CONCLUSION: The satisfactory behavior of this approach potentially suggests a wider clinical integration.

Successful Cochlear Implantation of a Split Electrode Array in a Patient With Far-advanced Otosclerosis Assisted by Electromagnetic Navigation: A Case Report.

BACKGROUND: Incomplete electrode insertion is frequent when implanting ossified cochleae with conventional linear electrodes. If split electrode arrays (SEA) are used, this complication occurs less frequently resulting in improved audiological performance (AP). Additional implementation of electromagnetic navigation systems (EMNS) may add additional safety to this procedure and may further improve AP. However, previously performed SEA cochlea implantations rarely implemented EMNS. The few cases reported a laborious approach with customized, three-dimensional-printed microstereotactic headframes, which limited clinical feasibility. Moreover, no postoperative AP was reported. In this case report a more feasible approach, using a commercially available EMNS, is described and postoperative AP is reported. PATIENT: A 70-year-old man with far-advanced otosclerosis was referred because of unsatisfactory speech intelligibility (monosyllabic word score of 0% at 75 dB sound pressure level) after cochlear implantation of a conventional linear electrode. Preoperative computed tomography revealed subtotal cochlear ossification and incomplete electrode insertion. INTERVENTION: Four titanium screws were inserted into the petrous bone for computed tomography-based registration using an EMNS. The previous mastoidectomy was expanded, the misplaced conventional linear electrode extracted and a manual, free-handed superior cochleostomy at the level of the tendon of the tensor tympani muscle was performed. The location and course of the drill-out procedure for the SEA was planned and verified with EMNS. RESULTS: Full electrode insertion for both electrode arrays of the SEA was achieved without any nerve dysfunction. Monosyllabic word score, determined 207 days after surgery, improved to 50 and 60% at 65 and 75 dB sound pressure level respectively. CONCLUSION: The implementation of EMNS in SEA cochlear implantation added additional safety to the procedure, which resulted in full electrode insertion and superior AP. Yet, outcome in cochlear implantation may vary. Larger case series to confirm this observation are required. The approach proposed for EMNS-guided SEA in this case report, using commercially available EMNS, may lead to a more frequent implementation in clinical routine due to its good clinical feasibility. Thus, larger case series may be generated.

Probe versus microscope: a comparison of different methods for image-to-patient registration.

PURPOSE: Computer-aided navigation is widely used in ENT surgery. The position of a surgical instrument is shown in the CT/MR images of the patient and can thus be a good support for the surgeon. The accuracy is highly dependent on the registration done prior to surgery. A microscope and a probe can both be used for registration and navigation, depending on the surgical intervention. A navigation system typically only reports the fiducial registration error after paired-point registration. However, the target registration error (TRE)-a measurement for the accuracy in the surgical area-is much more relevant. The aim of this work was to compare the performance of a microscope relative to a conventional probe-based approach with different registration methods. METHODS: In this study, optical tracking was used to register a plastic skull to its preoperative CT images with paired-point registration. Anatomical landmarks and skin-affixed markers were used as fiducials and targets. With both microscope and probe, four different registration methods were evaluated based on their TREs at 10 targets. For half of the experiments, a surface registration and/or external fiducials were used additionally to paired-point registration to study their influence to accuracy. RESULTS: Overall, probe registration leads to a smaller TRE ([Formula: see text]) than registration with a microscope ([Formula: see text]). Additional surface registration does not result in better accuracy of navigation for microscope and probe. The lowest mean TRE for both pointers can be achieved with paired-point registration only and radiolucent markers. CONCLUSION: Our experiments showed that a probe used for registration and navigation achieves lower TREs compared using a microscope. Neither additional surface registration nor additional fiducials on an external reference element are necessary for improved accuracy of navigated ENT surgery on a plastic skull.

Experimental validation of predicted application accuracies for computer-assisted (CAS) intraoperative navigation with paired-point registration.

PURPOSE: The target registration error (TRE) is a crucial parameter to estimate the potential usefulness of computer-assisted navigation intraoperatively. Both image-to-patient registration on base of rigid-body registration and TRE prediction methods are available for spatially isotropic and anisotropic data. This study presents a thorough validation of data obtained in an experimental operating room setting with CT images. METHODS: Optical tracking was used to register a plastic skull, an anatomic specimen, and a volunteer to their respective CT images. Plastic skull and anatomic specimen had implanted bone fiducials for registration; the volunteer was registered with anatomic landmarks. Fiducial localization error, fiducial registration error, and total target error (TTE) were measured; the TTE was compared to isotropic and anisotropic error prediction models. Numerical simulations of the experiment were done additionally. RESULTS: The user localization error and the TTE were measured and calculated using predictions, both leading to results as expected for anatomic landmarks and screws used as fiducials. TRE/TTE is submillimetric for the plastic skull and the anatomic specimen. In the experimental data a medium correlation was found between TRE and target localization error (TLE). Most of the predictions of the application accuracy (TRE) fall in the 68% confidence interval of the measured TTE. For the numerically simulated data, a prediction of TTE was not possible; TRE and TTE show a negligible correlation. CONCLUSION: Experimental application accuracy of computer-assisted navigation could be predicted satisfactorily with adequate models in an experimental setup with paired-point registration of CT images to a patient. The experimental findings suggest that it is possible to run navigation and prediction of navigation application accuracy basically defined by the spatial resolution/precision of the 3D tracker used.

Irradiation as a hazard for mucociliary clearance.

OBJECTIVES: In this paper we study effects of irradiation to pulmonary tissue on a micro and ultrastructural level to get insights into the dynamics of morphological changes and associated post-radiative physiological conditions. METHODS: Animal and human pulmonary tissue with and without radiation damage was subject to light, transmission, scanning and polarization microscopy and morphometric evaluation. RESULTS: The present investigations on the influence of irradiation on experimental and human lung tissue demonstrate that complex changes are induced in the cells which are essential for mucociliary clearance. These changes are a shortage of alveolar macrophages, cell apoptosis, proliferation of collagen ligament in the barrier of gaseous exchange, retraction of endothelial lining of capillaries and significant broadening of the gaseous exchange barrier, resulting in serious damage for the O2 and CO2 exchange. CONCLUSIONS: These changes at microscopic, cellular, and ciliary level trigger conditions for various diseases of the respiratory system, which is further assessed by a simultaneous computer aided estimation of ciliary function. With the concurrent world-wide increase of respiratory diseases, these findings are important knowledge for the clinical practice.

Estimating FLEimage distributions of manual fiducial localization in CT images.

PURPOSE: The fiducial localization error distribution (FLE) and fiducial configuration govern the application accuracy of point-based registration and drive target registration error (TRE) prediction models. The error of physically localizing patient fiducials ([Formula: see text]) is negligible when a registration probe matches the implanted screws with mechanical precision. Reliable trackers provide an unbiased estimate of the positional error ([Formula: see text]) with cheap repetitions. FLE further contains the localization error in the imaging data ([Formula: see text]), sampling of which in general is expensive and possibly biased. Finding the best techniques for estimating [Formula: see text] is crucial for the applicability of the TRE prediction methods. METHODS: We built a ground-truth (gt)-based unbiased estimator ([Formula: see text]) of [Formula: see text] from the samples collected in a virtual CT dataset in which the true locations of image fiducials are known by definition. Replacing true locations in [Formula: see text] by the sample mean creates a practical difference-to-mean (dtm)-based estimator ([Formula: see text]) that is applicable on any dataset. To check the practical validity of the dtm estimator, ten persons manually localized nine fiducials ten times in the virtual CT and the resulting [Formula: see text] and [Formula: see text] distributions were tested for statistical equality with a kernel-based two-sample test using the maximum mean discrepancy (MMD) (Gretton in J Mach Learn Res 13:723-773, 2012) statistics at [Formula: see text]. RESULTS: [Formula: see text] and [Formula: see text] were found (for most of the cases) not to be statistically significantly different; conditioning them on persons and/or screws however yielded statistically significant differences much more often. CONCLUSIONS: We conclude that [Formula: see text] is the best candidate (within our model) for estimating [Formula: see text] in homogeneous TRE prediction models. The presented approach also allows ground-truth-based numerical validation of [Formula: see text] estimators and (manual/automatic) image fiducial localization methods in phantoms with parameters similar to clinical datasets.

A new nasopharyngeal dynamic reference frame improves accuracy in navigated skull base targets.

OBJECTIVE: We questioned whether the position of the dynamic reference frame (DRF) influences the application accuracy in electromagnetically navigated cranial procedures. A carrier for an electromagnetic DRF was developed, which could be fixed at the posterior edge of the vomer near the center of the head. This nasopharyngeal DRF was compared with a standard DRF fixed to the surface of the forehead. METHODS: Image coordinates and real-world coordinates were co-registered and the total target error (TTE) was measured in the frontal and the lateral skull base of formalin fixed human head. At each anatomical site, 10 targets served for TTE determinations and 5 different fiducial combinations were used for registration. RESULTS: With the nasopharyngeal DRF, lower TTE values (2.8 ± 1.4 mm; mean ± SD) were observed when compared with the forehead DRF (3.7 ± 2.8 mm; P = .004). TTEs of both anatomical sites investigated were significantly lower when using the nasopharyngeal DRF (frontal skull base 3.4 vs 2.1 mm, P = .005 and lateral skull base 3.9 vs 3.5 mm, P = .013) than with the standard forehead mounted one. CONCLUSION: Positioning the DRF in the center of the head significantly improved the application accuracy of targets in the skull base with electromagnetic navigation by 25%.

Proof-of-concept of a laser mounted endoscope for touch-less navigated procedures.

BACKGROUND AND OBJECTIVES: During navigated procedures a tracked pointing device is used to define target structures in the patient to visualize its position in a registered radiologic data set. When working with endoscopes in minimal invasive procedures, the target region is often difficult to reach and changing instruments is disturbing in a challenging, crucial moment of the procedure. We developed a device for touch less navigation during navigated endoscopic procedures. MATERIALS AND METHODS: A laser beam is delivered to the tip of a tracked endoscope angled to its axis. Thereby the position of the laser spot in the video-endoscopic images changes according to the distance between the tip of the endoscope and the target structure. A mathematical function is defined by a calibration process and is used to calculate the distance between the tip of the endoscope and the target. The tracked tip of the endoscope and the calculated distance is used to visualize the laser spot in the registered radiologic data set. RESULTS: In comparison to the tracked instrument, the touch less target definition with the laser spot yielded in an over and above error of 0.12 mm. The overall application error in this experimental setup with a plastic head was 0.61 ± 0.97 mm (95% CI -1.3 to +2.5 mm). CONCLUSION: Integrating a laser in an endoscope and then calculating the distance to a target structure by image processing of the video endoscopic images is accurate. This technology eliminates the need for tracked probes intraoperatively and therefore allows navigation to be integrated seamlessly in clinical routine. However, it is an additional chain link in the sequence of computer-assisted surgery thus influencing the application error.