Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative data. METHODS: We retrospectively analyzed data including 21 predictors from patients undergoing colorectal surgery with bowel anastomosis at four Swiss hospitals. Several ML algorithms were applied for binary classification into AL or non-AL groups, utilizing a five-fold cross-validation strategy with a 90% training and 10% validation split. Additionally, a holdout test set from an external hospital was employed to assess the models' robustness in external validation. RESULTS: Among 1244 patients, 112 (9.0%) suffered from AL. The Random Forest model showed an AUC-ROC of 0.78 (SD: ± 0.01) on the internal test set, which significantly decreased to 0.60 (SD: ± 0.05) on the external holdout test set comprising 198 patients, including 7 (3.5%) with AL. Conversely, the Logistic Regression model demonstrated more consistent AUC-ROC values of 0.69 (SD: ± 0.01) on the internal set and 0.61 (SD: ± 0.05) on the external set. Accuracy measures for Random Forest were 0.82 (SD: ± 0.04) internally and 0.87 (SD: ± 0.08) externally, while Logistic Regression achieved accuracies of 0.81 (SD: ± 0.10) and 0.88 (SD: ± 0.15). F1 Scores for Random Forest moved from 0.58 (SD: ± 0.03) internally to 0.51 (SD: ± 0.03) externally, with Logistic Regression maintaining more stable scores of 0.53 (SD: ± 0.04) and 0.51 (SD: ± 0.02). CONCLUSION: In this pilot study, we evaluated ML-based prediction models for AL post-colorectal surgery and identified ten patient-related risk factors associated with AL. Highlighting the need for multicenter data, external validation, and larger sample sizes, our findings emphasize the potential of ML in enhancing surgical outcomes and inform future development of a web-based application for broader clinical use.

Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis.

BACKGROUND: Spinal cord (SC) gray and white matter pathology plays a central role in multiple sclerosis (MS). OBJECTIVE: We aimed to investigate the extent, pattern, and clinical relevance of SC gray and white matter atrophy in vivo. METHODS: 39 relapsing-remitting patients (RRMS), 40 progressive MS patients (PMS), and 24 healthy controls (HC) were imaged at 3T using the averaged magnetization inversion recovery acquisitions sequence. Total and lesional cervical gray and white matter, and posterior (SCPH) and anterior horn (SCAH) areas were automatically quantified. Clinical assessment included the expanded disability status scale, timed 25-foot walk test, nine-hole peg test, and the 12-item MS walking scale. RESULTS: PMS patients had significantly reduced cervical SCAH - but not SCPH - areas compared with HC and RRMS (both p < 0.001). In RRMS and PMS, the cervical SCAH areas increased significantly less in the region of cervical SC enlargement compared with HC (all p < 0.001). This reduction was more pronounced in PMS compared with RRMS (both p < 0.001). In PMS, a lower cervical SCAH area was the most important magnetic resonance imaging (MRI)-variable for higher disability scores. CONCLUSION: MS patients show clinically relevant cervical SCAH atrophy, which is more pronounced in PMS and at the level of cervical SC enlargement.

Multimodal feedback systems for smart laser osteotomy: Depth control and tissue differentiation.

OBJECTIVES: The study aimed to improve the safety and accuracy of laser osteotomy (bone surgery) by integrating optical feedback systems with an Er:YAG laser. Optical feedback consists of a real-time visual feedback system that monitors and controls the depth of laser-induced cuts and a tissue sensor differentiating tissue types based on their chemical composition. The developed multimodal feedback systems demonstrated the potential to enhance the safety and accuracy of laser surgery. MATERIALS AND METHODS: The proposed method utilizes a laser-induced breakdown spectroscopy (LIBS) system and long-range Bessel-like beam optical coherence tomography (OCT) for tissue-specific laser surgery. The LIBS system detects tissue types by analyzing the plasma generated on the tissue by a nanosecond Nd:YAG laser, while OCT provides real-time monitoring and control of the laser-induced cut depth. The OCT system operates at a wavelength of 1288 ± 30 nm and has an A-scan rate of 104.17 kHz, enabling accurate depth control. Optical shutters are used to facilitate the integration of these multimodal feedback systems. RESULTS: The proposed system was tested on five specimens of pig femur bone to evaluate its functionality. Tissue differentiation and visual depth feedback were used to achieve high precision both on the surface and in-depth. The results showed successful real-time tissue differentiation and visualization without any visible thermal damage or carbonization. The accuracy of the tissue differentiation was evaluated, with a mean absolute error of 330.4 µm and a standard deviation of ±248.9 µm, indicating that bone ablation was typically stopped before reaching the bone marrow. The depth control of the laser cut had a mean accuracy of 65.9 µm with a standard deviation of ±45 µm, demonstrating the system's ability to achieve the pre-planned cutting depth. CONCLUSION: The integrated approach of combining an ablative laser, visual feedback (OCT), and tissue sensor (LIBS) has significant potential for enhancing minimally invasive surgery and warrants further investigation and development.

Towards phase-sensitive optical coherence tomography in smart laser osteotomy: temperature feedback.

Thermal effects during bone surgery pose a common challenge, whether using mechanical tools or lasers. An irrigation system is a standard solution to cool the tissue and reduce collateral thermal damage. In bone surgery using Er:YAG laser, insufficient irrigation raises the risk of thermal damage, while excessive water lowers ablation efficiency. This study investigated the potential of optical coherence tomography to provide feedback by relating the temperature rise with the photo-thermal expansion of the tissue. A phase-sensitive optical coherence tomography system (central wavelength of λ=1.288 µm, a bandwidth of 60.9 nm and a sweep rate of 104.17 kHz) was integrated with an Er:YAG laser using a custom-made dichromatic mirror. Phase calibration was performed by monitoring the temperature changes (thermal camera) and corresponding cumulative phase changes using the phase-sensitive optical coherence tomography system during laser ablation. In this experiment, we used an Er:YAG laser with 230 mJ per pulse at 10 Hz for ablation. Calibration coefficients were determined by fitting the temperature values to phase later and used to predict the temperature rise for subsequent laser ablations. Following the phase calibration step, we used the acquired values to predict the temperature rise of three different laser-induced cuts with the same parameters of the ablative laser. The average root-mean-square error for the three experiments was measured to be around 4 °C. In addition to single-point prediction, we evaluated this method's performance to predict the tissue's two-dimensional temperature rise during laser osteotomy. The findings suggest that the proposed principle could be used in the future to provide temperature feedback for minimally invasive laser osteotomy.

Spinal cord gray matter atrophy is associated with functional decline in post-polio syndrome.

OBJECTIVE: To determine if patients with post-polio syndrome (PPS) show spinal cord gray matter (SCGM) atrophy and to assess associations between SCGM atrophy, muscle strength and patient-reported functional decline. METHODS: Twenty patients diagnosed with PPS (March of Dimes criteria) and 20 age- and sex-matched healthy controls (HC) underwent 3T axial 2D-rAMIRA magnetic resonance imaging at the intervertebral disc levels C2/C3-C6/C7, T9/T10 and the lumbar enlargement level (Tmax ) (0.5 × 0.5 mm2 in-plane resolution). SCGM areas were segmented manually by two independent raters. Muscle strength, self-reported fatigue, depression and pain measures were assessed. RESULTS: Post-polio syndrome patients showed significantly and preferentially reduced SCGM areas at C2/C3 (p = 0.048), C3/C4 (p = 0.001), C4/C5 (p < 0.001), C5/C6 (p = 0.004) and Tmax (p = 0.041) compared to HC. SCGM areas were significantly associated with muscle strength in corresponding myotomes even after adjustment for fatigue, pain and depression. SCGM areaTmax together with age and sex explained 68% of ankle dorsiflexion strength variance. No associations were found with age at or time since infection. Patients reporting PPS-related decline in arm function showed significant cervical SCGM atrophy compared to stable patients adjusted for initial disease severity. CONCLUSIONS: Patients with PPS show significant SCGM atrophy that correlates with muscle strength and is associated with PPS-related functional decline. Our findings suggest a secondary neurodegenerative process underlying SCGM atrophy in PPS that is not explained by aging or residua of the initial infection alone. Confirmation by longitudinal studies is needed. The described imaging methodology is promising for developing novel imaging surrogates for SCGM diseases.

Toward optoacoustic sciatic nerve detection using an all-fiber interferometric-based sensor for endoscopic smart laser surgery.

OBJECTIVES: Laser surgery requires efficient tissue classification to reduce the probability of undesirable or unwanted tissue damage. This study aimed to investigate acoustic shock waves (ASWs) as a means of classifying sciatic nerve tissue. MATERIALS AND METHODS: In this study, we classified sciatic nerve tissue against other tissue types-hard bone, soft bone, fat, muscle, and skin extracted from two proximal and distal fresh porcine femurs-using the ASWs generated by a laser during ablation. A nanosecond frequency-doubled Nd:YAG laser at 532 nm was used to create 10 craters on each tissue type's surface. We used a fiber-coupled Fabry-Pérot sensor to measure the ASWs. The spectrum's amplitude from each ASW frequency band measured was used as input for principal component analysis (PCA). PCA was combined with an artificial neural network to classify the tissue types. A confusion matrix and receiver operating characteristic (ROC) analysis was used to calculate the accuracy of the testing-data-based scores from the sciatic nerve and the area under the ROC curve (AUC) with a 95% confidence-level interval. RESULTS: Based on the confusion matrix and ROC analysis of the model's tissue classification results (leave-one-out cross-validation), nerve tissue could be classified with an average accuracy rate and AUC result of 95.78  ± 1.3% and 99.58  ± 0.6%, respectively. CONCLUSION: This study demonstrates the potential of using ASWs for remote classification of nerve and other tissue types. The technique can serve as the basis of a feedback control system to detect and preserve sciatic nerves in endoscopic laser surgery.

The impact of segmentation on whole-lung functional MRI quantification: Repeatability and reproducibility from multiple human observers and an artificial neural network.

PURPOSE: To investigate the repeatability and reproducibility of lung segmentation and their impact on the quantitative outcomes from functional pulmonary MRI. Additionally, to validate an artificial neural network (ANN) to accelerate whole-lung quantification. METHOD: Ten healthy children and 25 children with cystic fibrosis underwent matrix pencil decomposition MRI (MP-MRI). Impaired relative fractional ventilation (RFV ) and relative perfusion (RQ ) from MP-MRI were compared using whole-lung segmentation performed by a physician at two time-points (At1 and At2 ), by an MRI technician (B), and by an ANN (C). Repeatability and reproducibility were assess with Dice similarity coefficient (DSC), paired t-test and Intraclass-correlation coefficient (ICC). RESULTS: The repeatability within an observer (At1 vs At2 ) resulted in a DSC of 0.94 ± 0.01 (mean ± SD) and an unsystematic difference of -0.01% for RFV (P = .92) and +0.1% for RQ (P = .21). The reproducibility between human observers (At1 vs B) resulted in a DSC of 0.88 ± 0.02, and a systematic absolute difference of -0.81% (P < .001) for RFV and -0.38% (P = .037) for RQ . The reproducibility between human and the ANN (At1 vs C) resulted in a DSC of 0.89 ± 0.03 and a systematic absolute difference of -0.36% for RFV (P = .017) and -0.35% for RQ (P = .002). The ICC was >0.98 for all variables and comparisons. CONCLUSIONS: Despite high overall agreement, there were systematic differences in lung segmentation between observers. This needs to be considered for longitudinal studies and could be overcome by using an ANN, which performs as good as human observers and fully automatizes MP-MRI post-processing.

Itch reduction using immersive virtual reality-An experimental pilot study.

In a previous proof-of-concept study we have demonstrated that visual exposure to specific colors results in pruritic or antipruritic effects. To determine the effect of "antipruritic" colors when using immersive virtual reality (VR) and to assess whether psychometric values correlate with the response to the color exposure. In this cross-sectional interventional single-center study, itch patients were exposed to their subjective "antipruritic color" (defined by the Manchester Color Wheel) in a virtual monochromatic room for 10 min using a head-mounted display. Itch intensity rating (0-10 numerical rating scale [NRS]) was repeated at 1-min intervals. Additionally, dermatology life quality index, itch-related quality of life and the Hospital Anxiety and Depression Scale questionnaires were completed. Twenty-two patients (mean age 51.9 ± 23 years, 13 females) participated in the study. Following color exposure for 10 min itch intensity was significantly reduced compared to baseline (exact Wilcoxon signed-rank test, mdn-NRS 4.5 vs 3.0; z = -3.025, p = 0.001), confirmed by the area under the curve (z = -3.118; p = 0.001). No significant correlation between itch reduction and questionnaire scores was found (Spearman's Rho for all questionnaires). Visual exposure to the "antipruritic color" using immersive VR resulted in a significant decrease in itch intensity. This aligns with previous findings on the influence of colors on itch perception. The response of the intervention appeared independent of psychometric values. Thus, color exposure using immersive VR is a promising, low-cost, rapidly-acting, easily-applicable, non-pharmacological experimental antipruritic method.

Comparing the Bone Healing After Cold Ablation Robot-Guided Er:YAG Laser Osteotomy and Piezoelectric Osteotomy-A Pilot Study in a Minipig Mandible.

BACKGROUND AND OBJECTIVE: To take major advantage of erbium-doped yttrium aluminium garnet (Er:YAG) lasers in osteotomy-like freedom of cutting geometries and high accuracy-the integration and miniaturization of the robot, laser, and navigation technology was tried and applied to minipigs. The investigators hypothesized laser osteotomy would render acceptable bone healing based on the intraoperative findings and postoperative cut surface analysis. STUDY DESIGN/MATERIALS AND METHODS: We designed and implemented a comparative bone-cutting surgery in the minipig mandible with a cold ablation robot-guided Er:YAG laser osteotome (CARLO) and a piezoelectric (PZE) osteotome. The sample was composed of different patterns of defects in the mandibles of six grown-up female Goettingen minipigs. The predictor variable was Er:YAG osteotomy and PZE osteotomy. The outcome variable was the cut surface characteristics and bone healing at 4 and 8 weeks postoperatively. Descriptive and qualitative comparison was executed. RESULTS: The sample was composed of four kinds of bone defects on both sides of the mandibles of six minipigs. We observed more bleeding during the operation, open-cut surfaces, and a faster healing pattern with the laser osteotomy. There was a possible association between the intraoperative findings, postoperative cut surface analysis, and the bone healing pattern. CONCLUSIONS: The results of this study suggest that characteristic open-cut surfaces could explain favorable bone healing after laser osteotomy. Future studies will focus on the quantification of the early healing characteristics after laser osteotomy, its diverse application, and the safety feature. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.

Machine Learning-Based Optoacoustic Tissue Classification Method for Laser Osteotomes Using an Air-Coupled Transducer.

BACKGROUND AND OBJECTIVES: Using lasers instead of mechanical tools for bone cutting holds many advantages, including functional cuts, contactless interaction, and faster wound healing. To fully exploit the benefits of lasers over conventional mechanical tools, a real-time feedback to classify tissue is proposed. STUDY DESIGN/MATERIALS AND METHODS: In this paper, we simultaneously classified five tissue types-hard and soft bone, muscle, fat, and skin from five proximal and distal fresh porcine femurs-based on the laser-induced acoustic shock waves (ASWs) generated. For laser ablation, a nanosecond frequency-doubled Nd:YAG laser source at 532 nm and a microsecond Er:YAG laser source at 2940 nm were used to create 10 craters on the surface of each proximal and distal femur. Depending on the application, the Nd:YAG or Er:YAG can be used for bone cutting. For ASW recording, an air-coupled transducer was placed 5 cm away from the ablated spot. For tissue classification, we analyzed the measured acoustics by looking at the amplitude-frequency band of 0.11-0.27 and 0.27-0.53 MHz, which provided the least average classification error for Er:YAG and Nd:YAG, respectively. For data reduction, we used the amplitude-frequency band as an input of the principal component analysis (PCA). On the basis of PCA scores, we compared the performance of the artificial neural network (ANN), the quadratic- and Gaussian-support vector machine (SVM) to classify tissue types. A set of 14,400 data points, measured from 10 craters in four proximal and distal femurs, was used as training data, while a set of 3,600 data points from 10 craters in the remaining proximal and distal femur was considered as testing data, for each laser. RESULTS: The ANN performed best for both lasers, with an average classification error for all tissues of 5.01 ± 5.06% and 9.12 ± 3.39%, using the Nd:YAG and Er:YAG lasers, respectively. Then, the Gaussian-SVM performed better than the quadratic SVM during the cutting with both lasers. The Gaussian-SVM yielded average classification errors of 15.17 ± 13.12% and 16.85 ± 7.59%, using the Nd:YAG and Er:YAG lasers, respectively. The worst performance was achieved with the quadratic-SVM with a classification error of 50.34 ± 35.04% and 69.96 ± 25.49%, using the Nd:YAG and Er:YAG lasers. CONCLUSION: We foresee using the ANN to differentiate tissues in real-time during laser osteotomy. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.

Randomized study comparing 3D virtual reality and conventional 2D on-screen teaching of cerebrovascular anatomy.

OBJECTIVE: Performing aneurysmal clipping requires years of training to successfully understand the 3D neurovascular anatomy. This training has traditionally been obtained by learning through observation. Currently, with fewer operative aneurysm clippings, stricter work-hour regulations, and increased patient safety concerns, novel teaching methods are required for young neurosurgeons. Virtual-reality (VR) models offer the opportunity to either train a specific surgical skill or prepare for an individual surgery. With this study, the authors aimed to compare the spatial orientation between traditional 2D images and 3D VR models in neurosurgical residents or medical students. METHODS: Residents and students were each randomly assigned to describe 4 aneurysm cases, which could be either 2D images or 3D VR models. The time to aneurysm detection as well as a spatial anatomical description was assessed via an online questionnaire and compared between the groups. The aneurysm cases were 10 selected patient cases treated at the authors' institution. RESULTS: Overall, the time to aneurysm detection was shorter in the 3D VR model compared to 2D images, with a trend toward statistical significance (25.77 ± 37.26 vs 45.70 ± 51.94 seconds, p = 0.052). No significant difference was observed for residents (3D VR 24.47 ± 40.16 vs 2D 33.52 ± 56.06 seconds, p = 0.564), while in students a significantly shorter time to aneurysm detection was measured using 3D VR models (26.95 ± 35.39 vs 59.16 ± 44.60 seconds, p = 0.015). No significant differences between the modalities for anatomical and descriptive spatial mistakes were observed. Most participants (90%) preferred the 3D VR models for aneurysm detection and description, and only 1 participant (5%) described VR-related side effects such as dizziness or nausea. CONCLUSIONS: VR platforms facilitate aneurysm recognition and understanding of its spatial anatomy, which could make them the preferred method compared to 2D images in the years to come.

Accurate, rapid and reliable, fully automated MRI brainstem segmentation for application in multiple sclerosis and neurodegenerative diseases.

Neurodegenerative disorders, such as Alzheimer's disease (AD) and progressive forms of multiple sclerosis (MS), can affect the brainstem and are associated with atrophy that can be visualized by MRI. Anatomically accurate, large-scale assessments of brainstem atrophy are challenging due to lack of automated, accurate segmentation methods. We present a novel method for brainstem volumetry using a fully-automated segmentation approach based on multi-dimensional gated recurrent units (MD-GRU), a deep learning based semantic segmentation approach employing a convolutional adaptation of gated recurrent units. The neural network was trained on 67 3D-high resolution T1-weighted MRI scans from MS patients and healthy controls (HC) and refined using segmentations of 20 independent MS patients' scans. Reproducibility was assessed in MR test-retest experiments in 33 HC. Accuracy and robustness were examined by Dice scores comparing MD-GRU to FreeSurfer and manual brainstem segmentations in independent MS and AD datasets. The mean %-change/SD between test-retest brainstem volumes were 0.45%/0.005 (MD-GRU), 0.95%/0.009 (FreeSurfer), 0.86%/0.007 (manually edited segmentations). Comparing MD-GRU to manually edited segmentations the mean Dice scores/SD were: 0.97/0.005 (brainstem), 0.95/0.013 (mesencephalon), 0.98/0.006 (pons), 0.95/0.015 (medulla oblongata). Compared to the manual gold standard, MD-GRU brainstem segmentations were more accurate than FreeSurfer segmentations (p < .001). In the multi-centric acquired AD data, the mean Dice score/SD for the MD-GRU-manual segmentation comparison was 0.97/0.006. The fully automated brainstem segmentation method MD-GRU provides accurate, highly reproducible, and robust segmentations in HC and patients with MS and AD in 200 s/scan on an Nvidia GeForce GTX 1080 GPU and shows potential for application in large and longitudinal datasets.

Design and construction of an innovative brain phantom prototype for MRI.

PURPOSE: The purpose of this project was to construct a physical brain phantom for MRI, mimicking structure and T1 relaxation properties of white matter (WM) and gray matter (GM). METHODS: The phantom design comprised 2 compartments, 1 resembling the WM and 1 resembling the GM. Their T1 relaxation times, as assessed using an inversion recovery turbo spin echo sequence, were reproduced using an agar gel doped with contrast agent (CA) and their folding patterns were simulated through a molding-casting procedure using 3D-printed casts and flexible silicone molds. Three versions of the assembling procedure were adopted to build: Phantom1 without any separation; Phantom2 with a varnish layer; and Phantom3 with a thin wax layer between the compartments. RESULTS: Phantom1 was characterized by an immediate diffusion of CA between the 2 compartments. Phantom2 and Phantom3, instead, showed relaxation times and shape comparable with the target ones identified in a healthy control subject (WM: 754 ± 40 ms; GM: 1277 ± 96 ms). Moreover, both compartments revealed intact gyri and sulci. However, the diffusion of CA made Phantom2 stable only for a short period of time. Phantom3 showed stability within a time window of several days but the wax layer between the WM and GM was visible in the MRI. CONCLUSION: Structural and intensity properties of the constructed phantoms are useful in evaluating and validating steps from image acquisition to image processing. Moreover, the described constructing procedure and its modular design make it adjustable to a variety of applications.

Preferential spinal cord volume loss in primary progressive multiple sclerosis.

BACKGROUND: Little is known on longer term changes of spinal cord volume (SCV) in primary progressive multiple sclerosis (PPMS). OBJECTIVE: Longitudinal evaluation of SCV loss in PPMS and its correlation to clinical outcomes, compared to relapse-onset multiple sclerosis (MS) subtypes. METHODS: A total of 60 MS age-, sex- and disease duration-matched patients (12 PPMS, each 24 relapsing-remitting (RRMS) and secondary progressive MS (SPMS)) were analysed annually over 6 years of follow-up. The upper cervical SCV was measured on 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images using a semi-automatic software (CORDIAL), along with the total brain volume (TBV), brain T2 lesion volume (T2LV) and Expanded Disability Status Scale (EDSS). RESULTS: PPMS showed faster SCV loss over time than RRMS ( p < 0.01) and by trend ( p = 0.066) compared with SPMS. In contrast to relapse-onset MS, in PPMS SCV loss progressed independent of TBV and T2LV changes. Moreover, in PPMS, SCV was the only magnetic resonance imaging (MRI) measurement associated with EDSS increase over time ( p < 0.01), as opposed to RRMS and SPMS. CONCLUSION: SCV loss is a strong predictor of clinical outcomes in PPMS and has shown to be faster and independent of brain MRI metrics compared to relapse-onset MS.

State-of-the-art multimodality approach to assist ablations in complex anatomies-From 3D printing to virtual reality.

Imaging of the heart anatomy plays an important role, especially in catheter ablation for the treatment of arrhythmias in adults with congenital heart disease (ACHD). We present a comprehensive overview of the current state-of-the-art modalities available to plan and guide catheter ablation in an ACHD patient. In addition to the clinical assessment of the computed tomography and the integration of 3D reconstructions into the electroanatomical mapping system, 3D printing and virtual reality assessment showed its value in preprocedural planning of the intervention.

The Use of Finite Element Method Analysis for Modeling Different Osteotomy Patterns and Biomechanical Analysis of Craniosynostosis Correction.

PURPOSE: Several post-processing algorithms for 3D visualization of the skull in craniosynostosis with their specific advantages and disadvantages have been already described. The Finite Element Method (FEM) described herein can also be used to evaluate the efficacy of the cutting patterns with respect to an increase in the projected surface area under assumed uniform loading of the manipulated and cut bone segments. METHODS: The FEM analysis was performed. Starting with the classic cranial osteotomies for bifrontal craniotomy and orbital bandeau a virtually mirroring of the unaffected triangular shaped frontal bone was performed to achieve a cup-shaped sphere of constant thickness of 2.5 mm with a radius of 65 mm. Mechanical properties required for the analysis were Young's modulus of 340 MPa and Poisson's ratio of 0.22. Four different cutting patterns from straight to curved geometries have been projected onto the inner surface of the sphere with a cutting depth set to 2/3rds of the shell thickness. The necessary force for the deformation, the resulting tensions and the volume loss due to the osteotomy pattern were measured. RESULTS: Better outcomes were realized with pattern D. The necessary force was 73.6% smaller than the control group with 66N. Best stress distribution was achieved. Curved cutting patterns led to the highest peak of stress and thus to a higher risk of fracture. Straight bone cuts parallel to the corners or to the thighs of the sphere provided a better distribution of stresses with a small area with high stress. Additionally, also with pattern D a surface increase of 20.7% higher than reference was registered. CONCLUSION: As a proof of concept for different cutting geometries for skull molding in the correction of craniosynostosis, this computational model shows that depending of the cutting pattern different biomechanical behavior is achieved.

Reliable and fast volumetry of the lumbar spinal cord using cord image analyser (Cordial).

OBJECTIVE: To validate the precision and accuracy of the semi-automated cord image analyser (Cordial) for lumbar spinal cord (SC) volumetry in 3D T1w MRI data of healthy controls (HC). MATERIALS AND METHODS: 40 3D T1w images of 10 HC (w/m: 6/4; age range: 18-41 years) were acquired at one 3T-scanner in two MRI sessions (time interval 14.9±6.1 days). Each subject was scanned twice per session, allowing determination of test-retest reliability both in back-to-back (intra-session) and scan-rescan images (inter-session). Cordial was applied for lumbar cord segmentation twice per image by two raters, allowing for assessment of intra- and inter-rater reliability, and compared to a manual gold standard. RESULTS: While manually segmented volumes were larger (mean: 2028±245 mm3 vs. Cordial: 1636±300 mm3, p<0.001), accuracy assessments between manually and semi-automatically segmented images showed a mean Dice-coefficient of 0.88±0.05. Calculation of within-subject coefficients of variation (COV) demonstrated high intra-session (1.22-1.86%), inter-session (1.26-1.84%), as well as intra-rater (1.73-1.83%) reproducibility. No significant difference was shown between intra- and inter-session reproducibility or between intra-rater reliabilities. Although inter-rater reproducibility (COV: 2.87%) was slightly lower compared to all other reproducibility measures, between rater consistency was very strong (intraclass correlation coefficient: 0.974). CONCLUSION: While under-estimating the lumbar SCV, Cordial still provides excellent inter- and intra-session reproducibility showing high potential for application in longitudinal trials. KEY POINTS: • Lumbar spinal cord segmentation using the semi-automated cord image analyser (Cordial) is feasible. • Lumbar spinal cord is 40-mm cord segment 60 mm above conus medullaris. • Cordial provides excellent inter- and intra-session reproducibility in lumbar spinal cord region. • Cordial shows high potential for application in longitudinal trials.

Comparative microstructural analysis of bone osteotomies after cutting by computer-assisted robot-guided laser osteotome and piezoelectric osteotome: an in vivo animal study.

Most industrial laser applications utilize computer and robot assistance, for guidance, safety, repeatability, and precision. In contrast, medical applications using laser systems are mostly conducted manually. The advantages can be effective only when the system is coupled to a robotic guidance, as operating by hand does not reach the required accuracy. We currently developed the first laser osteotome which offers preoperative planning based on CT data, robot guidance, and a precise execution of the laser cuts. In an animal trial, our system was used to create a grid pattern of the same depth on the inner layer of parietal bone in 12 adult sheep. The same bone cuts were done with piezoelectric osteotome on the contralateral side. The micro-CT and histological analysis showed more new mineralized bone in the laser group compared to the piezoelectric group. As well, a cutting pattern with especially a constant osteotomy depth in the laser group was demonstrated. The here presented autonomous osteotomy tool shows not only an advantage in early bone healing stage but additionally sharp bone cuts with a very high accuracy and freely selectable design cuts.

Simultaneous acquisition of image and navigator slices using CAIPIRINHA for 4D MRI.

PURPOSE: Respiratory organ motion is still the major challenge of various image-guided treatments in the abdomen. Dynamic organ motion tracking, necessary for the treatment control, can be performed with volumetric time-resolved MRI that sequentially acquires one image and one navigator slice. Here, a novel imaging method is proposed for truly simultaneous high temporal resolution acquisition. METHODS: A standard balanced steady state free precession sequence was modified to simultaneously acquire two superimposed slices with different phase cycles, namely an image and a navigator slice. Instead of multiband RF pulses, two separate RF pulses were used for the excitation. Images were reconstructed using offline CAIPIRINHA reconstruction. Phantom and in vivo measurements of healthy volunteers were performed and evaluated. RESULTS: Phantom and in vivo measurements showed good image quality with high signal-to-noise ratio (SNR) and no reconstruction issues. CONCLUSION: We present a novel imaging method for truly simultaneous acquisition of image and navigator slices for four-dimensional (4D) MRI of organ motion. In this method, the time lag between the sequential acquisitions is eliminated, leading to an improved accuracy of organ motion models, while CAIPIRINHA reconstruction results in an improved SNR compared with an existing 4D MRI approach.

A comparative investigation of bone surface after cutting with mechanical tools and Er:YAG laser.

BACKGROUND AND OBJECTIVES: Despite of the long history of medical application, laser ablation of bone tissue became successful only recently. Laser bone cutting is proven to have higher accuracy and to increase bone healing compared to conventional mechanical bone cutting. But the reason of subsequent better healing is not biologically explained yet. In this study we present our experience with an integrated miniaturized laser system mounted on a surgical lightweight robotic arm. STUDY DESIGN/MATERIALS AND METHODS: An Erbium-doped Yttrium Aluminium Garnet (Er:YAG) laser and a piezoelectric (PZE) osteotome were used for comparison. In six grown up female Göttingen minipigs, comparative surgical interventions were done on the edentulous mandibular ridge. Our laser system was used to create different shapes of bone defects on the left side of the mandible. On the contralateral side, similar bone defects were created by PZE osteotome. Small bone samples were harvested to compare the immediate post-operative cut surface. RESULTS: The analysis of the cut surface of the laser osteotomy and conventional mechanical osteotomy revealed an essential difference. The scanning electron microscopy (SEM) analysis showed biologically open cut surfaces from the laser osteotomy. The samples from PZE osteotomy showed a flattened tissue structure over the cut surface, resembling the "smear layer" from tooth preparation. CONCLUSIONS: We concluded that our new finding with the mechanical osteotomy suggests a biological explanation to the expected difference in subsequent bone healing. Our hypothesis is that the difference of surface characteristic yields to different bleeding pattern and subsequently results in different bone healing. The analyses of bone healing will support our hypothesis.