Presurgical Planning Research Articles

Establishing a Point-of-Care Virtual Planning and 3D Printing Program.

Virtual surgical planning (VSP) and three-dimensional (3D) printing have become a standard of care at our institution, transforming the surgical care of complex patients. Patient-specific, anatomic models and surgical guides are clinically used to improve multidisciplinary communication, presurgical planning, intraoperative guidance, and the patient informed consent. Recent innovations have allowed both VSP and 3D printing to become more accessible to various sized hospital systems. Insourcing such work has several advantages including quicker turnaround times and increased innovation through collaborative multidisciplinary teams. Centralizing 3D printing programs at the point-of-care provides a greater cost-efficient investment for institutions. The following article will detail capital equipment needs, institutional structure, operational personnel, and other considerations necessary in the establishment of a POC manufacturing program.

Patient-specific implants in orbital reconstruction.

Advances in the use of patient-specific implants (PSIs) and virtual surgical planning (VSP) for reconstruction of primary and secondary traumatic orbital defects are explored. PSIs and VSP are emerging technologies that promise to make complex orbital reconstructions safer and more predictable for patients. Recent studies highlight principles of implant design, the novel use of multiunit implant constructs, and utility of intraoperative imaging adjuncts to achieve favorable outcomes. This article summarizes recent developments in PSIs for orbital reconstruction. A complete workflow including presurgical planning, execution in the operating room, postoperative analysis, and avoidance of common pitfalls and implant design errors are reviewed.

The Effects of Body Mass Index & Spine Flexibility on Surgical Outcomes for Patients with Adolescent Idiopathic Scoliosis

Retrospective cohort study. To investigate the relationship between body mass index (BMI), spine flexibility index (FI), and their combined effects on adolescent idiopathic scoliosis (AIS) surgical outcomes. BMI and FI are two factors considered during presurgical planning for AIS correction, but there is sparse research about their relationship. We hypothesize that AIS patients with increased BMI may be associated with decreased FI-a combination which could lead to worsened surgical outcomes. AIS patients ages 11 to 19 at surgery, who underwent posterior fusion at a single center from 2011 to 2017, were reviewed. Patients without proper radiographs to assess FI, or a previous spine surgical history, were excluded. FI was categorized as stiff (FI<50) or flexible (FI≥50), and patients were separated by major curve region. BMI was categorized as underweight (less than fifth percentile), healthy weight (fifth-85th percentile), overweight (85th-95th percentile), or obese (>95th percentile). Regression analysis was conducted to test BMI and FI's effects on intraoperative, immediate postoperative, and two-year postoperative outcomes. A total of 543 patients (82% female), with an average age of 14.9 years, were included. In all, 346 patients had available two-year data. A 10% increase in BMI was associated with a 1.3% decrease in FI for patients with major thoracolumbar/lumbar curves ( P =0.01). Obese patients were most likely to have a postoperative complication ( P =0.003) or a two-year complication ( P =0.04). Revision surgery occurred after 58% of postoperative complications (15/26) and 80% of two-year complications (4/5). FI was negatively associated with initial curve magnitude ( P <0.001), operative time ( P =0.02), and blood loss ( P =0.02). Overweight patients with flexible curves were 10.0 times more likely to sustain a postoperative complication than healthy weight patients with stiff curves ( P =0.001). Elevated BMI was associated with decreased FI in patients with major thoracolumbar/lumbar curves. Patients with a high BMI and high FI were associated with the greatest risk of postoperative complication.

Comparison of the Efficacy of the Panoramic and Cone Beam Computed Tomography Imaging Methods in the Surgical Planning of the Maxillary All-On-4, M-4, and V-4.

This study is aimed at analyzing the difference between the measurements made according to certain anatomical signs of the maxillary jaw using panoramic radiography and cone beam computed tomography (CBCT) to decide whether to use all-on-4, M-4, or V-4 configuration to prevent complications caused by incorrect measurements during the presurgical planning stage of the placement of implants in the all-on-4 technique. A retrospective study was conducted with 50 patients with upper edentulous jaws suitable for the all-on-4 technique, who underwent preoperative panoramic radiography and cone beam computed tomography evaluation for dental implant surgery. The shortest vertical distances between anatomical structures were measured. Measurements were made independently by two oral and maxillofacial surgeons, one experienced and the other inexperienced. A statistically significant difference was found between the mean values according to gender (p=0.045). When the measurements made by the experienced surgeon and the inexperienced surgeon were compared, there was no significant difference between panoramic radiography and cone beam computed tomography. In situations where bone measurements are required for deciding on all-on-4 or one of its configurations (M-4 and V-4), it was found that panoramic radiography gives significantly incorrect results compared to cone beam computed tomography (p<0.05). Cone beam computed tomography is more reliable than panoramic radiography and eliminates the margin of error in the planning of all-on-4 or its variations to be made by either an experienced or an inexperienced oral surgeon.

Voxel-Based Morphometric MRI Postprocessing-Assisted Laser Interstitial Thermal Therapy for Focal Cortical Dysplasia-Suspected Lesions: Technique and Outcomes.

MRI-guided laser interstitial thermal therapy (MRgLITT) is a novel treatment modality for focal cortical dysplasia (FCD). However, identifying the location and extent of subtle FCD by visual analysis during MRgLITT remains challenging. To introduce voxel-based morphometric MRI postprocessing into the procedure of MRgLITT for FCD-suspected lesions and assess the complementary value of the MRI postprocessing technique for the trajectory design and thermal parameter setting of MRgLITT. Junction and normalized fluid-attenuated inversion recovery signal intensity images were used to detect the gray-white matter junction blurring and cortical fluid-attenuated inversion recovery hyperintensity, respectively. According to the 2 postprocessing images, the region of interest (ROI) for ablation was drawn. The main principle of presurgical planning is that the trajectory of the laser fiber was designed as far as possible along the long axis of the ROI while the extent of planned ablation covered the entire ROI. The subsequent intraoperative procedure was performed under the guidance of the presurgical plan. Nine patients with epilepsy with FCD-suspected lesions underwent MRgLITT with the assistance of MRI postprocessing images. Among them, 4 patients were junction positive, 2 patients were normalized fluid-attenuated inversion recovery signal intensity positive, and the remaining 3 patients were positive for both. Postsurgical MRI demonstrated that the ROIs were ablated entirely in 7 patients. Engel Ia, Ib, and IV scores were obtained at 1-year follow-up for 6, 1, and 2 patients, respectively. MRI postprocessing provides complementary information for designing the laser fiber trajectory and subsequent ablation for FCDs.

Transfer Learning from Healthy to Unhealthy Patients for the Automated Classification of Functional Brain Networks in fMRI

Functional Magnetic Resonance Imaging (fMRI) is an essential tool for the pre-surgical planning of brain tumor removal, which allows the identification of functional brain networks to preserve the patient’s neurological functions. One fMRI technique used to identify the functional brain network is the resting-state-fMRI (rs-fMRI). This technique is not routinely available because of the necessity to have an expert reviewer who can manually identify each functional network. The lack of sufficient unhealthy data has so far hindered a data-driven approach based on machine learning tools for full automation of this clinical task. In this article, we investigate the possibility of such an approach via the transfer learning method from healthy control data to unhealthy patient data to boost the detection of functional brain networks in rs-fMRI data. The end-to-end deep learning model implemented in this article distinguishes seven principal functional brain networks using fMRI images. The best performance of a 75% correct recognition rate is obtained from the proposed deep learning architecture, which shows its superiority over other machine learning algorithms that were equally tested for this classification task. Based on this best reference model, we demonstrate the possibility of boosting the results of our algorithm with transfer learning from healthy patients to unhealthy patients. This application of the transfer learning technique opens interesting possibilities because healthy control subjects can be easily enrolled for fMRI data acquisition since it is non-invasive. Consequently, this process helps to compensate for the usual small cohort of unhealthy patient data. This transfer learning approach could be extended to other medical imaging modalities and pathology.

Impact of contrast-enhanced mammography in surgical management of breast cancers for women with dense breasts: a dual-center, multi-disciplinary study in Asia

ObjectiveTo evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts.MethodsWe conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.2) who underwent pre-surgical CEM imaging across two Asian institutions (Singapore and Taiwan). Majority (95.5%) of patients had dense breast tissue (BI-RADS category C or D). Surgical decision was recorded in a simulated blinded multi-disciplinary team setting on two separate scenarios: (i) pre-CEM setting with standard imaging, and clinical and histopathological results; and (ii) post-CEM setting with new imaging and corresponding histological findings from CEM. Alterations in surgical plan (if any) because of CEM imaging were recorded. Predictors CEM of patients who benefitted from surgical plan alterations were evaluated using logistic regression.ResultsCEM resulted in altered surgical plans in 36 (18%) of 200 patients in this study. CEM discovered clinically significant larger tumor size or extent in 24 (12%) patients and additional tumors in 12 (6%) patients. CEM also detected additional benign/false-positive lesions in 13 (6.5%) of the 200 patients. Significant predictors of patients who benefitted from surgical alterations found on multivariate analysis were pre-CEM surgical decision for upfront breast conservation (OR, 7.7; 95% CI, 1.9-32.1; p = 0.005), architectural distortion on mammograms (OR, 7.6; 95% CI, 1.3–42.9; p = .022), and tumor size of ≥ 1.5 cm (OR, 1.5; 95% CI, 1.0-2.2; p = .034).ConclusionCEM is an effective imaging technique for pre-surgical planning for Asian breast cancer patients with dense breasts.Key Points• CEM significantly altered surgical plans in 18% (nearly 1 in 5) of this Asian study cohort with dense breasts.• Significant patient and imaging predictors for surgical plan alteration include (i) patients considered for upfront breast-conserving surgery; (ii) architectural distortion lesions; and (iii) tumor size of ≥ 1.5 cm.• Additional false-positive/benign lesions detected through CEM were uncommon, affecting only 6.5% of the study cohort.

3D printing in aortic endovascular therapies.

Endovascular treatment of aortic disease, including aneurysm or dissection, is expanding at a rapid pace. Often, the specific patient anatomy in these cases is complex. Additive manufacturing, also known as three-dimensional (3D) printing, is especially useful in the treatment of aortic disease, due to its ability to manufacture physical models of complex patient anatomy. Compared to other surgical procedures, endovascular aortic repair can readily exploit the advantages of 3D printing with regard to operative planning and preoperative training. To date, there have been numerous uses of 3D printing in the treatment of aortic pathology as an adjunct in presurgical planning and as a basis for training modules for fellows and residents. In this review, we summarize the current uses of 3D printing in the endovascular management of aortic disease. We also review the process of producing these models, the limitations of their applications, and future directions of 3D printing in this field.

Principles and strategies for step-by-step AVM excision.

Arteriovenous malformations (AVMs) are some of the most challenging surgical entities. Like any challenging surgical procedure, AVM surgery is a series of basic but fundamental steps, each with its own nuances. Despite a myriad of published material regarding AVMs, there are few succinct illustrated summaries of these steps with an accompanying elucidation of the most common pitfalls. This paper provides a step-by-step description and illustration of the basic surgical principles of AVM microsurgical resection, focusing on the main key points and addressing the critical issues that surround this surgery. Deep anatomical knowledge and presurgical planning of these basic steps, combined with good contingency management skills, are paramount for an effective and safe AVM surgery.

Synthesis and characterisation of a cancerous liver for presurgical planning and training applications

ObjectivesOncology surgeons use animals and cadavers in training because of a lack of alternatives. The aim of this work was to develop a design methodology to create synthetic liver models...

How I do it: resection of spinal cord cavernous malformation.

Spinal cord cavernous malformations (CMs) account for 5 to 12% of all spinal vascular malformations. Surgical removal is indicated in symptomatic patients, especially if the CM comes close to the dorsal or lateral surface of the spinal cord. Spinal cord CMs pose critical challenges for the potential of severe disabling complications. We described the step-by-step surgical principles of spinal cord CM microsurgical resection. The main surgical steps are also illustrated in an accompanying operative video. Pre-surgical planning of the basic steps and good contingency management skills are paramount for an effective and safe spinal cord CM excision.

Toward Emulating Human Movement: Adopting a Data-Driven Bitmap-Based "Voxel" Multimaterial Workflow to Create a Flexible 3D Printed Neonatal Lower Limb.

It is increasingly common to produce physical anatomical medical models using high-fidelity multiproperty 3D printing to assist doctor-patient communication, presurgical planning, and surgical simulation. Currently, most medical models are created using image thresholding and traditional mesh-based segmentation techniques to produce mono-material boundaries (STL file formats) of anatomical features. Existing medical modeling manufacturing methods restrict shape specification to one material or density, which result in anatomically simple 3D printed medical models with no gradated material qualities. Currently, available high-resolution functionally graded multimaterial 3D printed medical models are rigid and do not represent biomechanical movement. To bypass the identified limitations of current 3D printing medical modeling workflows, we present a bitmap-based "voxel" multimaterial additive manufacturing workflow for the production of highly realistic and flexible anatomical models of the neonatal lower limb using computed tomographic ("CT") data. By interpolating and re-slicing a biomedical volumetric data set at the native 3D printer z resolution of 27 μm and using CT scan attenuation properties (Hounsfield units) to guide material mixing ratios, producing highly realistic models of the neonatal lower limb at a significantly faster rate than other manufacturing methods. The presented medical modeling workflow has considerable potential to improve medical modeling manufacturing methods by translating medical data directly into 3D printing files aiding in anatomical education and surgical simulation practices, especially in neonatal research and clinical training.

Impact of high-density EEG in presurgical evaluation for refractory epilepsy patients

ObjectiveElectrical source localization (ESI) can help to identify the seizure onset zone or propagation zone, but it is unclear how dipole localization techniques influence surgical planning. MethodsPatients who received a high density (HD)-EEG from 7/2014–7/2019 at Stanford were included if they met the following inclusion criteria: (1) adequate epileptiform discharges were recorded for source localization analysis, (2) underwent surgical treatment, which was at least 6 months before the survey. Interictal ESI was performed with the LORETA method on age matched MRIs. Six neurophysiologists from the Stanford Epilepsy Program independently reviewed each case through an HIPPA-protected online survey. The same cases were presented again with additional data from the HD-EEG study. Ratings of how much the HD-EEG findings added value and in what way were recorded. ResultsFifty out of 202 patients met the inclusion criteria, providing a total of 276 h of HDEEG recordings. All patients had video EEG recordings and at least one brain MRI, 88 % had neuropsychological testing, 78 % had either a PET or SPECT scan. Additional HD-EEG information was rated as helpful in 83.8 %, not useful in 14.4 % and misleading in 1.8 % of cases. In 20.4 % of cases the HD-EEG information altered decision-making in a major way, such as choosing a different surgical procedure, avoidance of invasive recording or suggesting placement of invasive electrodes in a lobe not previously planned. In 21.5 % of cases, HD-EEG changed the plan in a minor way, e.g., extra invasive electrodes near the previously planned sites in the same sub-lobar region. In 42.3 % cases, HD-EEG did not change their plan but provided confirmation. In cases with normal MRI, additional HD-EEG information was more likely to change physicians’ decision making during presurgical process when compared to the cases with MRI-visible lesions (53.3 % vs. 34.3 %, p = 0.002). Among patients achieving Engel class I/II outcome, the concordance rate of HD-EEG and resection zone was 64.7 % versus 35.3 % with class III/IV (p = 0.028). ConclusionHD-EEG assists presurgical planning for refractory epilepsy patients, with a higher yield in patients with non-lesional MRIs. Concordance of HD-EEG dipole analysis localization and resection site is a favorable outcome indicator.

Intracranial brain-computer interface spelling using localized visual motion response

Intracranial brain-computer interfaces (BCIs) can assist severely disabled persons in text communication and environmental control with high precision and speed. Nevertheless, sustainable BCI implants require minimal invasiveness. One of the implantation strategies is to adopt localized and robust cortical activities to drive BCI communication and to make a precise presurgical planning. The visual motion response is a good candidate for inclusion in this strategy because of its focal activity over the middle temporal visual area (MT). Here, we developed an intracranial BCI for spelling, utilizing only three electrodes over the MT area. The best recording electrodes were decided by preoperative functional magnetic resonance imaging (MRI) localization of the MT, and local neural activities were further enhanced by differential rereferencing of these electrodes. The BCI spelling system was validated both offline and online by five epilepsy patients, achieving the fastest speed of 62 bits/min, i.e., 12 characters/min. Moreover, the response patterns of dual-directional visual motion stimuli provided an additional dimension of BCI target encoding and paved the way for a higher information transfer rate of intracranial BCI spelling.

Harnessing artificial intelligence to automate delineation of volumetric breast cancers from magnetic resonance imaging to improve tumor characterization.

597 Background: Automated breast tumor identification and segmentation in magnetic resonance imaging (MRI) is a difficult and crucial area of study in breast cancer research. Artificial intelligence (AI) models are increasingly being developed for automated localization of lesions in imaging studies to facilitate quantitative assessment of features for improved diagnostic, prognostic and predictive performance. Such models have had success in detecting breast cancers in mammography, ultrasound and CT, but few have achieved three-dimensional (3D) volumetric tumor segmentation from breast MRI. The purpose of this study was to apply two state-of-the-art AI – specifically, deep learning (DL) - algorithms to 3D MRI breast cancer data and identify the higher performing algorithm for precise segmentation of breast tumors. Methods: We evaluated pre-treatment, T1 post-gadolinium contrast enhanced breast MRI from 222 patients with known breast cancers (n = 262). Images were split into training (n = 142), validation (n = 36), and hold-out test (n = 44) datasets. Two DL algorithms, U-Net and VAE-UNet, were trained to classify tumors on the training dataset across 1000 epochs. The output for each is a precise localization and segmentation of each tumor at the pixel level from every MRI image. We evaluated the performance of each algorithm using 5-fold cross-validation and testing on the validation and test sets. We calculated a dice accuracy score for each model as the performance comparison metric. Results: The highest dice accuracy score achieved on the validation dataset by generic U-Net was 83.38%, with an average across 1000 epochs of 62.41%. The highest dice accuracy achieved on the validation dataset by VAE-UNet was 82.62%, with an average across epochs of 61.28%. On our test dataset, the highest dice accuracy score achieved by U-Net was 93.09%, with an average across epochs of 66.31%, and the highest accuracy score for VAE-UNet was 90.98%, with average across epochs of 50.47%. Although U-Net appeared to perform slightly better than VAE-Unet for most cases, there were distinct cases where VAE-UNet outperformed U-Net (dice score up to 59% better than U-Net). Subsequent analysis indicated that VAE-UNet preferentially outperforms U-Net for tumors with low sphericity (p = 0.001). Conclusions: Our results suggest that U-Net is well suited for segmenting breast tumors from breast MRI in most cases, but that VAE-UNet outperforms U-Net when the tumor shapes are less spherical. Our findings could inform the choice of DL algorithms in research and clinical endeavors that rely on accurate breast cancer tumor segmentation. In particular, these two tools could be configured to facilitate tumor assessment from breast MRI in the clinical setting for: breast cancer screening in high-risk patient populations, pre-surgical planning, and monitoring of treatment response.

Revisiting maxillary implant overdentures in 2022: A topic review

The challenge for general dental practitioners to provide maxillary implant overdenture treatment for their patients is complicated by multiple, diverse parameters, compared to mandibular implant overdentures. This topic review on maxillary implant overdentures takes into consideration the specifications and challenges of different prosthodontic treatment options for clinicians in 2022. A broad search of the published literature was performed using MEDLINE and PubMed to identify pertinent articles published in English from 1990 to 2021. From an original total of 1176 titles, 106 references were selected. They were reviewed and categorized with respect to seven factors related to the prosthodontic design. These were interarch restorative space, implant number, implant distribution and spread, overdenture base reinforcement, palatal coverage, selection of attachment system and splinted/unsplinted prosthodontic designs. They influence clinical and patient outcomes in terms of implant and prosthesis success, support, retention, prosthodontic maintenance and satisfaction. Maxillary implant overdentures are a reliable treatment option for general dental practitioners, once competent with mandibular overdentures. The decision for adequate treatment for each individual patient is influenced by a diversity of parameters with clinicians needing to have a thorough knowledge and understanding of the anatomic obstacles, facial aesthetics, phonetics, and complete denture principles for essential pre-surgical and prosthodontic treatment planning. Currently there is no optimal number of implants, nor preferred attachment system, regardless of palatal coverage design. There are emerging trends of more evidence for use of reduced number of unsplinted implants simplifying procedures for general dental practice.

P.098 Usefulness of language mapping during cortical stimulation for presurgical planning in Stereo-encephalograph

Background: Background: Language determination is a pivotal part of presurgical investigations. Presurgical cortical stimulation (CS) with language mapping (LM) in patients with intracranial recordings (SEEG) is a growing practice in some Comprehensive Epilepsy Centers. Methods: Methods: This retrospective, single center study included patients implanted with SEEG that underwent CS for LM in our Epilepsy Monitoring Unit. We describe frequencies, demographic characteristics of these patients and whether or not CS with LM was useful. Results: Results: From January 2015 to June2021, a total of 177 patients were implanted with SEEG and analyzed. 95 patients had CS and 44 of these had CS with LM. The mean age was 33 (ranging from 15-70). During LM, anomia was induced in 26 (58%), speech arrest in 22 (49%), paraphasic errors in 13 (29%), and hesitation in 9 (20%). LM results were recorded as influencing surgical decision in 7 (16%) patients, 4 (9%) did not undergo surgery due to expected language deficits and 3 (7%) proceeded with surgery due to an acceptable risk of language deficit. Conclusions: Conclusions: Cortical stimulation language mapping is useful for decision-making in presurgical evaluation and should be encouraged whenever involvement of language is suspected when determining the epileptogenic zone.

Prospective pre-operative 3-T MR neurography peripheral nerve mapping of upper extremity amputations implanted with FAST-LIFE electrode interfaces of robotic hands: technical report.

Fascicular targeting of longitudinal intrafascicular electrode (FAST-LIFE) interface enables hand dexterity with exogenous electrical microstimulation for sensory restoration, custom neural recording hardware, and deep learning-based artificial intelligence for motor intent decoding. The purpose of this technical report from a prospective pilot study was to illustrate magnetic resonance neurography (MRN) mapping of hand and nerve anatomy in amputees and incremental value of MRN over electrophysiology findings in pre-surgical planning of FAST-LIFE interface (robotic hand) patients. After obtaining informed consent, patients with upper extremity amputations underwent pre-operative 3-T MRN, X-rays, and electrophysiology. MRN findings were correlated with electrophysiology reports. Descriptive statistics were performed. Five patients of ages 21-59years exhibited 3/5 partial hand amputations, and 2/5 transradial amputations on X-rays. The median and ulnar nerve end bulb neuromas measured 10.1 ± 3.04mm (range: 5.5-14mm, median: 10.5mm) and 10.9 ± 7.64mm (2-22mm, 9.75mm), respectively. The ADC of median and ulnar nerves were increased at 1.64 ± 0.1 × 10-3 mm2/s (range: 1.5-1.8, median: 1.64 × 10-3 mm2/s) and 1.70 ± 0.17 × 10-3 mm2/s (1.49-1.98 × 10-3 mm2/s, 1.65 × 10-3 mm2/s), respectively. Other identified lesions were neuromas of superficial branch of the radial nerve and anterior interosseous nerve. On electrophysiology, 2/5 reports were unremarkable, 2/5 showed mixed motor-sensory neuropathies of median and ulnar nerves along with radial sensory neuropathy, and 1/5 showed sensory neuropathy of lateral cutaneous nerve of the forearm. All patients regained naturalistic sensations and motor control of digits. 3-T MRN allows excellent demonstration of forearm and hand nerve anatomy, altered diffusion characteristics, and their neuromas despite unremarkable electrophysiology for pre-surgical planning of the FAST-LIFE (robotic hand) interfaces.

Clinical and CT sialography findings in 22 dogs with surgically confirmed sialoceles.

Sialoceles are an uncommon canine salivary gland disease, and complete surgical resection is important for a positive outcome. Radiographic sialography has been described as a diagnostic test for presurgical planning; however, superimposition artifacts may limit the diagnosis and detection of all affected glands. Computed tomographic (CT) sialography is a promising technique for delineating the salivary gland apparatus. The aims of this retrospective, observational study were to describe clinical and CT sialographic findings in a group of dogs with confirmed sialoceles, to determine the sensitivity of CT sialography for detecting affected salivary glands using surgery as the reference standard and to determine interobserver agreement for CT sialographic assessments. Dogs were included if they underwent a CT sialography study followed by surgical resection of the diseased gland(s) and histopathological analysis. Computed tomography sialography studies of dogs with surgically confirmed sialoceles (n = 22) were reviewed by a European College of Veterinary Diagnostic Imaging (ECVDI)-certified radiologist and an ECVDI resident. Interobserver agreement was calculated using Cohen's kappa statistics. CT sialography results were compared to surgical findings to determine sensitivity. Contrast leakage was detected in 12 of 22 dogs (54.5%), with intrasialocele leakage being most frequently observed (7/12, 58.3%). There was substantial agreement (κ = 0.70) between reviewers identifying diseased glands, substantial agreement (κ = 0.62) on the diagnostic quality, and no to slight agreement (к = 0.13) in the detection of contrast leakage. The overall sensitivity of CT sialography to detect surgically confirmed diseased glands was 66.7% (95% confidence interval: 48.8-80.8). In conclusion, these findings support the use of CT sialography as an adjunct diagnostic test for treatment planning in dogs with sialoceles.

Semi-automated digital workflow to design and evaluate patient-specific mandibular reconstruction implants

The reconstruction of large mandibular defects with optimal aesthetic and functional outcomes remains a major challenge for maxillofacial surgeons. The aim of this study was to design patient-specific mandibular reconstruction implants through a semi-automated digital workflow and to assess the effects of topology optimization on the biomechanical performance of the designed implants. By using the proposed workflow, a fully porous implant (LA-implant) and a topology-optimized implant (TO-implant) both made of Ti–6Al–4V ELI were designed and additively manufactured using selective laser melting. The mechanical performance of the implants was predicted by performing finite element analysis (FEA) and was experimentally assessed by conducting quasi-static and cyclic biomechanical tests. Digital image correlation (DIC) was used to validate the FE model by comparing the principal strains predicted by the FEM model with the measured distribution of the same type of strain. The numerical predictions were in good agreement with the DIC measurements and the predicted locations of specimen failure matched the actual ones. No statistically significant differences (p < 0.05) in the mean stiffness, mean ultimate load, or mean ultimate displacement were detected between the LA- and TO-implant groups. No implant failures were observed during quasi-static or cyclic testing under masticatory loads that were substantially higher (>1000 N) than the average maximum biting force of healthy individuals. Given its relatively lower weight (16.5%), higher porosity (17.4%), and much shorter design time (633.3%), the LA-implant is preferred for clinical application. This study clearly demonstrates the capability of the proposed workflow to develop patient-specific implants with high precision and superior mechanical performance, which will greatly facilitate cost- and time-effective pre-surgical planning and is expected to improve the surgical outcome.