Patient-specific simulation for tracheobronchial reconstruction procedures using 3-dimensional operable models: A proof-of-concept study.
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ABSTRACT:
SUBMITTER: Hashimoto K
PROVIDER: S-EPMC9366179 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
Publications
Patient-specific simulation for tracheobronchial reconstruction procedures using 3-dimensional operable models: A proof-of-concept study.
Hashimoto Kohei K Omura Kenshiro K Iwamoto Naoya N Ichinose Junji J Matsuura Yosuke Y Nakao Masayuki M Mun Mingyon M
JTCVS techniques 20220221
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Project description:Dynamic contrast-enhanced (DCE) perfusion imaging has shown great potential to non-invasively assess cancer development and its treatment by their characteristic tissue signatures. Different tracer kinetics models are being applied to estimate tissue and tumor perfusion parameters from DCE perfusion imaging. The goal of this work is to provide an in silico model-based pipeline to evaluate how these DCE imaging parameters may relate to the true tissue parameters. As histology data provides detailed microstructural but not functional parameters, this work can also help to better interpret such data. To this aim in silico vasculatures are constructed and the spread of contrast agent in the tissue is simulated. As a proof of principle we show the evaluation procedure of two tracer kinetic models from in silico contrast-agent perfusion data after a bolus injection. Representative microvascular arterial and venous trees are constructed in silico. Blood flow is computed in the different vessels. Contrast-agent input in the feeding artery, intra-vascular transport, intra-extravascular exchange and diffusion within the interstitial space are modeled. From this spatiotemporal model, intensity maps are computed leading to in silico dynamic perfusion images. Various tumor vascularizations (architecture and function) are studied and show spatiotemporal contrast imaging dynamics characteristic of in vivo tumor morphotypes. The Brix II also called 2CXM, and extended Tofts tracer-kinetics models common in DCE imaging are then applied to recover perfusion parameters that are compared with the ground truth parameters of the in silico spatiotemporal models. The results show that tumor features can be well identified for a certain permeability range. The simulation results in this work indicate that taking into account space explicitly to estimate perfusion parameters may lead to significant improvements in the perfusion interpretation of the current tracer-kinetics models.
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Project description:Introduction: Severe mitral regurgitation (MR) is a mitral valve disease that can lead to lifethreatening complications. MitraClip (MC) therapy is a percutaneous solution for patients who cannot tolerate surgical solutions. In MC therapy, a clip is implanted in the heart to reduce MR. To achieve optimal MC therapy, the cardiologist needs to foresee the outcomes of different scenarios for MC implantation, including the location of the MC. Although finite element (FE) modeling can simulate the outcomes of different MC scenarios, it is not suitable for clinical usage because it requires several hours to complete. Methods: In this paper, we used machine learning (ML) to predict the outcomes of MC therapy in less than 1 s. Two ML algorithms were used: XGBoost, which is a decision tree model, and a feed-forward deep learning (DL) model. The MC location, the geometrical attributes of the models and baseline stress and MR were the features of the ML models, and the predictions were performed for MR and maximum von Mises stress in the leaflets. The parameters of the ML models were determined to achieve the minimum errors obtained by applying the ML models on the validation set. Results: The results for the test set (not used during training) showed relative agreement between ML predictions and ground truth FE predictions. The accuracy of the XGBoost models were better than DL models. Mean absolute percentage error (MAPE) for the XGBoost predictions were 0.115 and 0.231, and the MAPE for DL predictions were 0.154 and 0.310, for MR and stress, respectively. Discussion: The ML models reduced the FE runtime from 6 hours (on average) to less than 1 s. The accuracy of ML models can be increased by increasing the dataset size. The results of this study have important implications for improving the outcomes of MC therapy by providing information about the outcomes of MC implantation in real-time.
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Project description:We developed a model for estimating demographic rates and population abundance based on multiple data sets revealing information about population age- and sex structure. Such models have previously been described in the literature as change-in-ratio models, but we extend the applicability of the models by i) using time series data allowing the full temporal dynamics to be modelled, by ii) casting the model in an explicit hierarchical modelling framework, and by iii) estimating parameters based on Bayesian inference. Based on sensitivity analyses we conclude that the approach developed here is able to obtain estimates of demographic rate with high precision whenever unbiased data of population structure are available. Our simulations revealed that this was true also when data on population abundance are not available or not included in the modelling framework. Nevertheless, when data on population structure are biased due to different observability of different age- and sex categories this will affect estimates of all demographic rates. Estimates of population size is particularly sensitive to such biases, whereas demographic rates can be relatively precisely estimated even with biased observation data as long as the bias is not severe. We then use the models to estimate demographic rates and population abundance for two Norwegian reindeer (Rangifer tarandus) populations where age-sex data were available for all harvested animals, and where population structure surveys were carried out in early summer (after calving) and late fall (after hunting season), and population size is counted in winter. We found that demographic rates were similar regardless whether we include population count data in the modelling, but that the estimated population size is affected by this decision. This suggest that monitoring programs that focus on population age- and sex structure will benefit from collecting additional data that allow estimation of observability for different age- and sex classes. In addition, our sensitivity analysis suggests that focusing monitoring towards changes in demographic rates might be more feasible than monitoring abundance in many situations where data on population age- and sex structure can be collected.
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Project description:BackgroundsLong-segment airway defect reconstruction, especially when carina is invaded, remains a challenge in clinical setting. Previous attempts at bioengineered carina reconstruction failed within 90 days due to delayed revascularization and recurrent infection.MethodsTo establish the feasibility of carina bioengineering use In-Vivo Bioreactor technique. Uncontrolled single-center cohort study including three patients with long-segment airway lesions invading carina. Radical resection of the lesions was performed using standard surgical techniques. After resection, In-Vivo Bioreactor airway reconstruction was performed using a nitinol stent wrapped in two layers of acellularized dermis matrix (ADM). Two Port-a-Cath catheters connected to two portable peristaltic pumps were inserted between the ADM layers. The implanted bioengineered airway was continuously perfused with an antibiotic solution via the pump system. Peripheral total nucleated cells (TNCs) were harvested and seeded into the airway substitute via a Port-a-Cath twice a week for 1 month. The patients were treated as a bioreactor for in situ regeneration of their own bioengineered airway substitute.ResultsThree patients were included in the study (mean age, 54.7 years). The first patient underwent 8 cm long trachea and carina reconstruction, the second patient 6 cm long trachea, carina and main bronchus reconstruction. The third patient right main bronchus and carina reconstruction. Major morbidity included gastric retention and pneumonia. All three patients survived till last follow-up and bronchoscopy follow-up showed well-vascularized regenerated tissue without leakage.ConclusionsIn this uncontrolled study, In-Vivo Bioreactor technique demonstrated potential to be applied for long-segment trachea, carina and bronchi reconstruction. Further research is needed to assess efficacy and safety.
| S-EPMC7354144 | biostudies-literature
Project description:ObjectiveSlide tracheoplasty is the standard technique to repair congenital long-segment tracheal stenosis. This operation most commonly requires median sternotomy, which has drawbacks in young children. We hypothesized that a transcervical approach without sternotomy would be feasible if done with a single-port robotic system.MethodsThis proof-of concept study was performed in 2 small adult cadavers using a single-port robotic surgical system via a small neck incision. Relevant information, including operative time and details of operative technique, were recorded.ResultsLong-segment slide tracheoplasty was completed successfully in 2 cadavers using a small neck incision and a single-port robotic surgical system. Strengths and pitfalls of the technique were identified, including technical refinements from the first attempt to the second. Operative time for robotic mobilization, incision, and anastomosis of the trachea was comparable to standard open approaches.ConclusionsSmall-incision transcervical slide tracheoplasty, assisted by a single-port surgical robotic system, is feasible in a human cadaver. More work is needed to determine safety and applicability in live patients, particularly in children.
| S-EPMC9735391 | biostudies-literature
Project description:Traditionally health statistics are derived from civil and/or vital registration. Civil registration in low- to middle-income countries varies from partial coverage to essentially nothing at all. Consequently the state of the art for public health information in low- to middle-income countries is efforts to combine or triangulate data from different sources to produce a more complete picture across both time and space - data amalgamation. Data sources amenable to this approach include sample surveys, sample registration systems, health and demographic surveillance systems, administrative records, census records, health facility records and others. We propose a new statistical framework for gathering health and population data - Hyak - that leverages the benefits of sampling and longitudinal, prospective surveillance to create a cheap, accurate, sustainable monitoring platform. Hyak has three fundamental components: Data amalgamation: A sampling and surveillance component that organizes two or more data collection systems to work together: (1) data from HDSS with frequent, intense, linked, prospective follow-up and (2) data from sample surveys conducted in large areas surrounding the Health and Demographic Surveillance System (HDSS) sites using informed sampling so as to capture as many events as possible;Cause of death: Verbal autopsy to characterize the distribution of deaths by cause at the population level; andSocioeconomic status (SES): Measurement of SES in order to characterize poverty and wealth. We conduct a simulation study of the informed sampling component of Hyak based on the Agincourt HDSS site in South Africa. Compared with traditional cluster sampling, Hyak's informed sampling captures more deaths, and when combined with an estimation model that includes spatial smoothing, produces estimates of both mortality counts and mortality rates that have lower variance and small bias.
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Project description:MAIN OUTCOME:Thirty patients (60%) found it satisfying or very satisfying to communicate their pain with the app. Pain experienced after surgery was scored by patients as 'no': 3 (6%), 'little': 5 (10%), 'bearable': 25 (50%), 'considerable': 13 (26%) and 'severe': 1 (2%). Forty-five patients (90%) were positive about the ease of recording. Forty-five patients (90%) could correctly record their pain with the app. Thirty-eight patients (76%) agreed that in-app notifications to record pain were useful. Two patients (4%) were too ill to use the application. Based on usability feedback, we will redesign the pain intensity wheel and the in-app pain chart to improve clarity for patients to understand the course of their pain. SECONDARY OUTCOMES:The median patient recorded pain app score 4.0 (range 0 to 10) and nurse recorded numerical rating scale (NRS) for pain NRS 4.0 (range 0 to 9) were not statistically different (p = 0.06). Forty-two percent from a total of 307 patient pain app scores were ≥ 5 (on a scale from 0 no pain at all to 10 worst imaginable pain). Of these, 83% were recorded as 'bearable' while only in 18% of the recordings patients asked for additional analgesia. The results suggest that self-recording the severity of postoperative pain by patients with a smartphone application could be useful for postoperative pain management. The application was perceived as user-friendly and had high satisfaction rates from both patients and stakeholders. Further research is needed to validate the 11-point numeric and faces pain scale with the current gold standards visual analogue scale (VAS) and NRS for pain.
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Project description:Multiligament knee reconstruction surgery is technically challenging, requiring careful planning and execution. Accurate placement of bone tunnels is important for graft function and there is an inherent risk of tunnel collision, which can compromise graft integrity. In this proof-of-concept study, we present a technique using computer navigation to help optimize tunnel placement and to avoid collision during multiligament knee reconstruction. A computed tomography (CT)-based navigation system was used to plan and execute femoral tunnel placement on a Sawbones model, for a Schenck KD-IV multiligament knee reconstruction. After CT scanning of the Sawbones model, commercially available software was used to plan tunnel trajectories for reconstruction of the posterolateral corner, medial ligament complex, and both cruciate ligaments. Tunnel entry points and trajectories were based on bony landmarks as identified on CT. The model was successfully registered with an accuracy of <0.5 mm. Execution of tunnel drilling was carried out for 7 femoral tunnels, guided by computer navigation. A postprocedure CT scan was then performed and superimposed over the preoperative planning scan. This demonstrated excellent correlation between planned and executed tunnels with no evidence of tunnel collision. This study supports the idea of using computer navigation to plan and execute tunnels in multiligament knee reconstruction.
| S-EPMC11369949 | biostudies-literature
Project description:BackgroundIntegrating results from multiple samples is often desirable, but privacy restrictions may preclude full data pooling, and most datasets do not include fully harmonized variable sets. We propose a simulation-based method leveraging partial information across datasets to guide creation of synthetic data based on explicit assumptions about the underlying causal structure that permits pooled analyses that adjust for all desired confounders in the context of privacy restrictions.MethodsThis proof-of-concept project uses data from the Health and Retirement Study (HRS) and Atherosclerosis Risk in Communities (ARIC) study. We specified an estimand of interest and a directed acyclic graph (DAG) summarizing the presumed causal structure for the effect of glycated hemoglobin (HbA1c) on cognitive change. We derived publicly reportable statistics to describe the joint distribution of each variable in our DAG. These summary estimates were used as data-generating rules to create synthetic datasets. After pooling, we imputed missing covariates in the synthetic datasets and used the synthetic data to estimate the pooled effect of HbA1c on cognitive change, adjusting for all desired covariates.ResultsDistributions of covariates and model coefficients and associated standard errors for our model estimating the effect of HbA1c on cognitive change were similar across cohort-specific original and preimputation synthetic data. The estimate from the pooled synthetic incorporates control for confounders measured in either original dataset.DiscussionOur approach has advantages over meta-analysis or individual-level pooling/data harmonization when privacy concerns preclude data sharing and key confounders are not uniformly measured across datasets.
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