Development and validation of a novel craniofacial statistical shape model for the virtual reconstruction of bilateral maxillary defects.

Bilateral maxillary defects are a challenge for fibula free flap reconstruction (FFFR) surgery due to limitations in virtual surgical planning (VSP) workflows. While meshes of unilateral defects can be mirrored to virtually reconstruct missing anatomy, Brown class c and d defects lack a contralateral reference and associated anatomical landmarks. This often results in poor placement of osteotomized fibula segments. This study was performed to improve the VSP workflow for FFFR using statistical shape modeling (SSM) - a form of unsupervised machine learning - to virtually reconstruct premorbid anatomy in an automated, reproducible, and patient-specific manner. A training set of 112 computed tomography scans was sourced from an imaging database by stratified random sampling. The craniofacial skeletons were segmented, aligned, and processed via principal component analysis. Reconstruction performance was validated on a set of 45 unseen skulls containing various digitally generated defects (Brown class IIa-d). Validation metrics demonstrated promising accuracy: mean 95th percentile Hausdorff distance of 5.47 ± 2.39 mm, mean volumetric Dice coefficient of 48.8 ± 14.5%, compactness of 7.28 × 105 mm2, specificity of 1.18 mm, and generality of 8.12 × 10-6 mm. SSM-guided VSP will allow surgeons to create patient-centric treatment plans, increasing FFFR accuracy, reducing complications, and improving postoperative outcomes.

Differences in the control of breathing between Himalayan and sea-level residents.

We compared the control of breathing of 12 male Himalayan highlanders with that of 21 male sea-level Caucasian lowlanders using isoxic hyperoxic ( = 150 mmHg) and hypoxic ( = 50 mmHg) Duffin's rebreathing tests. Highlanders had lower mean +/- s.e.m. ventilatory sensitivities to CO(2) than lowlanders at both isoxic tensions (hyperoxic: 2.3 +/- 0.3 vs. 4.2 +/- 0.3 l min(1) mmHg(1), P = 0.021; hypoxic: 2.8 +/- 0.3 vs. 7.1 +/- 0.6 l min(1) mmHg(1), P < 0.001), and the usual increase in ventilatory sensitivity to CO(2) induced by hypoxia in lowlanders was absent in highlanders (P = 0.361). Furthermore, the ventilatory recruitment threshold (VRT) CO(2) tensions in highlanders were lower than in lowlanders (hyperoxic: 33.8 +/- 0.9 vs. 48.9 +/- 0.7 mmHg, P < 0.001; hypoxic: 31.2 +/- 1.1 vs. 44.7 +/- 0.7 mmHg, P < 0.001). Both groups had reduced ventilatory recruitment thresholds with hypoxia (P < 0.001) and there were no differences in the sub-threshold ventilations (non-chemoreflex drives to breathe) between lowlanders and highlanders at both isoxic tensions (P = 0.982), with a trend for higher basal ventilation during hypoxia (P = 0.052). We conclude that control of breathing in Himalayan highlanders is distinctly different from that of sea-level lowlanders. Specifically, Himalayan highlanders have decreased central and absent peripheral sensitivities to CO(2). Their response to hypoxia was heterogeneous, with the majority decreasing their VRT indicating either a CO(2)-independent increase in activity of peripheral chemoreceptor or hypoxia-induced increase in [H(+)] at the central chemoreceptor. In some highlanders, the decrease in VRT was accompanied by an increase in sensitivity to CO(2), while in others VRT remained unchanged and their sub-threshold ventilations increased, although these were not statistically significant.

Precise control of end-tidal carbon dioxide levels using sequential rebreathing circuits.

Anaesthesiologists have traditionally been consulted to help design breathing circuits to attain and maintain target end-tidal carbon dioxide (P(ET)CO2). The methodology has recently been simplified by breathing circuits that sequentially deliver fresh gas (not containing carbon dioxide (CO2)) and reserve gas (containing CO2). Our aim was to determine the roles of fresh gas flow, reserve gas PCO2 and minute ventilation in the determination of P(ET)CO2. We first used a computer model of a non-rebreathing sequential breathing circuit to determine these relationships. We then tested our model by monitoring P(ET)CO2 in human volunteers who increased their minute ventilation from resting to five times resting levels. The optimal settings to maintain P(ET)CO2 independently of minute ventilation are 1) fresh gas flow equal to minute ventilation minus anatomical deadspace ventilation, and 2) reserve gas PCO2 equal to alveolar PCO2. We provide an equation to assist in identifying gas settings to attain a target PCO2. The ability to precisely attain and maintain a target PCO2 (isocapnia) using a sequential gas delivery circuit has multiple therapeutic and scientific applications.