OBJECTIVES:To validate whether cerebrospinal fluid oxyhaemoglobin (CSF-Hb), measured from external ventricular or lumbar drains, is associated with secondary brain injury (SAH-SBI) after aneurysmal subarachnoid haemorrhage (aSAH) and to assess its value as a real-time monitoring biomarker. DESIGN:Pre-registered multicentre prospective observational cohort study. SETTING:Eight neurosurgical tertiary centres in Switzerland, Germany and Austria between August 2021 and June 2024. PARTICIPANTS:366 patients with aSAH (mean age 58 years; 65% women). Of these, 260 provided cerebrospinal fluid (CSF) samples via external ventricular drain (EVD; 2467 samples, median 10 days per patient) and 66 via lumbar drain (LD; 379 samples, median 6 days). INTERVENTIONS:Daily CSF samples were collected via EVD or LD from day 1 to day 14 after haemorrhage; no therapeutic interventions were tested. MAIN OUTCOME MEASURES:CSF-Hb and its metabolites were analysed post hoc in a blinded manner. The primary outcome was SAH-SBI, defined as a composite of angiographic vasospasm (aVSP), delayed cerebral ischaemia (DCI) and delayed ischaemic neurological deficits (DIND), assessed daily over 14 days. Secondary outcomes included temporal CSF-Hb profiles and associations with aneurysm location, haematoma volume, intraventricular haemorrhage, chronic hydrocephalus and 3 month functional outcome. RESULTS:CSF-Hb showed a delayed peak pattern: concentrations were low after aSAH, rose to a maximum on day 10 (EVD-derived CSF-Hb median 11.3 µM, IQR 2.64 to 25.90) and then declined. Larger haematoma volume (p<0.001) and intraventricular haemorrhage (p<0.001) were associated with higher EVD-derived CSF-Hb. SAH-SBI occurred in 209/366 patients (57%). Daily EVD-derived CSF-Hb showed no association with SAH-SBI (p=0.25) and only poor prognostic potential for same-day SAH-SBI (area under the curve 0.59, 95% CI 0.56 to 0.63), with substantial between-centre heterogeneity. In a post-hoc exploratory analysis, higher CSF methaemoglobin showed a positive point-estimate of association with SAH-SBI (OR 1.18 per log(µM), 95% CI 1.02 to 1.36). Higher acute-phase EVD-derived CSF-Hb was associated with chronic hydrocephalus and a poor 3 month functional outcome. Catheter-related infection rates were low (2.2%). CONCLUSIONS:In this preregistered multicentre validation study, EVD-derived CSF-Hb did not perform as a robust real-time monitoring biomarker for SAH-SBI, showing limited same-day discrimination and substantial between-centre heterogeneity. These findings argue against clinical implementation of CSF-Hb point-measurement as a single-parameter biomarker. Higher CSF methaemoglobin was associated with SAH-SBI; this hypothesis-generating observation requires prospective confirmation and motivates continued investigation of haemolysis-related pathways. Future work using the HeMoVal biobank will apply multi-marker, pathway-level analyses to define haemolysis-related biomarker signatures and provide a platform for robust external validation of future candidates. TRIAL REGISTRATION NUMBER:NCT04998370.

The functional outcome of patients with intracranial hemorrhage strongly relates to the degree of secondary brain injury (SBI) evolving within days after the initial bleeding. The spatiotemporal interplay of specific inflammatory processes within different brain compartments has not been sufficiently characterized, limiting potential therapeutic interventions to prevent and treat SBI.

Secondary brain injury (SBI) occurs with a lag of several days post-bleeding in patients with aneurysmal subarachnoid hemorrhage (aSAH) and is a strong contributor to mortality and long-term morbidity. aSAH-SBI coincides with cell-free hemoglobin (Hb) release into the cerebrospinal fluid. This temporal association and convincing pathophysiological concepts suggest that CSF-Hb could be a targetable trigger of SBI. However, sparse experimental evidence for Hb’s neurotoxicity in vivo defines a significant research gap for clinical translation. We modeled the CSF-Hb exposure observed in aSAH patients in conscious sheep, which allowed us to assess neurological functions in a gyrencephalic species. Twelve animals were randomly assigned for 3-day bi-daily intracerebroventricular (ICV) injections of either Hb or Hb combined with the high-affinity Hb scavenger protein haptoglobin (Hb-Hp, CSL888). Repeated CSF sampling confirmed clinically relevant CSF-Hb concentrations. This prolonged CSF-Hb exposure over 3 days resulted in disturbed movement activity, reduced food intake, and impaired observational neuroscores. The Hb-induced neurotoxic effects were significantly attenuated when Hb was administered with equimolar haptoglobin. Preterminal magnetic resonance imaging (MRI) showed no CSF-Hb-specific structural brain alterations. In both groups, histology demonstrated an inflammatory response and revealed enhanced perivascular histiocytic infiltrates in the Hb-Hp group, indicative of adaptive mechanisms. Heme exposure in CSF and iron deposition in the brain were comparable, suggesting comparable clearance efficiency of Hb and Hb-haptoglobin complexes from the intracranial compartment. We identified a neurological phenotype of CSF-Hb toxicity in conscious sheep, which is rather due to neurovascular dysfunction than structural brain injury. Haptoglobin was effective at attenuating CSF-Hb-induced neurological deterioration, supporting its therapeutic potential.

Preclinical studies indicate that the systemic application of C1-inhibitor, clinically used to treat hereditary angioedema, reduces secondary brain injury after ischemic stroke. This study assessed the effect of C1-inhibitor on secondary brain injury after hemorrhagic stroke. We used an established striatal whole-blood injection mouse model to mimic intracerebral hemorrhage-related secondary brain injury. Based on the spatiotemporal dynamics in our model, we calculated the necessary sample size (n = 24) and determined the most sensitive time point to detect potential group differences (48 h) prior to the experiments. The experimental setup, tissue processing and image analysis adhered to our published protocol. We randomized mice into three groups: C1-inhibitor treatment, placebo, and sham. Histology was standardized by taking eight anatomically predefined slices across the entire lesion. Lesion size, vascular leakage, and inflammatory responses were assessed using automated thresholding and dextran/ICAM1/CD45 intensity mapping. Investigators were blinded to group allocation during the experiment, tissue processing, and image analysis. Whole blood injection resulted in significantly larger lesion size and more pronounced vascular leakage and cellular inflammation compared to the sham group. However, there was no difference in lesion size or inflammatory markers between the C1-inhibitor and placebo groups. In addition, there was no difference in the inflammatory response of the choroid plexus, which has been identified as a central organ orchestrating inflammation after intracerebral hemorrhage. The protective effect of C1-inhibitor might be isolated to pathophysiological processes with a predominant thromboinflammatory component, as in ischemia-reperfusion, but less so in permanent ischemia or intracerebral hemorrhage.

G-ratio is crucial for understanding the nervous system’s health and function as it measures the relative myelin thickness around an axon. However, manual measurement is biased and variable, emphasizing the need for an automated and standardized technique. Although deep learning holds promise, current implementations lack clinical relevance and generalizability. This study aimed to develop an automated pipeline for selecting nerve fibers and calculating relevant g-ratio using quality parameters in optical microscopy. Histological sections from the sciatic nerves of 16 female mice were prepared and stained with either p-phenylenediamine (PPD) or toluidine blue (TB). A custom UNet model was trained on a mix of both types of staining to segment the sections based on 7,694 manually delineated nerve fibers. Post-processing excluded non-relevant nerves. Axon diameter, myelin thickness, and g-ratio were computed from the segmentation results and its reliability was assessed using the intraclass correlation coefficient (ICC). Validation was performed on adjacent cuts of the same nerve. Then, morphometrical analyses of both staining techniques were performed. High agreement with the ground truth was shown by the model, with dice scores of 0.86 (axon) and 0.80 (myelin) and pixel-wise accuracy of 0.98 (axon) and 0.94 (myelin). Good inter-device reliability was observed with ICC at 0.87 (g-ratio) and 0.83 (myelin thickness), and an excellent ICC of 0.99 for axon diameter. Although axon diameter significantly differed from the ground truth (p = 0.006), g-ratio (p = 0.098) and myelin thickness (p = 0.877) showed no significant differences. No statistical differences in morphological parameters (g-ratio, myelin thickness, and axon diameter) were found in adjacent cuts of the same nerve (ANOVA p-values: 0.34, 0.34, and 0.39, respectively). Comparing all animals, staining techniques yielded significant differences in mean g-ratio (PPD: 0.48 ± 0.04, TB: 0.50 ± 0.04), myelin thickness (PPD: 0.83 ± 0.28 μm, TB: 0.60 ± 0.20 μm), and axon diameter (PPD: 1.80 ± 0.63 μm, TB: 1.78 ± 0.63 μm). The proposed pipeline automatically selects relevant nerve fibers for g-ratio calculation in optical microscopy. This provides a reliable measurement method and serves as a potential pre-selection approach for large datasets in the context of healthy tissue. It remains to be demonstrated whether this method is applicable to measure g-ratio related with neurological disorders by comparing healthy and pathological tissue. Additionally, our findings emphasize the need for careful interpretation of inter-staining morphological parameters.

OBJECTIVES:Cerebrospinal fluid hemoglobin has been positioned as a potential biomarker and drug target for aneurysmal subarachnoid hemorrhage-related secondary brain injury (SAH-SBI). The maximum amount of hemoglobin, which may be released into the cerebrospinal fluid, is defined by the initial subarachnoid hematoma volume (ISHV). In patients without external ventricular or lumbar drain, there remains an unmet clinical need to predict the risk for SAH-SBI. The aim of this study was to explore automated segmentation of ISHV as a potential surrogate for cerebrospinal fluid hemoglobin to predict SAH-SBI.METHODS:This study is based on a retrospective analysis of imaging and clinical data from 220 consecutive patients with aneurysmal subarachnoid hemorrhage collected over a five-year period. 127 annotated initial non-contrast CT scans were used to train and test a convolutional neural network to automatically segment the ISHV in the remaining cohort. Performance was reported in terms of Dice score and intraclass correlation. We characterized the associations between ISHV and baseline cohort characteristics, SAH-SBI, ventriculoperitoneal shunt dependence, functional outcome, and survival. Established clinical (World Federation of Neurosurgical Societies, Hunt & Hess) and radiological (modified Fisher, Barrow Neurological Institute) scores served as references.RESULTS:A strong volume agreement (0.73 Dice, range 0.43 - 0.93) and intraclass correlation (0.89, 95% CI, 0.81-0.94) were shown. While ISHV was not associated with the use of antithrombotics or cardiovascular risk factors, there was strong evidence for an association with a lower Glasgow Coma Scale at hospital admission. Aneurysm size and location were not associated with ISHV, but the presence of intracerebral or intraventricular hemorrhage were independently associated with higher ISHV. Despite strong evidence for a positive association between ISHV and SAH-SBI, the discriminatory ability of ISHV for SAH-SBI was insufficient. The discriminatory ability of ISHV was, however, higher regarding ventriculoperitoneal shunt dependence and functional outcome at three-months follow-up. Multivariate survival analysis provided strong evidence for an independent negative association between survival probability and both ISHV and intraventricular hemorrhage.CONCLUSIONS:The proposed algorithm demonstrates strong performance in volumetric segmentation of the ISHV on the admission CT. While the discriminatory ability of ISHV for SAH-SBI was similar to established clinical and radiological scores, it showed a high discriminatory ability for ventriculoperitoneal shunt dependence and functional outcome at three-months follow-up.

ABSTRACTPurposeCell-free hemoglobin in the cerebrospinal fluid (CSF-Hb) may be one of the main drivers of secondary brain injury after aneurysmal subarachnoid hemorrhage. Haptoglobin scavenging of CSF-Hb has been shown to mitigate cerebrovascular disruption. Using digital subtraction angiography (DSA) and blood oxygenation-level dependent cerebrovascular reactivity imaging (BOLD-CVR) the aim was to assess the acute toxic effect of CSF-Hb on cerebral blood flow and autoregulation, as well as to test the protective effects of haptoglobin.MethodsDSA imaging was performed in eight anesthetized and ventilated sheep (mean weight: 80.4 kg) at baseline, 15, 30, 45 and 60 minutes after infusion of hemoglobin (Hb) or co-infusion with haptoglobin (Hb:Haptoglobin) into the left lateral ventricle. Additionally, 10 ventilated sheep (mean weight: 79.8 kg) underwent BOLD-CVR imaging to assess the cerebrovascular reserve capacity.ResultsDSA imaging did not show a difference in mean transit time or cerebral blood flow. Wholebrain BOLD-CVR compared to baseline decreased more in the Hb group after 15 minutes (Hb vs Hb:Haptoglobin: −0.03 ±0.01 vs −0.01 ±0.02) and remained diminished compared to Hb:Haptoglobin group after 30 minutes (Hb vs Hb:Haptoglobin: −0.03 ±0.01 vs 0.0 ±0.01), 45 minutes (Hb vs Hb:Haptoglobin: −0.03 ±0.01 vs 0.01 ±0.02) and 60 minutes (Hb vs Hb:Haptoglobin: −0.03 ±0.02 vs 0.01 ±0.01).ConclusionIt is demonstrated that CSF-Hb toxicity leads to rapid cerebrovascular reactivity impairment, which is blunted by haptoglobin co-infusion. BOLD-CVR may therefore be further evaluated as a monitoring strategy for CSF-Hb toxicity after aSAH.

Accuracy of image-guided liver surgery is challenged by deformation of the liver during the procedure. This study aims at improving navigation accuracy by using intraoperative deep learning segmentation and nonrigid registration of hepatic vasculature from ultrasound (US) images to compensate for changes in liver position and deformation. This was a single-center prospective study of patients with liver metastases from any origin. Electromagnetic tracking was used to follow US and liver movement. A preoperative 3D model of the liver, including liver lesions, and hepatic and portal vasculature, was registered with the intraoperative organ position. Hepatic vasculature was segmented using a reduced 3D U-Net and registered to preoperative imaging after initial alignment followed by nonrigid registration. Accuracy was assessed as Euclidean distance between the tumor center imaged in the intraoperative US and the registered preoperative image. Median target registration error (TRE) after initial alignment was 11.6 mm in 25 procedures and improved to 6.9 mm after nonrigid registration (p = 0.0076). The number of TREs above 10 mm halved from 16 to 8 after nonrigid registration. In 9 cases, registration was performed twice after failure of the first attempt. The first registration cycle was completed in median 11 min (8:00–18:45 min) and a second in 5 min (2:30–10:20 min). This novel registration workflow using automatic vascular detection and nonrigid registration allows to accurately localize liver lesions. Further automation in the workflow is required in initial alignment and classification accuracy.

Despite extensive preoperative imaging, intraoperative localization of liver lesions after systemic treatment can be challenging. Therefore, an image-guided navigation setup is explored that links preoperative diagnostic scans and 3D models to intraoperative ultrasound (US), enabling overlay of detailed diagnostic images on intraoperative US. Aim of this study is to assess the workflow and accuracy of such a navigation system which compensates for liver motion. Electromagnetic (EM) tracking was used for organ tracking and movement of the transducer. After laparotomy, a sensor was attached to the liver surface while the EM-tracked US transducer enabled image acquisition and landmark digitization. Landmarks surrounding the lesion were selected during patient-specific preoperative 3D planning and identified for registration during surgery. Endpoints were accuracy and additional times of the investigative steps. Accuracy was computed at the center of the target lesion. In total, 22 navigated procedures were performed. Navigation provided useful visualization of preoperative 3D models and their overlay on US imaging. Landmark-based registration resulted in a mean fiducial registration error of 10.3 ± 4.3 mm, and a mean target registration error of 8.5 ± 4.2 mm. Navigation was available after an average of 12.7 min. We developed a navigation method combining ultrasound with active liver tracking for organ motion compensation, with an accuracy below 10 mm. Fixation of the liver sensor near the target lesion compensates for local movement and contributes to improved reliability during navigation. This represents an important step forward in providing surgical navigation throughout the procedure. Trial Registration: This study is registered in the Netherlands Trial Register (number NL7951).

Introduction: Intraoperative ultrasound (US) localization of lesions after neoadjuvant chemotherapy is challenging because their size may decrease beyond the ultrasound resolution. To improve their localization, we introduce an ultrasound-based electromagnetic (EM) navigation system which maps the preoperative image with the intraoperative ultrasound, thus highlighting their location. Methods: Based on MRI or CT, a 3D model of the liver, lesions, hepatic and portal vein was generated and matched with the intraoperative organ position either by 1) identifying common landmarks between the pre- and intraoperative image or 2) automatically using deformable modeling of hepatic and portal vasculature extracted from 3DUS using deep learning. Accuracy was assessed as Euclidean distance between the lesion imaged in the preoperative image and the one identified in intraoperative 3DUS. Results: From March 2019 to May 2021, 45 navigated procedures were safely performed. Navigation provided additional localization features by overlaying preoperative 3D models of liver lesions, vasculature and biliary anatomy onto the intraoperative ultrasound. Accuracy, calculated in 36 patients, was 8.5 ± 4.2 mm for the landmark method (n=20), and 5.7 ± 3.6 mm for automatic generation of the vasculature (n=16) (p=0.043). Surgical navigation was available on average after 13.4 minutes. Conclusion: The proposed navigation system allows to accurately localize liver lesions and is improved by automatic vasculature detection in the US image and compensation of respiratory motion and liver manipulation.

In recent years, insect husbandry has seen an increased interest in order to supply in the production of raw materials, food, or as biological/environmental control. Unfortunately, large insect rearings are susceptible to pathogens, pests and parasitoids which can spread rapidly due to the confined nature of a rearing system. Thus, it is of interest to monitor the spread of such manifestations and the overall population size quickly and efficiently. Medical imaging techniques could be used for this purpose, as large volumes can be scanned non-invasively. Due to its 3D acquisition nature, computed tomography seems to be the most suitable for this task. This study presents an automated, computed tomography-based, counting method for bee rearings that performs comparable to identifying all Osmia cornuta cocoons manually. The proposed methodology achieves this in an average of 10 seconds per sample, compared to 90 minutes per sample for the manual count over a total of 12 samples collected around lake Zurich in 2020. Such an automated bee population evaluation tool is efficient and valuable in combating environmental influences on bee, and potentially other insect, rearings.

BACKGROUND:Recent investigations suggested that pediatric posttraumatic stress disorder (PTSD) is associated with adverse brain development. However, sex differences are poorly understood.METHODS:In this study, 61 medically healthy children and adolescents (31 males and 30 females) with chronic PTSD secondary to abuse, who had similar trauma and mental health histories, and 122 healthy controls (62 males and 60 females) underwent comprehensive psychiatric assessments and an anatomical MRI brain scan.RESULTS:When gender groups were analyzed separately, findings of larger prefrontal lobe CSF volumes and smaller midsagittal area of the corpus callosum subregion 7 (splenium) were seen in both boys and girls with maltreatment-related PTSD compared to their gender-matched comparison subjects. Subjects with PTSD did not show the normal age related increases in the area of the total corpus callosum and its region 7 (splenium) compared to non-maltreated subjects; however, this finding was more prominent in males with PTSD. Significant sex by group effects demonstrated smaller cerebral volumes and corpus callosum regions 1 (rostrum) and 6 (isthmus) in PTSD males and greater lateral ventricular volume increases in maltreated males with PTSD than maltreated females with PTSD.CONCLUSIONS:These data suggest that there are sex differences in the brain maturation of boys and girls with maltreatment-related PTSD. Longitudinal MRI brain investigations of childhood PTSD and the relationship of gender to psychosocial outcomes are warranted.

Abstract Background The functional neurological outcome of patients with intracerebral hemorrhage (ICH) strongly relates to the degree of secondary brain injury (ICH-SBI) evolving within days after the initial bleeding. Different mechanisms including the incitement of inflammatory pathways, dysfunction of the blood–brain barrier (BBB), activation of resident microglia, and an influx of blood-borne immune cells, have been hypothesized to contribute to ICH-SBI. Yet, the spatiotemporal interplay of specific inflammatory processes within different brain compartments has not been sufficiently characterized, limiting potential therapeutic interventions to prevent and treat ICH-SBI. Methods We used a whole-blood injection model in mice, to systematically characterized the spatial and temporal dynamics of inflammatory processes after ICH using 7-Tesla magnetic resonance imaging (MRI), spatial RNA sequencing (spRNAseq), functional BBB assessment, and immunofluorescence average-intensity-mapping. Results We identified a pronounced early response of the choroid plexus (CP) peaking at 12–24 h that was characterized by inflammatory cytokine expression, epithelial and endothelial expression of leukocyte adhesion molecules, and the accumulation of leukocytes. In contrast, we observed a delayed secondary reaction pattern at the injection site (striatum) peaking at 96 h, defined by gene expression corresponding to perilesional leukocyte infiltration and correlating to the delayed signal alteration seen on MRI. Pathway analysis revealed a dependence of the early inflammatory reaction in the CP on toll-like receptor 4 (TLR4) signaling via myeloid differentiation factor 88 (MyD88). TLR4 and MyD88 knockout mice corroborated this observation, lacking the early upregulation of adhesion molecules and leukocyte infiltration within the CP 24 h after whole-blood injection. Conclusions We report a biphasic brain reaction pattern after ICH with a MyD88-TLR4-dependent early inflammatory response of the CP, preceding inflammation, edema and leukocyte infiltration at the lesion site. Pharmacological targeting of the early CP activation might harbor the potential to modulate the development of ICH-SBI.

Secondary brain injury after aneurysmal subarachnoid hemorrhage (SAH-SBI) contributes to poor outcomes in patients after rupture of an intracranial aneurysm. The lack of diagnostic biomarkers and novel drug targets represent an unmet need. The aim of this study was to investigate the clinical and pathophysiological association between cerebrospinal fluid hemoglobin (CSF-Hb) and SAH-SBI. In a cohort of 47 patients, we collected daily CSF-samples within 14 days after aneurysm rupture. There was very strong evidence for a positive association between spectrophotometrically determined CSF-Hb and SAH-SBI. The accuracy of CSF-Hb to monitor for SAH-SBI markedly exceeded that of established methods (AUC: 0.89 [0.85-0.92]). Temporal proteome analysis revealed erythrolysis accompanied by an adaptive macrophage response as the two dominant biological processes in the CSF-space after aneurysm rupture. Ex-vivo experiments on the vasoconstrictive and oxidative potential of Hb revealed critical inflection points overlapping CSF-Hb thresholds in patients with SAH-SBI. Selective depletion and in-solution neutralization by haptoglobin or hemopexin efficiently attenuated the vasoconstrictive and lipid peroxidation activities of CSF-Hb. Collectively, the clinical association between high CSF-Hb levels and SAH-SBI, the underlying pathophysiological rationale, and the favorable effects of haptoglobin and hemopexin in ex-vivo experiments position CSF-Hb as a highly attractive biomarker and potential drug target.

Purpose Registration of pre- and intraoperative images is a crucial step of surgical liver navigation, where rigid registration of vessel centerlines is currently commonly used. When using 3D ultrasound (US), accuracy during navigation might be influenced by the size of the intraoperative US volume, yet the relationship between registration accuracy and US volume size is understudied. In this study, we specify an optimal 3D US volume size for registration using varying volumes of liver vasculature. While previous studies measured accuracy at registered fiducials, in this work, accuracy is determined at the target lesion which is clinically the most relevant structure. Methods Three-dimensional US volumes were acquired in 14 patients after laparotomy and liver mobilization. Manual segmentation of vasculature and centerline extraction was performed. Intraoperative and preoperative vasculature centerlines were registered with coherent point drift, using different sub-volumes (sphere with radius r = 30, 40, horizontal ellipsis , 120 mm). Accuracy was measured by fiducial registration error (FRE) between vessel centerlines and target registration error (TRE) at the center of the target lesion. Results The lowest FRE for vessel registration was reached with r = 50 mm (6.5 +/- 2.5 mm), the highest with r = 120 mm (7.1 +/- 2.1 mm). Clinical accuracy at the target lesion, resulted most accurate (TRE = 8.8 +/- 5.0 mm) in sub-volumes with a radius of 50 mm. Smaller US sub-volumes resulted in lower average TREs when compared to larger US sub-volumes (Pearson's correlation coefficient R = 0.91, p < 0.001). Conclusion Our results indicate that there is a linear correlation between US volume size and registration accuracy at the tumor. Volumes with radii of 50 mm around the target lesion yield higher accuracy (p < 0.05) (Trial number IRBd18032, 11 September 2018).

Accurate hepatic vessel segmentation and registration using ultrasound (US) can contribute to beneficial navigation during hepatic surgery. However, it is challenging due to noise and speckle in US imaging and liver deformation. Therefore, a workflow is developed using a reduced 3D U-Net for segmentation, followed by non-rigid coherent point drift (CPD) registration. By means of electromagnetically tracked US, 61 3D volumes were acquired during surgery. Dice scores of 0.77, 0.65 and 0.66 were achieved for segmentation of all vasculature, hepatic vein and portal vein respectively. This compares to inter-observer variabilities of 0.85, 0.88 and 0.74 respectively. Target registration error at a tumor lesion of interest was lower (7.1 mm) when registration is performed either on the hepatic or the portal vein, compared to using all vasculature (8.9 mm). Using clinical data, we developed a workflow consisting of multi-class segmentation combined with selective non-rigid registration that leads to sufficient accuracy for integration in computer assisted liver surgery.

Dual-energy CT (DECT) was introduced to address the inability of conventional single-energy computed tomography (SECT) to distinguish materials with similar absorbances but different elemental compositions. However, material decomposition algorithms based purely on the physics of the underlying attenuation process have several limitations, leading to low signal-to-noise ratio (SNR) in the derived material-specific images. To overcome these, we trained a convolutional neural network (CNN) to develop a framework to reconstruct non-contrast SECT images from DECT scans. We show that the traditional physics-based decomposition algorithms do not bring to bear the full information content of the image data. A CNN that leverages the underlying physics of the DECT image generation process as well as the anatomic information gleaned via training with actual images can generate higher fidelity processed DECT images.

Accurate hepatic vessel segmentation on ultrasound (US) images can be an important tool in the planning and execution of surgery, however proves to be a challenging task due to noise and speckle. Our method comprises a reduced filter 3D U-Net implementation to automatically detect hepatic vasculature in 3D US volumes. A comparison is made between volumes acquired with a 3D probe and stacked 2D US images based on electromagnetic tracking. Experiments are conducted on 67 scans, where 45 are used in training, 12 in validation and 10 in testing. This network architecture yields Dice scores of 0.740 and 0.781 for 3D and stacked 2D volumes respectively, comparing promising to literature and inter-observer performance (Dice = 0.879).