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Quantitative susceptibility mapping (QSM) is an MRI post-processing technique that produces spatially resolved magnetic susceptibility maps from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but accumulates errors. This study aims to overcome existing limitations by developing a Laplacian-of-Trigonometric-functions (LoT) enhanced deep neural network for near-instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MRI phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the proposed neural networks. The proposed iQFM and iQSM methods in healthy subjects yielded comparable results to those involving the intermediate steps while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. High susceptibility contrast between multiple sclerosis lesions and healthy tissue was also achieved using the proposed methods. Comparative studies indicated that the most significant contributor to iQFM and iQSM over conventional multi-step methods was the elimination of traditional Laplacian unwrapping. The reconstruction time on the order of minutes for traditional approaches was shortened to around 0.1 s using the trained iQFM and iQSM neural networks. [Display omitted]

Low-passage, serum-free cell lines cultured from patient tumour tissue are the gold-standard for preclinical studies and cellular investigations of glioblastoma (GBM) biology, yet entrenched, poorly-representative cell line models are still widely used, compromising the significance of much GBM research. We submit that greater adoption of these critical resources will be promoted by the provision of a suitably-sized, meaningfully-described reference collection along with appropriate tools for working with them. Consequently, we present a curated panel of 12 readily-usable, genetically-diverse, tumourigenic, patient-derived, low-passage, serum-free cell lines representing the spectrum of molecular subtypes of IDH-wildtype GBM along with their detailed phenotypic characterisation plus a bespoke set of lentiviral plasmids for bioluminescent/fluorescent labelling, gene expression and CRISPR/Cas9-mediated gene inactivation. The cell lines and all accompanying data are readily-accessible via a single website, Q-Cell (qimrberghofer.edu.au/q-cell/) and all plasmids are available from Addgene. These resources should prove valuable to investigators seeking readily-usable, well-characterised, clinically-relevant, gold-standard models of GBM.

Computational fluid dynamics (CFD) simulations are increasingly utilised to evaluate intracranial aneurysm (IA) haemodynamics to aid in the prediction of morphological changes and rupture risk. However, these models vary and differences in published results warrant the investigation of IA-CFD reproducibility. This study aims to explore sources of intra-team variability and determine its impact on the aneurysm morphology and CFD parameters. A team of four operators were given six sets of magnetic resonance angiography data spanning a decade from one patient with a middle cerebral aneurysm. All operators were given the same protocol and software for model reconstruction and numerical analysis. The morphology and haemodynamics of the operator models were then compared. The segmentation, smoothing factor, inlet and outflow branch lengths were found to cause intra-team variability. There was 80% reproducibility in the time-averaged wall shear stress distribution among operators with the major difference attributed to the level of smoothing. Based on these findings, it was concluded that the clinical applicability of CFD simulations may be feasible if a standardised segmentation protocol is developed. Moreover, when analysing the aneurysm shape change over a decade, it was noted that the co-existence of positive and negative values of the wall shear stress divergence (WSSD) contributed to the growth of a daughter sac.

Abstract BACKGROUND: The management of unruptured aneurysms is controversial, with the decision to treat influenced by aneurysm characteristics including size and morphology. Aneurysmal bleb formation is thought to be associated with an increased risk of rupture. OBJECTIVE: To correlate computational fluid dynamic (CFD) indices with bleb formation. METHODS: Anatomic models were constructed from 3-dimensional rotational angiography data in 27 patients with cerebral aneurysms harboring a single bleb. Additional models representing the aneurysm before bleb formation were constructed by digitally removing the bleb. We characterized hemodynamic features of models both with and without the blebs using CFDs. Flow structure, wall shear stress (WSS), pressure, and oscillatory shear index (OSI) were analyzed. RESULTS: There was a statistically significant association between bleb location at or adjacent to the point of maximal WSS (74%, P = .019), irrespective of rupture status. Aneurysmal blebs were related to the inflow or outflow jet in 89% of cases (P < .001), whereas 11% were unrelated. Maximal wall pressure and OSI were not significantly related to bleb location. The bleb region attained a lower WSS after its formation in 96% of cases (P < .001) and was also lower than the average aneurysm WSS in 86% of cases (P < .001). CONCLUSION: Cerebral aneurysm blebs generally form at or adjacent to the point of maximal WSS and are aligned with major flow structures. Wall pressure and OSI do not contribute to determining bleb location. The measurement of WSS using CFD models may potentially predict bleb formation and thus improve the assessment of rupture risk in unruptured aneurysms.

Intracranial aneurysms (IAs) are present in 2–6% of the global population and can be catastrophic upon rupture with a mortality rate of 30–50%. IAs are commonly detected through time-of-flight magnetic resonance angiography (TOF-MRA), however, this data is rarely available for research and training purposes. The provision of imaging resources such as TOF-MRA images is imperative to develop new strategies for IA detection, rupture prediction, and surgical training. To support efforts in addressing data availability bottlenecks, we provide an open-access TOF-MRA dataset comprising 63 patients, of which 24 underwent interval surveillance imaging by TOF-MRA. Patient scans were evaluated by a neuroradiologist, providing aneurysm and vessel segmentations, clinical annotations, 3D models, in addition to 3D Slicer software environments containing all this data for each patient. This dataset is the first to provide interval surveillance imaging for supporting the understanding of IA growth and stability. This dataset will support computational and experimental research into IA dynamics and assist surgical and radiology training in IA treatment.

BackgroundIntracranial perianeurysmal cysts are a rare finding associated with cerebral aneurysms. Patients may present with symptoms secondary to mass effect from perianeurysmal cysts requiring drainage. These lesions can masquerade as neoplasms if dedicated vascular imaging is not performed, leading to misdiagnosis.MethodA retrospective search of our database was done for intracranial aneurysms that have been treated between 1998 and 2020. A literature search was then performed on PubMed and Google Scholar with the search terms ‘aneurysm’, ‘intracranial/intracerebral’, ‘cyst’, and ‘perianeurysmal cyst’. Patient demographics, aneurysms and cysts characteristics were then summarized as a table and in the discussion.ResultsThree cases where intracranial aneurysm had associated perianeurysmal cysts were found in our database. Combined with the available literature a total of 19 cases of perianeurysmal cysts have thus far been reported since this entity was first described in 2002. A significant number of perianeurysmal cysts (5/19) required intervention. In 5/19 cases the patient presented with a perianeurysmal cyst without a history of subarachnoid hemorrhage. Of the 10 cases where aneurysm follow-up was reported there were 5 cases where there was aneurysm recurrence necessitating re-treatment.ConclusionSignificant variability exists in the patient demographics, aneurysm and cyst characteristics of perianeurysmal cysts. This suggests that there is no single unified etiology and pathogenesis. These lesions are a rare finding and at present do not appear to carry diagnostic or prognostic significance. Management of perianeurysmal cysts is case-dependent and intervention should be considered when treating the related aneurysm, especially in patients with secondary symptoms.

This thesis examines the development of media consumer information labels, challenging the commonly held conception of censorship as a purely restrictive force. Media ratings and labels are often viewed as “soft censorship,” though in analyzing the transition from approval- based codes, such as the Comics Code, to disapproval-based codes, such as the Parental Advisory Label for music, strategic political and industry incentives are revealed beyond content restriction or elimination. I argue that media-labeling moral panics have instead served primarily as a political campaign tool to build emotionally engaging child protection platforms that reframe complex systemic issues as easily solvable problems, while providing major industry players an opportunity to write codes to the disadvantage of smaller independent competitors.

BackgroundRecovery following traumatic brain injury (TBI) is highly heterogeneous. Characterising longitudinal functional trajectories may enable more individualised care and inform the trial design. This study aimed to identify distinct patterns of functional recovery in the first 12 months post-injury using the Glasgow Outcome Scale – Extended (GOSE).MethodsPatients with available GOSE data from Transforming Research and Clinical Knowledge in Traumatic Brain Injury, a prospective, multicentre study, were included. A two-stage multiple imputation procedure addressed missingness, and trajectories were modelled using polytomous variable latent class analysis (poLCA) in both complete-case and imputed datasets.ResultsAmong the 2,100 participants with TBI, poLCA identified seven distinct recovery trajectories based on GOSE scores. These included (1) death (6.2%), (2) persistent GOSE 2–5 (5.7%), (3) improvement from GOSE 3–5 to GOSE 5 by 3 months with no further gains (9.0%), (4) rapid improvement from GOSE 3–5 to GOSE 7–8 sustained through follow-up (7.0%), (5) gradual improvement from GOSE 3–6 to GOSE 5–7 over 6 months (15.3%), (6) rapid early improvement from GOSE 4–7 to GOSE 6–8 by 3 months and then plateauing (21.8%) and (7) progression from GOSE 5–8 to GOSE 7–8 within 3 months, with stable outcomes thereafter (25.1%). Recovery class membership was significantly associated with the initial Glasgow Coma Scale scores, CT severity (Marshall and Rotterdam scores) and presence of psychiatric comorbidities.ConclusionsOur findings support a shift towards trajectory-based stratification in clinical care and research. Incorporating these patterns into prognostic modelling may improve outcome prediction, personalise rehabilitation and refine eligibility criteria for interventional trials.

Recent studies have suggested that irregular pulsation of intracranial aneurysm during the cardiac cycle may be potentially associated with aneurysm rupture risk. However, there is a lack of quantification method for irregular pulsations. This study aims to quantify irregular pulsations by the displacement and strain distribution of the intracranial aneurysm surface during the cardiac cycle using four-dimensional CT angiographic image data. Four-dimensional CT angiography was performed in 8 patients. The image data of a cardiac cycle was divided into approximately 20 phases, and irregular pulsations were detected in four intracranial aneurysms by visual observation, and then the displacement and strain of the intracranial aneurysm was quantified using coherent point drift and finite element method. The displacement and strain were compared between aneurysms with irregular and normal pulsations in two different ways (total and stepwise). The stepwise first principal strain was significantly higher in aneurysms with irregular than normal pulsations (0.20±0.01 vs 0.16±0.02, p=0.033). It was found that the irregular pulsations in intracranial aneurysms usually occur during the consecutive ascending or descending phase of volume changes during the cardiac cycle. In addition, no statistically significant difference was found in the aneurysm volume changes over the cardiac cycle between the two groups. Our method can successfully quantify the displacement and strain changes in the intracranial aneurysm during the cardiac cycle, which may be proven to be a useful tool to quantify intracranial aneurysm deformability and aid in aneurysm rupture risk assessment.

Background Identifying haemodynamic factors associated with thin-walled regions (TWRs) of intracranial aneurysms is critical for improving pre-surgical rupture risk assessment. Intraoperatively, these regions are visually distinguished by a red, translucent appearance and are considered highly rupture prone. However, current imaging modalities lack the resolution to detect such vulnerable areas preoperatively. This study aimed to determine whether thin-walled regions exhibit distinct local haemodynamic profiles compared to adjacent normal-appearing wall regions. Methods Sixteen patient-specific models of unruptured middle cerebral artery aneurysms were reconstructed from digital subtraction angiography images. Intraoperative TWRs were identified using a colour segmentation method based on Delta E metrics. Computational fluid dynamics (CFD) simulations were used to compute six haemodynamic parameters: wall shear stress (WSS), time-averaged WSS (TaWSS), oscillatory shear index (OSI), relative residence time (RRT), WSS divergence (WSSD), and pressure. Haemodynamic data were extracted from spatially localised surface patches within confirmed thin and normal regions. Linear mixed-effects models were applied to compare parameters while accounting for patient-level and intra-patient variability, using normalised values to improve model fit. Results Thin regions exhibited significantly higher WSS, TaWSS, WSSD, and pressure, and reduced RRT. WSS and TaWSS were approximately 3.3% and 2.8% higher in TWRs, respectively. WSSD was 5.4% higher and RRT was 0.3% lower, suggesting faster, more divergent flow in thin regions. Pressure was modestly but significantly elevated at + 1.3%. No significant difference was observed in OSI between regions. Conclusions Thin-walled regions in intracranial aneurysms demonstrate a distinctive haemodynamic profile characterised by stronger, sustained shear forces, greater shear divergence, and reduced residence time, suggesting a dynamic mechanical environment that promotes focal wall thinning. Our findings suggest that persistent shear-driven stress, rather than oscillatory flow, is a key haemodynamic feature of thin-walled regions and may contribute to localised aneurysm wall vulnerability.