Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging

Model-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be segmented for proper visualisation and interpretation of perfusion maps. This research proposes Turbolift learning, which trains a modified version of the multi-scale Attention UNet on different liver segmentation tasks serially, following the order of the trainings CT, CBCT, CBCT TST - making the previous trainings act as pre-training stages for the subsequent ones - addressing the problem of limited number of datasets for training. For the final task of liver segmentation from CBCT TST, the proposed method achieved an overall Dice scores of 0.874±0.031 and 0.905±0.007 in 6-fold and 4-fold cross-validation experiments, respectively - securing statistically significant improvements over the model, which was trained only for that task. Experiments revealed that Turbolift not only improves the overall performance of the model but also makes it robust against artefacts originating from the embolisation materials and truncation artefacts. Additionally, in-depth analyses confirmed the order of the segmentation tasks. This paper shows the potential of segmenting the liver from CT, CBCT, and CBCT TST, learning from the available limited training data, which can possibly be used in the future for the visualisation and evaluation of the perfusion maps for the treatment evaluation of liver diseases.

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

BACKGROUND

CT perfusion imaging (CTP) is used in the diagnostic workup of acute ischemic stroke (AIS). CTP may be performed within the angio suite using flat detector CT (FDCT) to help reduce patient management time.

PURPOSE

In order to significantly improve FDCT perfusion (FDCTP) imaging, data-processing algorithms need to be able to compensate for the higher levels of noise, slow rotation speed, and a lower frame rate of current FDCT devices.

METHODS

We performed a realistic simulation of FDCTP acquisition based on CTP data from seven subjects. We used the time separation technique (TST) as a model-based approach for FDCTP data processing. We propose a novel dimension reduction in which we approximate the time attenuation curves by a linear combination of trigonometric functions. Our goal was to show that the TST can be used even without prior assumptions on the shape of the attenuation profiles.

RESULTS

We first demonstrated that a trigonometric basis is suitable for dimension reduction of perfusion data. Using simulated FDCTP data, we have shown that a trigonometric basis in the TST provided better results than the classical straightforward processing even with additional noise. Average correlation coefficients of perfusion maps were improved for cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT) maps. In a moderate noise scenario, the average Pearson's coefficient for the CBF map was improved using the TST from 0.76 to 0.81. For the MTT map, it was improved from 0.37 to 0.45. Furthermore, we achieved a total processing time from the reconstruction of FDCTP data to the generation of perfusion maps of under 5 min.

CONCLUSIONS

In our study cohort, perfusion maps created from FDCTP data using the TST with a trigonometric basis showed equivalent perfusion deficits to classic CT perfusion maps. It follows, that this novel FDCTP technique has potential to provide fast and accurate FDCTP imaging for AIS patients.

Hereditary Haemorrhagic Telangiectasia (HHT) Marked by ACVRL1C1120T Variant Displays Hypopigmented Naevi and Frequent Bleeding Episodes if CYP2C9 Co-Mutated: Clinical Notes & Rationale of Patient Registry

Hereditary haemorrhagic telangiectasia (HHT) exhibits considerable phenotypic heterogeneity. Therefore, precise mutation screening and evaluation of patient risk must be determined in every HHT family. We present an HHT-2 case with an initial life-threatening bleeding episode that led to identification of a relatively large HHT family. Exome sequencing of the family members determined HHT-associated ACVRL1C1120T variant resulting in Arg374Trp substitution at the Ser/Thr-kinase domain region. The affected members display typical epistaxis symptomatology from early childhood resulting in sideropoenia. In addition, the HHT patients also displayed dermatology findings such as facial teleangiectasias and trunk/limb white spots representing post-inflammatory hypopigmentation. Interestingly, co-segregating with modifying cytochrome P450 (CYP2C) variant in the HHT patients led to NSAID intolerance marked by increased frequency of bleeding episodes. No arterial-venous malformation of the visceral organs and brain or association with cancer were observed. The heterogeneity of clinical presentation and the role of other variants support the need of regular patient monitoring and development of a nation-wide patient registry.