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Highlights • Target respiratory-motion over the entire course of treatment can be captured by MRI. • The study compares the accuracy of 4DCT to 30s MR for pretreatment motion estimation. • Both techniques are reliable for lesions moving with amplitudes below 0.7 cm. Abstract Introduction Aim of this study was to investigate the ability of pre-treatment four dimensional computed tomography (4DCT) to capture respiratory-motion observed in thoracic and abdominal lesions during treatment. Treatment motion was acquired using full-treatment cine-MR acquisitions. Results of this analysis were compared to the ability of 30 seconds (s) cine Magnetic Resonance (MR) to estimate the same parameters. Methods A 4DCT and 30 s cine-MR (ViewRay, USA) were acquired on the simulation day for 7 thoracic and 13 abdominal lesions. Mean amplitude, intra- and inter-fraction amplitude variability, and baseline drift were extracted from the full treatment data acquired by 2D cine-MR, and correlated to the motion on pre-treatment 30 s cine-MR and 4DCT. Using the full treatment data, safety margins on the ITV, necessary to account for all motion variability from 4DCT observed during treatment, were calculated. Mean treatment amplitudes were 2 ± 1 mm and 5 ± 3 mm in the anteroposterior (AP) and craniocaudal (CC) direction, respectively. Differences between mean amplitude during treatment and amplitude on 4DCT or during 30 s cine-MR were not significant, but 30 s cine-MR was more accurate than 4DCT. Intra-fraction amplitude variability was positively correlated with both 30 s cine-MR and 4DCT amplitude. Inter-fraction amplitude variability was minimal. Results Mean baseline drift over all fractions and patients equalled 1 ± 1 mm in both CC and AP direction, but drifts per fraction up to 16 mm (CC) and 12 mm (AP) were observed. Margins necessary on the ITV ranged from 0 to 8 mm in CC and 0 to 5 mm in AP direction. Neither amplitude on 4DCT nor during 30 s cine MR is correlated to the magnitude of drift or the necessary margins in both directions. Conclusion Lesions moving with small amplitude show limited amplitude variability throughout treatment, making passive motion management strategies seem adequate. However, other variations such as baseline drifts and shifts still cause significant geometrical uncertainty, favouring real-time monitoring and an active approach for all lesions influenced by respiratory motion. [ABSTRACT FROM AUTHOR]

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information. [ABSTRACT FROM AUTHOR]

• Development of an automated method for lesion detection and segmentation. • An interpretable method to facilitate interaction with the medical doctor. • Image analysis of whole-body 18F-FDG PET/CT. • Automated localization of liver volume of interest. • False positive reduction by a convolutional neural network. Background and objective: In oncology, 18-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) / computed tomography (CT) is widely used to identify and analyse metabolically-active tumours. The combination of the high sensitivity and specificity from 18 F-FDG PET and the high resolution from CT makes accurate assessment of disease status and treatment response possible. Since cancer is a systemic disease, whole-body imaging is of high interest. Moreover, whole-body metabolic tumour burden is emerging as a promising new biomarker predicting outcome for innovative immunotherapy in different tumour types. However, this comes with certain challenges such as the large amount of data for manual reading, different appearance of lesions across the body and cumbersome reporting, hampering its use in clinical routine. Automation of the reading can facilitate the process, maximise the information retrieved from the images and support clinicians in making treatment decisions. Methods: This work proposes a fully automated system for lesion detection and segmentation on whole-body 18 F-FDG PET/CT. The novelty of the method stems from the fact that the same two-step approach used when manually reading the images was adopted, consisting of an intensity-based thresholding on PET followed by a classification that specifies which regions represent normal physiological uptake and which are malignant tissue. The dataset contained 69 patients treated for malignant melanoma. Baseline and follow-up scans together offered 267 images for training and testing. Results: On an unseen dataset of 53 PET/CT images, a median F1-score of 0.7500 was achieved with, on average, 1.566 false positive lesions per scan. Metabolically-active tumours were segmented with a median dice score of 0.8493 and absolute volume difference of 0.2986 ml. Conclusions: The proposed fully automated method for the segmentation and detection of metabolically-active lesions on whole-body 18 F-FDG PET/CT achieved competitive results. Moreover, it was compared to a direct segmentation approach which it outperformed for all metrics. [ABSTRACT FROM AUTHOR]

Poster: Physics track: Imaging acquisition and processing PO-1732: Feasibility of virtual dual-energy imaging through deep learning for markerless tumour tracking S. Amador Sánchez, J. Dhont, J. De Mey, M. Malbrain, J. Vandemeulebroucke. [Extracted from the article]

Cytochrome P450cam (CYP101Fe 3+ ) regioselectively hydroxylates camphor. Possible hydroxylating intermediates in the catalytic cycle of this well-characterized enzyme have been proposed on the basis of experiments carried out at very low temperatures and shunt reactions, but their presence has not yet been validated at temperatures above 0 °C during a normal catalytic cycle. Here, we demonstrate that it is possible to mimic the natural catalytic cycle of CYP101Fe 3+ by using pulse radiolysis to rapidly supply the second electron of the catalytic cycle to camphor-bound CYP101[FeO 2 ] 2+ Judging by the appearance of an absorbance maximum at 440 nm, we conclude that CYP101[FeOOH] 2+ (compound 0) accumulates within 5 μs and decays rapidly to CYP101Fe 3+ , with a k 440 nm of 9.6 × 10 4 s -1 All processes are complete within 40 μs at 4 °C. Importantly, no transient absorbance bands could be assigned to CYP101[FeO 2+ por •+ ] (compound 1) or CYP101[FeO 2+ ] (compound 2). However, indirect evidence for the involvement of compound 1 was obtained from the kinetics of formation and decay of a tyrosyl radical. 5-Hydroxycamphor was formed quantitatively, and the catalytic activity of the enzyme was not impaired by exposure to radiation during the pulse radiolysis experiment. The rapid decay of compound 0 enabled calculation of the limits for the Gibbs activation energies for the conversions of compound 0 → compound 1 → compound 2 → CYP101Fe 3+ , yielding a Δ G ‡ of 45, 39, and 39 kJ/mol, respectively. At 37 °C, the steps from compound 0 to the iron(III) state would take only 4 μs. Our kinetics studies at 4 °C complement the canonical mechanism by adding the dimension of time., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)