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- Fournier, Laure, et al.
(författare)
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Incorporating radiomics into clinical trials : expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers
- 2021
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Ingår i: European Radiology. - : SPRINGER. - 0938-7994 .- 1432-1084. ; 31:8, s. 6001-6012
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Tidskriftsartikel (refereegranskat)abstract
- Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials.
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| 5. |
- Lidell, Martin, 1970, et al.
(författare)
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Evidence for two types of brown adipose tissue in humans
- 2013
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 19:5, s. 631-634
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Tidskriftsartikel (refereegranskat)abstract
- The previously observed supraclavicular depot of brown adipose tissue (BAT) in adult humans was
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| 6. |
- Lindmark, Daniel, 1960-, et al.
(författare)
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Rituella rum och heliga platser : en inledning
- 2020
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Ingår i: Rituella rum och heliga platser. - Skellefteå : Artos & Norma bokförlag. - 9789177771517 ; , s. 7-16
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Lundin (Palmerius), Karljohan, 1977-, et al.
(författare)
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Enabling design and interactive selection of haptic modes
- 2007
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Ingår i: Virtual Reality. - : Springer Science and Business Media LLC. - 1359-4338 .- 1434-9957.
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Tidskriftsartikel (refereegranskat)abstract
- The ever increasing size and complexity of volumetric data in a wide range of disciplines makes it useful to augment volume visualization tools with alternative modalities. Studies have shown that introducing haptics can significantly increase both exploration speed and precision. It is also capable of conveying material properties of data and thus has great potential to improve user performance in volume data exploration. In this paper we describe how recent advances in volume haptics can be used to build haptic modes-building blocks for haptic schemes. These modes have been used as base components of a toolkit allowing for more efficient development of haptic prototypes and applications. This toolkit allows interactive construction, configuration and fine-tuning of both visual and haptic representations of the data. The technology is also used in a pilot study to determine the most important issues and aspects in haptic volume data interaction and exploration, and how the use of haptic modes can facilitate the implementation of effective haptic schemes.
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| 9. |
- Tesche, Christian, et al.
(författare)
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Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR Results From MACHINE Registry
- 2020
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Ingår i: JACC Cardiovascular Imaging. - : ELSEVIER SCIENCE INC. - 1936-878X .- 1876-7591. ; 13:3, s. 760-770
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVESThis study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR).BACKGROUNDCT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated.METHODSA total of 482 vessels from 314 patients (age 62.3 +/- 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and >=$400) on a per-vessel level with invasive FFR as the reference standard.RESULTSThe diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC >= 400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC >= 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001).CONCLUSIONSMachine-learning-based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621). (C) 2020 by the American College of Cardiology Foundation.
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| 10. |
- Ynnerman, Anders, 1963-, et al.
(författare)
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Multi-Touch Surfaces and Patient-Specific Data
- 2021. - 1
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Ingår i: Digital Anatomy. - Cham : Springer. - 9783030619046 ; , s. 223-242
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Bokkapitel (refereegranskat)abstract
- While the usefulness of 3D visualizations has been shown for a range of clinical applications such as treatment planning it still had difficulties in being adopted in widespread clinical practice. This chapter describes how multi-touch surfaces with patient-specific data have contributed to breaking this barrier, paving the way for adoption into clinical practice and, at the same time, also found widespread use in educational settings and in communication of science to the general public. The key element identified for this adoption is the string of steps found in the full imaging chain, which will be described as an introduction to the topic in this chapter. Emphasis in the chapter is, however, visualization aspects, e.g., intuitive interaction with patient-specific data captured with the latest high speed and high-quality imaging modalities. A necessary starting point for this discussion is the foundations of and state-of-the-art in volumetric rendering, which form the basis for the underlying theory part of the chapter. The chapter presents two use cases. One case is focusing on the use of multi-touch in medical education and the other is focusing on the use of touch surfaces at public venues, such as science centers and museums.
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