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- Andersen, Paul Krüger, et al.
(author)
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Response to the Proposal for a Directive on Corporate Sustainability Due Diligence by Nordic and Baltic Company Law Scholars
- 2022
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Other publication (other academic/artistic)abstract
- On February 23, 2022, The EU Commission published its Proposal for a Directive of the European Parliament and of the Council on Corporate Sustainability Due Diligence and amending Directive (EU) 2019/1937 (“CSDDD” or “the Proposal”). The purpose of the Proposal, to further the “Union’s transition to a climate-neutral and green economy in line with the European Green Deal and in delivering on the UN Sustainable Development Goals”, is of great importance, and the Commission’s initiative is therefore commendable. However, it is our firm opinion that the Proposal should not be enacted in its present form, and that if it were to be, it would not only damage European businesses but also run the risk of having an adverse effect on both the transition to a climate-neutral economy as well as the goal of delivering on the UN Sustainable Development Goals. This is to a large extent because many of the Proposal’s provisions are excessive, unfounded and disproportionate and as such in violation of the fundamental principles of subsidiarity and proportionality safeguarded by Art. 5 TEU as well as having a questionable basis in Art. 50 TFEU. Furthermore and in regard of procedure, we find that the presentation of the Proposal by the Commission represents a disregard for the principles of better regulation that should not pass unnoticed and must be observed in the future to maintain trust in the legislative process of the Union.In this response to the consultation, we have presented an analysis of the key issues of the Proposal from a corporate governance perspective. We have divided the response into two parts: one on the pure corporate governance parts of the Proposal (article 15, 25 and 26) and one of the due diligence parts of the Proposal. With regards to the corporate governance parts of the Proposal, our conclusion is that they, by and large, should not be included in the proposed directive at all. Including them would in several ways be in breach of the EU principles on subsidiarity and proportionality, but perhaps more importantly, they are not only unsubstantiated by available empirical evidence on corporate behaviour, but also refuted by what we know. There is also good reason to believe that the proposed rules on director’s duties and environmental remuneration would risk decreasing the effectiveness of the stock markets within the EU contrary to the goal of a Capital Market Union, which also risk slowing down the necessary transition to a green economy and the goals of the EU Green Deal. The regulation necessary for the Capital Market Union and the EU Green Deal should complement each other, not collide as would be the outcome if the Proposal is adopted in its present form.With regards to the due diligence parts of the Proposal, our criticism is limited to corporate governance aspects and far less fundamental. We primarily believe that grounds for harmonisation needs further consideration in the present very challenging times, that Article 22 on Civil Liability might in several ways be counter-productive to the goals of the Proposal, that the effects on SMEs as well as for the financial companies included covered by the Proposal warrants further analysis, that the choice to focus the Proposal on individual companies instead of company groups needs to be reviewed, and that a risk based approach should be taken rather than an approach were companies are unable to focus their efforts to where they can be most effective. Overall, these issues can be worked out, but if they are not, then the proposed directive would not only have a severe adverse impact on EU companies and possibly capital markets, but might actually hinder EU companies from acting in the way that the Proposal aims for them to do.This joint response to the public consultation is made by a group of Nordic and Baltic company law scholars who, although we may not agree on every detail, do share the main arguments and grave concerns expressed here.
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| 2. |
- Sjöholm, Therese, et al.
(author)
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A whole-body diffusion MRI normal atlas : development, evaluation and initial use
- 2023
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In: Cancer Imaging. - : BioMed Central (BMC). - 1740-5025 .- 1470-7330. ; 23:1
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Journal article (peer-reviewed)abstract
- Background: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task.Methods: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture.Results: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision.Conclusions: Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.
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| 3. |
- Sjöholm, Therese
(author)
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Cancer imaging and image analysis methods in whole-body MRI and PET/MRI
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Diagnostic medical imaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) can provide structural and functional assessments of the whole body. This has great value for potentially systemic diseases such as cancer. To take advantage of the enormous amount of data provided by current imaging systems, improvements in whole-body imaging protocols and advancements in image analysis methods are however needed. This thesis aims to develop advanced imaging and image analysis methods for the purpose of tumour characterisation in MRI and combined PET/MRI whole-body image datasets. Early prediction of progression free survival (PFS) and overall survival (OS) in patients with relapsed/refractory (r/r) large B-cell lymphoma (LBCL) undergoing chimeric antigen receptor (CAR) T-cell therapy was assessed using whole-body PET/MRI pre- and post-therapy. Reference standard manual segmentations of tumours and non-malignant lymphoid tissue were used, and an extended set of semi-quantitative and quantitative PET/MRI metrics was extracted. Predictive PET/MRI metrics included the metabolic tumour volume (MTV), tumour apparent diffusion coefficient (ADC) and 18F-fluorodeoxyglucose (FDG) uptake in non-malignant bone marrow. To enable automated image analysis, deformable image registration was used to create multiparametric normal atlases of healthy volunteers examined with whole-body FDG PET, diffusion weighted imaging (DWI) MRI and water-fat MRI. To improve the geometric accuracy of DWI in the normal atlas, the reverse polarity gradient (RPG) distortion correction method was evaluated. RPG increased the geometrical alignment between DWI and structural images acquired in the same scan session, with little effect on healthy tissue ADC. It was further shown that healthy tissue assessments in atlas space was possible, with the normal atlas employed to study voxel-wise correlations between ADC and age across the whole body, confirming results from a manual segmentation approach. As proof of concept, a probabilistic atlas based approach was successfully used for segmentation of suspected malignant disease in FDG PET data and detection of liver fat infiltration in fat fraction (FF) MRI data. Lastly, using a cohort of r/r LBCL patients, statistical deviations between patient and normal atlas DWI data included as input in a deep learning based model, improved its performance for automated tumour segmentation.
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| 4. |
- Sjöholm, Therese, et al.
(author)
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Improved geometric accuracy of whole body diffusion-weighted imaging at 1.5T and 3T using reverse polarity gradients
- 2022
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12
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Journal article (peer-reviewed)abstract
- Whole body diffusion-weighted imaging (WB-DWI) is increasingly used in oncological applications, but suffers from misalignments due to susceptibility-induced geometric distortion. As such, DWI and structural images acquired in the same scan session are not geometrically aligned, leading to difficulties in e.g. lesion detection and segmentation. In this work we assess the performance of the reverse polarity gradient (RPG) method for correction of WB-DWI geometric distortion. Multi-station DWI and structural magnetic resonance imaging (MRI) data of healthy controls were acquired at 1.5T (n = 20) and 3T (n = 20). DWI data was distortion corrected using the RPG method based on b = 0 s/mm(2) (b0) and b = 50 s/mm(2) (b50) DWI acquisitions. Mutual information (MI) between low b-value DWI and structural data increased with distortion correction (P < 0.05), while improvements in region of interest (ROI) based similarity metrics, comparing the position of incidental findings on DWI and structural data, were location dependent. Small numerical differences between non-corrected and distortion corrected apparent diffusion coefficient (ADC) values were measured. Visually, the distortion correction improved spine alignment at station borders, but introduced registration-based artefacts mainly for the spleen and kidneys. Overall, the RPG distortion correction gave an improved geometric accuracy for WB-DWI data acquired at 1.5T and 3T. The b0- and b50-based distortion corrections had a very similar performance.
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| 6. |
- Tarai, Sambit, et al.
(author)
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Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors
- 2024
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In: Heliyon. - : Elsevier. - 2405-8440. ; 10:4
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Journal article (peer-reviewed)abstract
- Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.
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