| 1. |
- Zhang, X., et al.
(författare)
-
Human total, basal and activity energy expenditures are independent of ambient environmental temperature
- 2022
-
Ingår i: iScience. - : Elsevier Inc.. - 2589-0042. ; 25:8
-
Tidskriftsartikel (refereegranskat)abstract
- Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (−10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and Ta emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18–25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures.
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
- Lerner, Minna, et al.
(författare)
-
Clinical validation of a commercially available deep learning software for synthetic CT generation for brain
- 2021
-
Ingår i: Radiation Oncology. - : Springer Science and Business Media LLC. - 1748-717X. ; 16:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Most studies on synthetic computed tomography (sCT) generation for brain rely on in-house developed methods. They often focus on performance rather than clinical feasibility. Therefore, the aim of this work was to validate sCT images generated using a commercially available software, based on a convolutional neural network (CNN) algorithm, to enable MRI-only treatment planning for the brain in a clinical setting. Methods: This prospective study included 20 patients with brain malignancies of which 14 had areas of resected skull bone due to surgery. A Dixon magnetic resonance (MR) acquisition sequence for sCT generation was added to the clinical brain MR-protocol. The corresponding sCT images were provided by the software MRI Planner (Spectronic Medical AB, Sweden). sCT images were rigidly registered and resampled to CT for each patient. Treatment plans were optimized on CT and recalculated on sCT images for evaluation of dosimetric and geometric endpoints. Further analysis was also performed for the post-surgical cases. Clinical robustness in patient setup verification was assessed by rigidly registering cone beam CT (CBCT) to sCT and CT images, respectively. Results: All sCT images were successfully generated. Areas of bone resection due to surgery were accurately depicted. Mean absolute error of the sCT images within the body contour for all patients was 62.2 ± 4.1 HU. Average absorbed dose differences were below 0.2% for parameters evaluated for both targets and organs at risk. Mean pass rate of global gamma (1%/1 mm) for all patients was 100.0 ± 0.0% within PTV and 99.1 ± 0.6% for the full dose distribution. No clinically relevant deviations were found in the CBCT-sCT vs CBCT-CT image registrations. In addition, mean values of voxel-wise patient specific geometric distortion in the Dixon images for sCT generation were below 0.1 mm for soft tissue, and below 0.2 mm for air and bone. Conclusions: This work successfully validated a commercially available CNN-based software for sCT generation. Results were comparable for sCT and CT images in both dosimetric and geometric evaluation, for both patients with and without anatomical anomalies. Thus, MRI Planner is feasible to use for radiotherapy treatment planning of brain tumours.
|
|
| 6. |
- Lerner, Minna, et al.
(författare)
-
MRI-only based treatment with a commercial deep-learning generation method for synthetic CT of brain
- 2020
-
Ingår i: ; , s. 47-47
-
Konferensbidrag (refereegranskat)abstract
- ObjectivesTo show feasibility of synthetic computed tomography (sCT) images generated using a commerciallyavailable software, enabling MRI-only treatment planning for the brain in a clinical setting.Patients and Methods20 and 16 patients with brain malignancies, including post-surgical cases, were included for validationand treatment, respectively. Dixon MR images of the skull were exported to the MRI Planner software(Spectronic Medical AB), which utilizes convolutional neural network algorithms for sCT generation.In the validation study, sCT images were rigidly registered and resampled to CT geometry for eachpatient. Treatment plans were optimized on CT and retrospectively recalculated on sCT images forevaluation of dosimetric and geometric endpoints. Clinical robustness in patient setup verification wasassessed by rigidly registering cone beam CT (CBCT) to sCT and CT images, respectively.The treatment study was performed on sCT images, using CT solely for QA purposes.ResultsAll sCT images were successfully generated in the validation study. Mean absolute error of the sCTimages within the body contour for all patients was 62.2 ± 4.1 HU. Average absorbed dose differenceswere below 0.2%. Mean pass rate of global gamma (1%/1mm) for all patients was 100.0 ± 0.0 % withinPTV and 99.1 ± 0.6 % for the full dose distribution. No clinically relevant deviations were found in theCBCT-sCT vs CBCT-CT image registrations. Areas of bone resection due to surgery were accuratelydepicted in the sCT images. Finally, treatment success rate was 15/16. One patient was excluded due tosCT artifacts from a haemostatic substance injected during surgery.Conclusion15 patients have successfully received MRI-only RT for brain tumours using the validated commerciallyavailable sCT software. Validation showed comparable results between sCT and CT images for bothdosimetric and geometric endpoints
|
|
| 7. |
|
|
| 8. |
- Lerner, Minna, et al.
(författare)
-
Prospective Clinical Feasibility Study for MRI-Only Brain Radiotherapy
- 2022
-
Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 11
-
Tidskriftsartikel (refereegranskat)abstract
- Objectives: MRI-only radiotherapy (RT) provides a workflow to decrease the geometric uncertainty introduced by the image registration process between MRI and CT data and to streamline the RT planning. Despite the recent availability of validated synthetic CT (sCT) methods for the head region, there are no clinical implementations reported for brain tumors. Based on a preceding validation study of sCT, this study aims to investigate MRI-only brain RT through a prospective clinical feasibility study with endpoints for dosimetry and patient setup. Material and Methods: Twenty-one glioma patients were included. MRI Dixon images were used to generate sCT images using a CE-marked deep learning-based software. RT treatment plans were generated based on MRI delineated anatomical structures and sCT for absorbed dose calculations. CT scans were acquired but strictly used for sCT quality assurance (QA). Prospective QA was performed prior to MRI-only treatment approval, comparing sCT and CT image characteristics and calculated dose distributions. Additional retrospective analysis of patient positioning and dose distribution gamma evaluation was performed. Results: Twenty out of 21 patients were treated using the MRI-only workflow. A single patient was excluded due to an MRI artifact caused by a hemostatic substance injected near the target during surgery preceding radiotherapy. All other patients fulfilled the acceptance criteria. Dose deviations in target were within ±1% for all patients in the prospective analysis. Retrospective analysis yielded gamma pass rates (2%, 2 mm) above 99%. Patient positioning using CBCT images was within ± 1 mm for registrations with sCT compared to CT. Conclusion: We report a successful clinical study of MRI-only brain radiotherapy, conducted using both prospective and retrospective analysis. Synthetic CT images generated using the CE-marked deep learning-based software were clinically robust based on endpoints for dosimetry and patient positioning.
|
|
| 9. |
- Speakman, John R., et al.
(författare)
-
Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure
- 2023
-
Ingår i: Nature Metabolism. - : NATURE PORTFOLIO. - 2522-5812. ; 5:4, s. 579-588
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Obesity is caused by a prolonged positive energy balance(1,2). Whether reduced energy expenditure stemming from reduced activity levels contributes is debated(3,4). Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.
|
|
