| 1. |
- Abtahi, Jahan, et al.
(författare)
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Bisphosphonate coating might improve fixation of dental implants in the maxilla: A pilot study
- 2010
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Ingår i: International Journal of Oral and Maxillofacial Surgery. - : Elsevier Science B.V., Amsterdam. - 0901-5027 .- 1399-0020. ; 39:7, s. 673-677
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Tidskriftsartikel (refereegranskat)abstract
- This pilot study evaluates the clinical stability of bisphosphonate-coated dental implants placed using a two-stage surgical procedure in five patients. Each patient received seven regular Brånemark implants, one of which was coated with bisphosphonate in a fibrinogen matrix. The coated implant was inserted where the bone was expected to have the least favourable quality. The level of the marginal bone around each implant was measured by intraoral periapical radiographs and implant stability was recorded using resonance frequency measurements. Frequency values (ISQ) were obtained peroperatively before flap closure and after 6 months at abutment connection. At abutment connection the bisphosphonate-coated implants were removed en bloc in two patients for histological examination. An animal experiment had previously confirmed that gamma-sterilization did not reduce bioactivity of the bisphosphonate coating. In each patient, the bisphosphonate-coated implant showed the largest improvement in ISQ level of all implants. Their values at the start tended to be lower, and the absolute value at 6 months did not differ. No complications occurred with the coated implants. Histology showed no abnormalities. Improvement in ISQ values was an expected effect of the bisphosphonate coating, but could be due to the choice of insertion site. This finding warrants a randomized, blinded study.
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| 2. |
- Ge, Chenjie, 1991, et al.
(författare)
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Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size, and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included.
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| 3. |
- Hellstrand Tang, Ulla, 1956, et al.
(författare)
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Exploring the Role of Complexity in Health Care Technology Bottom-Up Innovations : Multiple-Case Study Using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability Complexity Assessment Tool
- 2024
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Ingår i: JMIR Human Factors. - : JMIR Publications. - 2292-9495. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: New digital technology presents new challenges to health care on multiple levels. There are calls for further research that considers the complex factors related to digital innovations in complex health care settings to bridge the gap when moving from linear, logistic research to embracing and testing the concept of complexity. The nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework was developed to help study complexity in digital innovations.OBJECTIVE: This study aims to investigate the role of complexity in the development and deployment of innovations by retrospectively assessing challenges to 4 digital health care innovations initiated from the bottom up.METHODS: A multicase retrospective, deductive, and explorative analysis using the NASSS complexity assessment tool LONG was conducted. In total, 4 bottom-up innovations developed in Region Västra Götaland in Sweden were explored and compared to identify unique and shared complexity-related challenges.RESULTS: The analysis resulted in joint insights and individual learning. Overall, the complexity was mostly found outside the actual innovation; more specifically, it related to the organization's readiness to integrate new innovations, how to manage and maintain innovations, and how to finance them. The NASSS framework sheds light on various perspectives that can either facilitate or hinder the adoption, scale-up, and spread of technological innovations. In the domain of condition or diagnosis, a well-informed understanding of the complexity related to the condition or illness (diabetes, cancer, bipolar disorders, and schizophrenia disorders) is of great importance for the innovation. The value proposition needs to be clearly described early to enable an understanding of costs and outcomes. The questions in the NASSS complexity assessment tool LONG were sometimes difficult to comprehend, not only from a language perspective but also due to a lack of understanding of the surrounding organization's system and its setting.CONCLUSIONS: Even when bottom-up innovations arise within the same support organization, the complexity can vary based on the developmental phase and the unique characteristics of each project. Identifying, defining, and understanding complexity may not solve the issues but substantially improves the prospects for successful deployment. Successful innovation within complex organizations necessitates an adaptive leadership and structures to surmount cultural resistance and organizational impediments. A rigid, linear, and stepwise approach risks disregarding interconnected variables and dependencies, leading to suboptimal outcomes. Success lies in embracing the complexity with its uncertainty, nurturing creativity, and adopting a nonlinear methodology that accommodates the iterative nature of innovation processes within complex organizations.
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| 4. |
- Kjeldgård, Linnea, 1985-, et al.
(författare)
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Sickness absence and disability pension among injured working-aged pedestrians - a population-based Swedish register study
- 2021
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Ingår i: BMC Public Health. - : Springer Science and Business Media LLC. - 1471-2458. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The knowledge is scarce about sickness absence (SA) and disability pension (DP) among pedestrians injured in a traffic-related accident, including falls. Thus, the aim was to explore the frequencies of types of accidents and injuries and their association with SA and DP among working-aged individuals. Methods: A nationwide register-based study, including all individuals aged 16-64 and living in Sweden, who in 2010 had in- or specialized outpatient healthcare after a new traffic-related accident as a pedestrian. Information on age, sex, sociodemographics, SA, DP, type of accident, injury type, and injured body region was used. Frequencies of pedestrians with no SA or DP, with ongoing SA or full-time DP already at the time of the accident, and with a new SA spell >14 days in connection to the accident were analyzed. Crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for new SA were estimated by logistic regression. Results: In total, 5576 pedestrians received healthcare due to a traffic-related accident (of which 75% were falls, with half of the falls related to snow and ice). At the time of the accident, 7.5% were already on SA and 10.8% on full-time DP, while 20% started a new SA spell. The most common types of injuries were fractures (45%) and external injuries (30%). The body region most frequently injured was the lower leg, ankle, foot, and other (in total 26%). Older individuals had a higher OR for new SA compared with younger (OR 1.91; 95% CI 1.44-2.53, for ages: 45-54 vs. 25-34). The injury type with the highest OR for new SA, compared with the reference group external injuries, was fractures (9.58; 7.39-12.43). The injured body region with the highest OR for new SA, compared with the reference group head, face, and neck, was lower leg, ankle, foot, and other (4.52; 2.78-7.36). Conclusions: In this explorative nationwide study of the working-aged pedestrians injured in traffic-related accidents including falls, one fifth started a new SA spell >14 days. Fractures, internal injuries, collisions with motor vehicle, and falls related to snow and ice had the strongest associations with new SA.
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| 5. |
- Alt Murphy, Margit, 1970, et al.
(författare)
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An upper body garment with integrated sensors for people with neurological disorders – early development and evaluation
- 2019
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Ingår i: BMC Biomedical Engineering. - : Springer Science and Business Media LLC. - 2524-4426. ; 1:3
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Tidskriftsartikel (refereegranskat)abstract
- Background: To develop a novel wearable garment with integrated sensors for continuous monitoring of physiological and movement related variables to evaluate progression, tailor treatments and improve diagnosis in epilepsy, Parkinson’s disease and stroke. Methods: An iterative development process and evaluation of an upper body garment with integrated sensors included: identification of user needs, specification of technical and garment requirements, garment development and production as well as evaluation of garment design, functionality and usability. The project is a multidisciplinary collaboration with experts from medical, engineering, textile, and material science within the wearITmed consortium. The work was organized in regular meetings, task groups and hands-on workshops. User needs were identified using results from a mixed-methods systematic review, a focus group study and expert groups. Usability was evaluated in 19 individuals (13 controls, 6 patients with Parkinson’s disease) using semi-structured interviews and qualitative content analysis. Results: A prototype designed to monitor movements and heart rate was developed. The garment was well accepted by the users regarding design and comfort, although the users were cautious about the technology and suggested improvements. All electronic components passed a washability test. The most robust data was obtained from accelerometer and gyroscope sensors while the electrodes for heart rate registration were sensitive to motion. artefacts. The algorithm development within the wearITmed consortium has shown promising results. Conclusions: The prototype was accepted by the users. Technical improvements are needed, but preliminary data indicate that the garment has potential to be used as a tool for diagnosis and treatment selection and could provide added value for monitoring seizures in epilepsy, fluctuations in PD and activity levels in stroke. Future work aims to improve the prototype further, develop algorithms, and evaluate the functionality and usability in targeted patient groups. The potential of incorporating blood pressure and heart-rate variability monitoring will also be explored.
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| 6. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
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A novel federated deep learning scheme for glioma and its subtype classification
- 2023
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Ingår i: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: Deep learning (DL) has shown promising results in molecular-based classification of glioma subtypes from MR images. DL requires a large number of training data for achieving good generalization performance. Since brain tumor datasets are usually small in size, combination of such datasets from different hospitals are needed. Data privacy issue from hospitals often poses a constraint on such a practice. Federated learning (FL) has gained much attention lately as it trains a central DL model without requiring data sharing from different hospitals. Method: We propose a novel 3D FL scheme for glioma and its molecular subtype classification. In the scheme, a slice-based DL classifier, EtFedDyn, is exploited which is an extension of FedDyn, with the key differences on using focal loss cost function to tackle severe class imbalances in the datasets, and on multi-stream network to exploit MRIs in different modalities. By combining EtFedDyn with domain mapping as the pre-processing and 3D scan-based post-processing, the proposed scheme makes 3D brain scan-based classification on datasets from different dataset owners. To examine whether the FL scheme could replace the central learning (CL) one, we then compare the classification performance between the proposed FL and the corresponding CL schemes. Furthermore, detailed empirical-based analysis were also conducted to exam the effect of using domain mapping, 3D scan-based post-processing, different cost functions and different FL schemes. Results: Experiments were done on two case studies: classification of glioma subtypes (IDH mutation and wild-type on TCGA and US datasets in case A) and glioma grades (high/low grade glioma HGG and LGG on MICCAI dataset in case B). The proposed FL scheme has obtained good performance on the test sets (85.46%, 75.56%) for IDH subtypes and (89.28%, 90.72%) for glioma LGG/HGG all averaged on five runs. Comparing with the corresponding CL scheme, the drop in test accuracy from the proposed FL scheme is small (−1.17%, −0.83%), indicating its good potential to replace the CL scheme. Furthermore, the empirically tests have shown that an increased classification test accuracy by applying: domain mapping (0.4%, 1.85%) in case A; focal loss function (1.66%, 3.25%) in case A and (1.19%, 1.85%) in case B; 3D post-processing (2.11%, 2.23%) in case A and (1.81%, 2.39%) in case B and EtFedDyn over FedAvg classifier (1.05%, 1.55%) in case A and (1.23%, 1.81%) in case B with fast convergence, which all contributed to the improvement of overall performance in the proposed FL scheme. Conclusion: The proposed FL scheme is shown to be effective in predicting glioma and its subtypes by using MR images from test sets, with great potential of replacing the conventional CL approaches for training deep networks. This could help hospitals to maintain their data privacy, while using a federated trained classifier with nearly similar performance as that from a centrally trained one. Further detailed experiments have shown that different parts in the proposed 3D FL scheme, such as domain mapping (make datasets more uniform) and post-processing (scan-based classification), are essential.
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| 7. |
- Johansson, Björn
(författare)
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Opacification of anterior part of hydrophilic acrylic IOL or a prelenticular inflammatory membrane?
- 2012
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Ingår i: Journal of cataract and refractive surgery. - Philadelphia : Elsevier. - 0886-3350 .- 1873-4502. ; 38:6, s. 1115-1116
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Tidskriftsartikel (refereegranskat)abstract
- In their recent case report, Park and Chuck1 describe the bilateral appearance of an opacification at the plane of the anterior surface of the hydrophilic acrylic Akreos MI60 intraocular lens (IOL) (Bausch & Lomb). The patient's general history of diabetes mellitus, proliferative retinopathy, and iris rubeosis explains the limited pupil dilation preventing visualization of the capsulorhexis opening in their slitlamp images.
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| 8. |
- Palmquist, Anders, 1977, et al.
(författare)
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Complex geometry and integrated macro-porosity: Clinical applications of electron beam melting to fabricate bespoke bone-anchored implants
- 2023
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Ingår i: Acta Biomaterialia. - : Elsevier BV. - 1742-7061 .- 1878-7568. ; 156, s. 125-145
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Forskningsöversikt (refereegranskat)abstract
- The last decade has witnessed rapid advancements in manufacturing technologies for biomedical implants. Additive manufacturing (or 3D printing) has broken down major barriers in the way of producing complex 3D geometries. Electron beam melting (EBM) is one such 3D printing process applicable to metals and alloys. EBM offers build rates up to two orders of magnitude greater than comparable laser-based technologies and a high vacuum environment to prevent accumulation of trace elements. These features make EBM particularly advantageous for materials susceptible to spontaneous oxidation and nitrogen pick-up when exposed to air (e.g., titanium and titanium-based alloys). For skeletal reconstruction(s), anatomical mimickry and integrated macro-porous architecture to facilitate bone ingrowth are undoubtedly the key features of EBM manufactured implants. Using finite element modelling of physiological loading conditions, the design of a prosthesis may be further personalised. This review looks at the many unique clinical applications of EBM in skeletal repair and the ground-breaking innovations in prosthetic rehabilitation. From a simple acetabular cup to the fifth toe, from the hand-wrist complex to the shoulder, and from vertebral replacement to cranio-maxillofacial reconstruction, EBM has experienced it all. While sternocostal reconstructions might be rare, the repair of long bones using EBM manufactured implants is becoming exceedingly frequent. Despite the various merits, several challenges remain yet untackled. Nevertheless, with the capability to produce osseointegrating implants of any conceivable shape/size, and permissive of bone ingrowth and functional loading, EBM can pave the way for numerous fascinating and novel applications in skeletal repair, regeneration, and rehabilitation. Statement of significance: Electron beam melting (EBM) offers unparalleled possibilities in producing contaminant-free, complex and intricate geometries from alloys of biomedical interest, including Ti6Al4V and CoCr. We review the diverse range of clinical applications of EBM in skeletal repair, both as mass produced off-the-shelf implants and personalised, patient-specific prostheses. From replacing large volumes of disease-affected bone to complex, multi-material reconstructions, almost every part of the human skeleton has been replaced with an EBM manufactured analog to achieve macroscopic anatomical-mimickry. However, various questions regarding long-term performance of patient-specific implants remain unaddressed. Directions for further development include designing personalised implants and prostheses based on simulated loading conditions and accounting for trabecular bone microstructure with respect to physiological factors such as patient's age and disease status.
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| 9. |
- Borrelli, Pablo, et al.
(författare)
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Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival
- 2021
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 41:1, s. 62-67
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods can provide an objective image analysis. We aimed at developing and validating an AI-based tool for detection of lymph node lesions. Methods A group of 399 patients with biopsy-proven PCa who had undergone(18)F-choline PET/CT for staging prior to treatment were used to train (n = 319) and test (n = 80) the AI-based tool. The tool consisted of convolutional neural networks using complete PET/CT scans as inputs. In the test set, the AI-based lymph node detections were compared to those of two independent readers. The association with PCa-specific survival was investigated. Results The AI-based tool detected more lymph node lesions than Reader B (98 vs. 87/117;p = .045) using Reader A as reference. AI-based tool and Reader A showed similar performance (90 vs. 87/111;p = .63) using Reader B as reference. The number of lymph node lesions detected by the AI-based tool, PSA, and curative treatment was significantly associated with PCa-specific survival. Conclusion This study shows the feasibility of using an AI-based tool for automated and objective interpretation of PET/CT images that can provide assessments of lymph node lesions comparable with that of experienced readers and prognostic information in PCa patients.
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| 10. |
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