| 61. |
- Polymeri, Erini, et al.
(författare)
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Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
- 2020
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Ingår i: Clinical Physiology and Functional Imaging. - Chichester : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 40:2, s. 106-113
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-naïve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2·65, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by Sørensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0·78 and 0·79, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P = 0·02), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival. © 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine
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| 62. |
- Memedi, Mevludin, 1983-, et al.
(författare)
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A web application for follow-up of results from a mobile device test battery for Parkinson’s disease patients
- 2011
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Ingår i: Computer Methods and Programs in Biomedicine. - Amsterdam : Elsevier BV. - 0169-2607 .- 1872-7565. ; 104:2, s. 219-226
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Tidskriftsartikel (refereegranskat)abstract
- A test battery consisting of self-assessments and motor tests for patients with Parkinson’s disease (PD) was constructed and implemented on a hand computer with touch screen in a telemedicine setting. In this work, a Web-based system was developed to deliver decision support information to treating clinical staff for assessing PD symptoms in their patients. Test results from the hand unit are transferred to a central server and processed into scores for different symptom dimensions and an “overall test score” reflecting the overall condition of the patient during a test period. The IBM Computer System Usability Questionnaire was administered to assess the users’ satisfaction with the system. Results showed that a majority of users who completed the evaluation were quite satisfied with the usability although a sizeable minority were not. Response times were tested by simulating up to 100 users accessing the web application at the same time. The average page completion times were in the range of 0.5 seconds indicating fast response. The system was able to summarize the test-battery data and present them in a useful manner. Its main contribution is a novel way to easily access symptom information from the home environment of patients.
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| 63. |
- Fredenberg, Erik, PhD, 1979-, et al.
(författare)
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A low-absorption x-ray energy filter for small-scale applications
- 2009
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Ingår i: Optics Express. - : The Optical Society. - 1094-4087. ; 17:14, s. 11388-11398
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Tidskriftsartikel (refereegranskat)abstract
- We present an experimental and theoretical evaluation of an x-ray energy filter based on the chromatic properties of a prism-array lens (PAL). It is intended for small-scale applications such as medical imaging. The PAL approximates a Fresnel lens and allows for high efficiency compared to filters based on ordinary refractive lenses, however at the cost of a lower energy resolution. Geometrical optics was found to provide a good approximation for the performance of a flawless lens, but a field-propagation model was used for quantitative predictions. The model predicted a 0.29 ΔE/E energy resolution and an intensity gain of 6.5 for a silicon PAL at 23.5 keV. Measurements with an x-ray tube showed good agreement with the model in energy resolution and peak energy, but a blurred focal line contributed to a 29% gain reduction. We believe the blurring to be caused mainly by lens imperfections, in particular at the periphery of the lens.
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| 64. |
- Forsgren, Mikael
(författare)
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The Non-Invasive Liver Biopsy : Determining Hepatic Function in Diffuse and Focal LiverDisease
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The liver is one of the largest organs within the human body and it handles many vital tasks such as nutrient processing, toxin removal, and synthesis of important proteins. The number of people suffering from chronic liver disease is on the rise, likely due to the present ‘western’ lifestyle. As disease develops in the liver there are pathophysiological manifestations within the liver parenchyma that are both common and important to monitor. These manifestations include inflammation, fatty infiltration (steatosis), excessive scar tissue formation (fibrosis and cirrhosis), and iron loading. Importantly, as the disease progresses there is concurrent loss of liver function. Furthermore, postoperative liver function insufficiency is an important concern when planning surgical treatment of the liver, because it is associated with both morbidity and mortality. Liver function can also be hampered due to drug-induced injuries, an important aspect to consider in drug-development.Currently, an invasive liver needle biopsy is required to determine the aetiology and to stage or grade the pathophysiological manifestations. There are important limitations with the biopsy, which include, risk of serious complications, mortality, morbidity, inter- and intra-observer variability, sampling error, and sampling variability. Cleary, it would be beneficial to be able investigate the pathophysiological manifestations accurately, non-invasively, and on regional level.Current available laboratory liver function blood panels are typically insufficient and often only indicate damage at a late stage. Thus, it would be beneficial to have access to biomarkers that are both sensitive and responds to early changes in liver function in both clinical settings and for the pharmaceutical industry and regulatory agencies.The main aim of this thesis was to develop and evaluate methods that can be used for a ‘non-invasive liver biopsy’ using magnetic resonance (MR). We also aimed to develop sensitive methods for measure liver function based on gadoxetate-enhanced MR imaging (MRI).The presented work is primarily based on a prospective study on c. 100 patients suffering from chronic liver disease of varying aetiologies recruited due to elevated liver enzyme levels, without clear signs of decompensated cirrhosis. Our results show that the commonly used liver fat cut-off for diagnosing steatosis should be lowered from 5% to 3% when using MR proton-density fat fraction (PDFF). We also show that MR elastography (MRE) is superior in staging fibrosis.Finally we presented a framework for quantifying liver function based on gadoxetate-enhanced MRI. The method is based on clinical images and a clinical approved contrast agent (gadoxetate). The framework consists of; state-of the-art image reconstruction and correction methods, a mathematical model, and a precise model parametrization method. The model was developed and validated on healthy subjects. Thereafter the model was found applicable on the chronic liver disease cohort as well as validated using gadoxetate levels in biopsy samples and blood samples. The liver function parameters correlated with clinical markers for liver function and liver fibrosis (used as a surrogate marker for liver function).In summary, it should be possible to perform a non-invasive liver biopsy using: MRI-PDFF for liver fat and iron loading, MRE for liver fibrosis and possibly also inflammation, and measure liver function using the presented framework for analysing gadoxetate-enhanced MRI. With the exception of an MREtransducer no additional hardware is required on the MR scanner. The liver function method is likely to be useful both in a clinical setting and in pharmaceutical trials.
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| 65. |
- Jurcevic, Sanja, 1971-, et al.
(författare)
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Bioinformatics analysis of miRNAs in the neuroblastoma 11q-deleted region reveals a role of miR-548l in both 11q-deleted and MYCN amplified tumour cells
- 2022
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Neuroblastoma is a childhood tumour that is responsible for approximately 15% of all childhood cancer deaths. Neuroblastoma tumours with amplification of the oncogene MYCN are aggressive, however, another aggressive subgroup without MYCN amplification also exists; rather, they have a deleted region at chromosome arm 11q. Twenty-six miRNAs are located within the breakpoint region of chromosome 11q and have been checked for a possible involvement in development of neuroblastoma due to the genomic alteration. Target genes of these miRNAs are involved in pathways associated with cancer, including proliferation, apoptosis and DNA repair. We could show that miR-548l found within the 11q region is downregulated in neuroblastoma cell lines with 11q deletion or MYCN amplification. In addition, we showed that the restoration of miR-548l level in a neuroblastoma cell line led to a decreased proliferation of these cells as well as a decrease in the percentage of cells in the S phase. We also found that miR-548l overexpression suppressed cell viability and promoted apoptosis, while miR-548l knockdown promoted cell viability and inhibited apoptosis in neuroblastoma cells. Our results indicate that 11q-deleted neuroblastoma and MYCN amplified neuroblastoma coalesce by downregulating miR-548l.
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| 66. |
- Makvandi, Kianoush, et al.
(författare)
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Multiparametric magnetic resonance imaging allows non-invasive functional and structural evaluation of diabetic kidney disease
- 2022
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Ingår i: Clinical Kidney Journal. - : Oxford University Press (OUP). - 2048-8505 .- 2048-8513. ; 15:7, s. 1387-1402
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Tidskriftsartikel (refereegranskat)abstract
- Background We sought to develop a novel non-contrast multiparametric MRI (mpMRI) protocol employing several complementary techniques in a single scan session for a comprehensive functional and structural evaluation of diabetic kidney disease (DKD). Methods In the cross-sectional part of this prospective observational study, 38 subjects ages 18-79 years with type 2 diabetes and DKD [estimated glomerular filtration rate (eGFR) 15-60 mL/min/1.73 m(2)] and 20 age- and gender-matched healthy volunteers (HVs) underwent mpMRI. Repeat mpMRI was performed on 23 DKD subjects and 10 HVs. By measured GFR (mGFR), 2 DKD subjects had GFR stage G2, 16 stage G3 and 20 stage G4/G5. A wide range of MRI biomarkers associated with kidney haemodynamics, oxygenation and macro/microstructure were evaluated. Their optimal sensitivity, specificity and repeatability to differentiate diabetic versus healthy kidneys and categorize various stages of disease as well as their correlation with mGFR/albuminuria was assessed. Results Several MRI biomarkers differentiated diabetic from healthy kidneys and distinct GFR stages (G3 versus G4/G5); mean arterial flow (MAF) was the strongest predictor (sensitivity 0.94 and 1.0, specificity 1.00 and 0.69; P = .04 and .004, respectively). Parameters significantly correlating with mGFR were specific measures of kidney haemodynamics, oxygenation, microstructure and macrostructure, with MAF being the strongest univariate predictor (r = 0.92; P < .0001). Conclusions A comprehensive and repeatable non-contrast mpMRI protocol was developed that, as a single, non-invasive tool, allows functional and structural assessment of DKD, which has the potential to provide valuable insights into underlying pathophysiology, disease progression and analysis of efficacy/mode of action of therapeutic interventions in DKD.
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| 67. |
- Calon, Tim, et al.
(författare)
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Multimodal analysis of the tissue response to a bone-anchored hearing implant. : 11.Calon TGA, Johansson ML, Omar O, Shah FA, Budding D, Trobos M, Thomsen P, Stokroos RJ, Palmquist
- 2019
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Ingår i: 2nd Politzer Society Meeting/2nd World Congress of Otology, 28 May - 1 June, 2019, Warsaw, Poland..
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 68. |
- Sarve, Hamid, et al.
(författare)
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Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes.
- 2011
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Ingår i: Computer methods and programs in biomedicine. - : Elsevier BV. - 1872-7565 .- 0169-2607. ; 102:1, s. 25-34
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Tidskriftsartikel (refereegranskat)abstract
- Bone-implant integration is measured in several ways. Traditionally and routinely, 2D histological sections of samples, containing bone and the biomaterial, are stained and analyzed using a light microscope. Such histological section provides detailed cellular information about the bone regeneration in the proximity of the implant. However, this information reflects the integration in only a very small fraction, a 10 μm thick slice, of the sample. In this study, we show that feature values quantified on 2D sections are highly dependent on the orientation and the placement of the section, suggesting that a 3D analysis of the whole sample is of importance for a more complete judgment of the bone structure in the proximity of the implant. We propose features describing the 3D data by extending the features traditionally used for 2D-analysis. We present a method for extracting these features from 3D image data and we measure them on five 3D SRμCT image volumes. We also simulate cuts through the image volume positioned at all possible section positions. These simulations show that the measurement variations due to the orientation of the section around the center line of the implant are about 30%.
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| 69. |
- Fredriksson, Alexandru Grigorescu, et al.
(författare)
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Turbulent kinetic energy in the right ventricle : Potential MR marker for risk stratification of adults with repaired Tetralogy of Fallot
- 2018
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Ingår i: Journal of Magnetic Resonance Imaging. - Hoboken : John Wiley & Sons. - 1053-1807 .- 1522-2586. ; 47:4, s. 1043-1053
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To assess right ventricular (RV) turbulent kinetic energy (TKE) in patients with repaired Tetralogy of Fallot (rToF) and a spectrum of pulmonary regurgitation (PR), as well as to investigate the relationship between these 4D flow markers and RV remodeling.Materials and Methods: Seventeen patients with rToF and 10 healthy controls were included in the study. Patients were divided into two groups based on PR fraction: one lower PR fraction group (11%) and one higher PR fraction group (>11%). Field strength/sequences: 3D cine phase contrast (4D flow), 2D cine phase contrast (2D flow), and balanced steady-state free precession (bSSFP) at 1.5T. Assessment: The RV volume was segmented in the morphologic short-axis images and TKE parameters were computed inside the segmented RV volume throughout diastole. Statistical tests: One-way analysis of variance with Bonferroni post-hoc test; unpaired t-test; Pearson correlation coefficients; simple and stepwise multiple regression models; intraclass correlation coefficient (ICC).Results: The higher PR fraction group had more remodeled RVs (140 6 25 vs. 107 6 22 [lower PR fraction, P < 0.01] and 93 6 15 ml/m2[healthy, P < 0.001] for RV end-diastolic volume index [RVEDVI]) and higher TKE values (5.95 6 3.15 vs. 2.23 6 0.81 [lower PR fraction, P < 0.01] and 1.91 6 0.78 mJ [healthy, P < 0.001] for Peak Total RV TKE). Multiple regression analysis between RVEDVI and 4D/2D flow parameters showed that Peak Total RV TKE was the strongest predictor of RVEDVI (R25 0.47, P 5 0.002).Conclusion: The 4D flow-specific TKE markers showed a slightly stronger association with RV remodeling than conventional 2D flow PR parameters. These results suggest novel hemodynamic aspects of PR in the development of late complications after ToF repair.
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| 70. |
- Javeed, Ashir, 1989-, et al.
(författare)
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Breaking barriers : a statistical and machine learning-based hybrid system for predicting dementia
- 2023
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Ingår i: Frontiers in Bioengineering and Biotechnology. - : Frontiers Media S.A.. - 2296-4185. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Dementia is a condition (a collection of related signs and symptoms) that causes a continuing deterioration in cognitive function, and millions of people are impacted by dementia every year as the world population continues to rise. Conventional approaches for determining dementia rely primarily on clinical examinations, analyzing medical records, and administering cognitive and neuropsychological testing. However, these methods are time-consuming and costly in terms of treatment. Therefore, this study aims to present a noninvasive method for the early prediction of dementia so that preventive steps should be taken to avoid dementia. Methods: We developed a hybrid diagnostic system based on statistical and machine learning (ML) methods that used patient electronic health records to predict dementia. The dataset used for this study was obtained from the Swedish National Study on Aging and Care (SNAC), with a sample size of 43040 and 75 features. The newly constructed diagnostic extracts a subset of useful features from the dataset through a statistical method (F-score). For the classification, we developed an ensemble voting classifier based on five different ML models: decision tree (DT), naive Bayes (NB), logistic regression (LR), support vector machines (SVM), and random forest (RF). To address the problem of ML model overfitting, we used a cross-validation approach to evaluate the performance of the proposed diagnostic system. Various assessment measures, such as accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and Matthew’s correlation coefficient (MCC), were used to thoroughly validate the devised diagnostic system’s efficiency. Results: According to the experimental results, the proposed diagnostic method achieved the best accuracy of 98.25%, as well as sensitivity of 97.44%, specificity of 95.744%, and MCC of 0.7535. Discussion: The effectiveness of the proposed diagnostic approach is compared to various cutting-edge feature selection techniques and baseline ML models. From experimental results, it is evident that the proposed diagnostic system outperformed the prior feature selection strategies and baseline ML models regarding accuracy.
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