Publications by authors named "Anders Heyden"

8 Publications

  • Page 1 of 1

An Artificial Intelligence-based Support Tool for Automation and Standardisation of Gleason Grading in Prostate Biopsies.

Eur Urol Focus 2021 Sep 7;7(5):995-1001. Epub 2020 Dec 7.

Division of Urological Cancers, Department of Translational Medicine, Lund University, Malmö, Sweden. Electronic address:

Background: Gleason grading is the standard diagnostic method for prostate cancer and is essential for determining prognosis and treatment. The dearth of expert pathologists, the inter- and intraobserver variability, as well as the labour intensity of Gleason grading all necessitate the development of a user-friendly tool for robust standardisation.

Objective: To develop an artificial intelligence (AI) algorithm, based on machine learning and convolutional neural networks, as a tool for improved standardisation in Gleason grading in prostate cancer biopsies.

Design, Setting, And Participants: A total of 698 prostate biopsy sections from 174 patients were used for training. The training sections were annotated by two senior consultant pathologists. The final algorithm was tested on 37 biopsy sections from 21 patients, with digitised slide images from two different scanners.

Outcome Measurements And Statistical Analysis: Correlation, sensitivity, and specificity parameters were calculated.

Results And Limitations: The algorithm shows high accuracy in detecting cancer areas (sensitivity: 100%, specificity: 68%). Compared with the pathologists, the algorithm also performed well in detecting cancer areas (intraclass correlation coefficient [ICC]: 0.99) and assigning the Gleason patterns correctly: Gleason patterns 3 and 4 (ICC: 0.96 and 0.94, respectively), and to a lesser extent, Gleason pattern 5 (ICC: 0.82). Similar results were obtained using two different scanners.

Conclusions: Our AI-based algorithm can reliably detect prostate cancer and quantify the Gleason patterns in core needle biopsies, with similar accuracy as pathologists. The results are reproducible on images from different scanners with a proven low level of intraobserver variability. We believe that this AI tool could be regarded as an efficient and interactive tool for pathologists.

Patient Summary: We developed a sensitive artificial intelligence tool for prostate biopsies, which detects and grades cancer with similar accuracy to pathologists. This tool holds promise to improve the diagnosis of prostate cancer.
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http://dx.doi.org/10.1016/j.euf.2020.11.001DOI Listing
September 2021

Immediate loading of implants in the edentulous mandible: a multicentre study.

Oral Maxillofac Surg 2016 Dec 16;20(4):385-390. Epub 2016 Sep 16.

Department of Oral & Maxillofacial Surgery and Periodontics, Faculty of Dentistry of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.

Purpose: The aim of this prospective study was to investigate the two-year outcomes following immediate loading of mono-cortically engaged implants.

Materials And Methods: Thirty healthy mandible edentulous patients with an average age of 67.3 years and presenting with sufficient bony ridge at the mandible symphysis were included in the study. Four Astra Tech, Ti-Oblast implants were installed between the mental foramina using the mono-cortical anchorage technique. The primary stability of the implants was assessed by resonance frequency analysis (RFA). After uni-abutments were placed, a temporary bridge was constructed and fixed the same day. The definitive bridges were installed 6 weeks after implant surgery. Five of 120 placed implants were lost in four patients during the first 6 weeks and these patients were excluded from the follow-up. The changes in marginal bone level (n = 20) were evaluated in Brazilian and Swedish groups at baseline, 6 weeks, 6 months, 12 months and 24 months. The RFA (n = 30) was evaluated at baseline, 6 weeks, 6 months, 12 months and 24 months postoperatively.

Results: Compared with baseline measurements, the postoperative values for marginal bone level (6 weeks, 6 months, 12 months and 24 months) were significantly reduced (p < 0.05), while no differences were observed in the RFA analysis (12 months and 24 months).

Conclusions: The immediate loading of mono-cortically engaged implants in the edentulous mandible is safe and predictable and implant stability remains excellent after 2-year follow-up.
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http://dx.doi.org/10.1007/s10006-016-0577-yDOI Listing
December 2016

Efficient simulations of tubulin-driven axonal growth.

J Comput Neurosci 2016 08 28;41(1):45-63. Epub 2016 Apr 28.

Centre for Mathematical Sciences, Lund University, P.O. Box 118, 221 00, Lund, Sweden.

This work concerns efficient and reliable numerical simulations of the dynamic behaviour of a moving-boundary model for tubulin-driven axonal growth. The model is nonlinear and consists of a coupled set of a partial differential equation (PDE) and two ordinary differential equations. The PDE is defined on a computational domain with a moving boundary, which is part of the solution. Numerical simulations based on standard explicit time-stepping methods are too time consuming due to the small time steps required for numerical stability. On the other hand standard implicit schemes are too complex due to the nonlinear equations that needs to be solved in each step. Instead, we propose to use the Peaceman-Rachford splitting scheme combined with temporal and spatial scalings of the model. Simulations based on this scheme have shown to be efficient, accurate, and reliable which makes it possible to evaluate the model, e.g. its dependency on biological and physical model parameters. These evaluations show among other things that the initial axon growth is very fast, that the active transport is the dominant reason over diffusion for the growth velocity, and that the polymerization rate in the growth cone does not affect the final axon length.
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http://dx.doi.org/10.1007/s10827-016-0604-xDOI Listing
August 2016

Multimodel pathway enrichment methods for functional evaluation of expression regulation.

J Proteome Res 2012 May 21;11(5):2955-67. Epub 2012 Apr 21.

Department of Immunotechnology, Lund University Biomedical Centre D13, SE-221 84 Lund, Sweden.

Functional analysis of quantitative expression data is becoming common practice within the proteomics and transcriptomics fields; however, a gold standard for this type of analysis has yet not emerged. To grasp the systemic changes in biological systems, efficient and robust methods are needed for data analysis following expression regulation experiments. We discuss several conceptual and practical challenges potentially hindering the emergence of such methods and present a novel method, called FEvER, that utilizes two enrichment models in parallel. We also present analysis of three disparate differential expression data sets using our method and compare our results to other established methods. With many useful features such as pathway hierarchy overview, we believe the FEvER method and its software implementation will provide a useful tool for peers in the field of proteomics. Furthermore, we show that the method is also applicable to other types of expression data.
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http://dx.doi.org/10.1021/pr300038bDOI Listing
May 2012

An improved method for detecting and delineating genomic regions with altered gene expression in cancer.

Genome Biol 2008 Jan 21;9(1):R13. Epub 2008 Jan 21.

Department of Clinical Genetics, Lund University Hospital, SE-221 85 Lund, Sweden.

Genomic regions with altered gene expression are a characteristic feature of cancer cells. We present a novel method for identifying such regions in gene expression maps. This method is based on total variation minimization, a classical signal restoration technique. In systematic evaluations, we show that our method combines top-notch detection performance with an ability to delineate relevant regions without excessive over-segmentation, making it a significant advance over existing methods. Software (Rendersome) is provided.
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http://dx.doi.org/10.1186/gb-2008-9-1-r13DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2395254PMC
January 2008

Variational surface interpolation from sparse point and normal data.

IEEE Trans Pattern Anal Mach Intell 2007 Jan;29(1):181-4

School of Technology and Society, Malmö University, SE-205 06 Malmö, Sweden.

Many visual cues for surface reconstruction from known views are sparse in nature, e.g., specularities, surface silhouettes, and salient features in an otherwise textureless region. Often, these cues are the only information available to an observer. To allow these constraints to be used either in conjunction with dense constraints such as pixel-wise similarity, or alone, we formulate such constraints in a variational framework. We propose a sparse variational constraint in the level set framework, enforcing a surface to pass through a specific point, and a sparse variational constraint on the surface normal along the observed viewing direction, as is the nature of, e.g., specularities. These constraints are capable of reconstructing surfaces from extremely sparse data. The approach has been applied and validated on the shape from specularities problem.
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http://dx.doi.org/10.1109/tpami.2007.250610DOI Listing
January 2007

Three-dimensional biofilm model with individual cells and continuum EPS matrix.

Biotechnol Bioeng 2006 Aug;94(5):961-79

Applied Mathematics Group, School of Technology and Society, Malmö University, Ostra/Stora Varvsgatan 11H, Malmö SE-205 06, Sweden.

An innovative type of biofilm model is derived by combining an individual description of microbial particles with a continuum representation of the biofilm matrix. This hybrid model retains the advantages of each approach, while providing a more realistic description of the temporal development of biofilm structure in two or three spatial dimensions. The general model derivation takes into account any possible number of soluble components. These are substrates and metabolic products, which diffuse and react in the biofilm within individual microbial cells. The cells grow, divide, and produce extracellular polymeric substances (EPS) in a multispecies model setting. The EPS matrix is described by a continuum representation as incompressible viscous fluid, which can expand and retract due to generation and consumption processes. The cells move due to a pushing mechanism between cells in colonies and by an advective mechanism supported by the EPS dynamics. Detachment of both cells and EPS follows a continuum approach, whereas cells attach in discrete events. Two case studies are presented for model illustration. Biofilm consolidation is explained by shrinking due to EPS and cell degradation processes. This mechanism describes formation of a denser layer of cells in the biofilm depth and occurrence of an irregularly shaped biofilm surface under nutrient limiting conditions. Micro-colony formation is investigated by growth of autotrophic microbial colonies in an EPS matrix produced by heterotrophic cells. Size and shape of colonies of ammonia and nitrite-oxidizing bacteria (NOB) are comparatively studied in a standard biofilm and in biofilms aerated from a membrane side.
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http://dx.doi.org/10.1002/bit.20917DOI Listing
August 2006

Segmentation of complex cell clusters in microscopic images: application to bone marrow samples.

Cytometry A 2005 Jul;66(1):24-31

Institute of Laboratory Medicine, Department of Clinical Genetics, Lund University Hospital, Lund, Sweden.

Background: Morphologic examination of bone marrow and peripheral blood samples continues to be the cornerstone in diagnostic hematology. In recent years, interest in automatic leukocyte classification using image analysis has increased rapidly. Such systems collect a series of images in which each cell must be segmented accurately to be classified correctly. Although segmentation algorithms have been developed for sparse cells in peripheral blood, the problem of segmenting the complex cell clusters characterizing bone marrow images is harder and has not been addressed previously.

Methods: We present a novel algorithm for segmenting clusters of any number of densely packed cells. The algorithm first oversegments the image into cell subparts. These parts are then assembled into complete cells by solving a combinatorial optimization problem in an efficient way.

Results: Our experimental results show that the algorithm succeeds in correctly segmenting densely clustered leukocytes in bone marrow images.

Conclusions: The presented algorithm enables image analysis-based analysis of bone marrow samples for the first time and may also be adopted for other digital cytometric applications where separation of complex cell clusters is required.
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http://dx.doi.org/10.1002/cyto.a.20153DOI Listing
July 2005
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