Scientific Papers - Life Sciences and Medical Imaging

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2009

Ahmed B A, Korn R, Kietzmann M, Kim J, Schmidt G, Binnig G, Haider M A : Automated CT Based Liver Volume Assessment Liver volume is an important measure of functional capacity. Much prior work has been done in normal livers without metastases.  Manual volumetry is time-consuming, tedious and generally not reproducible. Therefore, there has been a growing interest in the development of fast and accurate segmentation methods. The purpose of this study was to evaluate the accuracy of liver volume measured by a fully-automated segmentation software that quantifies liver volume in patients with metastatic liver disease using contextual information from adjacent structures, including lungs, the spine, ribs and gallbladder. (Poster presented by the Joint Department of Medical Imaging, University Health Network Mount Sinai Hospital and Womens College Hospital, the University of Toronto and Definiens at RSNA 2009)

Baatz M, Zimmermann J, Blackmore CG: Automated Analysis and Detailed Quantification of Biomedical Images Using Definiens Cognition Network Technology Biomedicine has seen tremendous advances in the field of image acquisition. The generation of digital images of high information content has become so straightforward and efficient that the volume of images accumulating in biomedical disciplines is posing significant challenges. Until now, conventional image analysis solutions are generally pixel-based and limited in the amount of information that they extract. However, a software system enabling the complex analysis of biomedical images should not impose restrictions on detection, classification and quantification of structures, but rather allow unlimited freedom to answer exhaustively all conceivable questions about the interactions and relationships between structures. Crucial to this is the precise and robust segmentation of relevant structures in digital micrographs. This challenge involves bringing structure, morphology and context into play. Based on the Definiens Cognition Network Technology(R), solutions have been deployed for use in biomedicine. The technology is object-oriented, multi-scale, context-driven and knowledge-based. Images are interpreted on the properties of networked image objects, which results in numerous advantages. This approach enables users to bring in detailed expert knowledge and enables complex analyses to be performed with unprecedented accuracy, even on poor quality data or for structures exhibiting heterogeneous properties or variable phenotypes. Extracted structures are the basis for detailed morphometric, structural and relational measurements which can be exported for each individual structure. These data can be used for decision support or correlated against experimental or molecular data, thus bridging classical biomedicine with molecular biology. An overview of the technology is provided with examples from different biomedical applications. (In: Combinatorial Chemistry and High Throughput Screening,  Nov 1 2009).

Eisenhauer EA , Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, Rubinstein L, Shankarg L, Dodd L, Kaplan R, Lacombe D, Verweij J: New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1) Background: Assessment of the change in tumour burden is an important feature of the clinical evaluation of cancer therapeutics: both tumour shrinkage (objective response) and disease progression are useful endpoints in clinical trials. Since RECISTwas published in 2000, many investigators, cooperative groups, industry and government authorities have adopted these criteria in the assessment of treatment outcomes. However, a number of questions and issues have arisen which have led to the development of a revised RECIST guideline (version 1.1). Evidence for changes, summarised in separate papers in this special issue, has come from assessment of a large data warehouse (>6500 patients), simulation studies and literature reviews. (...) Future work: A key question considered by the RECISTWorking Group in developing RECIST 1.1 was whether it was appropriate to move from anatomic unidimensional assessment of tumour burden to either volumetric anatomical assessment or to functional assessment with PET or MRI. It was concluded that, at present, there is not sufficient standardisation or evidence to abandon anatomical assessment of tumour burden. The only exception to this is in the use of FDG-PET imaging as an adjunct to determination of progression. As is detailed in the final paper in this special issue, the use of these promising newer approaches requires appropriate clinical validation studies. (in: European Journal of Cancer, Volume  45 , Issue 2, 2009, pp. 228 –247)  

Hesterman J Y , Zimmermann J , Hoppin J W, Gershman B , Harlin K, Yu H , Norenberg J P: Development of a segmentation routine for evaluating whole-body data sets spanning multiple SPECT/CT studies and applications Fast, accurate extraction of quantitative anatomical and functional information from 3D data sets is a critical, and sometimes rate-limiting, step in analyzing biological questions through in vivo imaging. The ability to apply a single analysis routine for the extraction of application-specific features helps resolve the time-limiting aspect of such analysis, increases reproducibility, and reduces observer variability. This work examines the ability of such an analysis  utine to evaluate whole-body data sets from a variety of small-animal SPECT/CT studies, consisting primarily of oncology applications, but also including pulmonary and neurology applications. (Poster presented at the 4th European Molecular Imaging Meeting of the European Society for Molecular Imaging ESMI, Barcelona/Spain, 27-30 May 2009).

Korn R, Schaepe A, Schmidt G, Binnig G, Bendtsen C: Lung Tumor Analysis (LuTA) with Definiens Cognition Network Technology® Accurate semi-automated and fully automated segmentation and quantification of organs are possible with Definiens Cognition Network Technology® by providing a framework for rapid development and scalable execution of image analysis solutions. Definiens Cognition Network Technology® combines pixel process techniques, with iterative, context-based object or segment generation and classification processes using a semantic knowledge base. Together with Merck Definiens co-developed a prototype application that demonstrates the ability to automatically and semi-automatically identify and recognize organs and tumors in DICoM (Digital Imaging and Communications in Medicine) images. The application is designed to enable fast and easy annotation of liver, lung nodules or other user-defined regions of interest. Flexible controls allow the annotation of structures of the user‘s choice. once a user has clicked on a region of interest, in one two-dimensional (2D) slice, the application builds out the object three-dimensionally (3D) and calculates the volume, length, width and thickness of the tumor. (Poster presented at the Merck Technology Symposium 2009)

Mair B, Tangl S, Feierfeil J, Skiba D, Watzek G, Gruber R: Age-related efficacy of parathyroid hormone on osseointegration in the rat Objective: Aging is a physiological determinant that can distinguish the outcome of a pharmaceutical therapy to improve osseointegration of titanium implants. Here we examined the possible interaction of intermittent parathyroid hormone (PTH) and the age of the recipient on the parameters of osseointegration in a rat tibia implantation model. Material and methods: Twenty female Wistar rats aged 8 months and 20 female rats aged 2 months received PTH at 60 mg/kg body weight or a vehicle by a subcutaneous injection three times a week. After 4 weeks, histomorphometric analysis of the peri-implant area was performed. The possible interaction of the two factors on ‘bone volume per tissue volume’  (BV/TV) and ‘bone-to-implant contact’ (BIC) was tested by two-way analysis of variance. Results: Based on data from the medullary compartment, two-way analysis of variance revealed that the effect of ‘intermittent PTH’ depends on the ‘age of the recipient’ when BV/TV is considered the dependent variable (P¼0.04). Post hoc tests indicated that PTH leads to an increase of BV/TV of adult and young rats. However, when BIC was considered the dependent variable, no interaction was observed (P¼0.14). PTH but not aging has a significant impact on BIC. In the cortical compartment, no effects of PTH on osseointegration were observed. Conclusions: The findings indicate that treatment with PTH is more effective on the periimplant bone regeneration in adult than in young animals, supporting the importance to consider the influences of age on the development of pharmaceutical therapies to increase the process of osseointegration. (In: Clinical Oral Implants Research, volume 20, issue 4, 2009, pp: 400–405)

Schönmeyer R, Ellenberg P, Feehan O, Schmidt G, Athelogou M, Binnig G: Image and Table Analysis for Automated Detection and Diagnosis of Breast Lesions within the Mammo-iCAD Research Project Mammo-iCAD is a research project funded by the Bavarian Research Administration with the aim of developing an intelligent software platform that supports diagnostic decision-making in mammography. By retrieving knowledge from radiologic images, diagnostic findings and demographical data, researchers want to build a thorough and collaborative network of expertise that enables medical practitioners to extract relevant information and combine it with their patients’ data to make better treatment decisions. The Definiens Research Team has developed a Case Based Reasoning (CBR) – Computer Aided Diagnosis (CAD) prototype for mammography data to help radiologists to match up patient cases with similar cases from a reference database. (Poster presented at CARS 2009 in Berlin, June 23-27)

Schmidt G, Kietzmann M, Kim J and Binnig G.: Definiens Cognition Network Technology for Fully Automatic 3D Segmentation of Lymph Nodes in CT Data Definiens Cognition Network Technology is used to automatically segment lymph nodes in their anatomical context from CT data. Image analysis results of 28 patient data sets are compared to annotations provided by medical experts. Related to the annotations the sensitivity is on average about 80% while the averaged false positive rate is about 2 per scan. (Paper presented at the 11th Congress of the IUPESM - the Medical Physics and Biomedical Engineering World Congress 2009; Munich, Sep 07 - 12, 2009)

Schmidt G, Zimmermann J, Binnig G.: Automated quantification of SPECT/CT information with Definiens Cognition Network Technology: Fast, accurate extraction of quantitative anatomical and functional information from 3D data sets is a critical step in analyzing biological questions through in vivo small animal imaging. This work examines the development of an image analysis solution to extract and quantify major anatomical features from SPECT/CT (single photon emission computed tomography) data using the Definiens Cognition Network Technology. The automation helps to reduce analysis time; increases reproducibility, and decreases observer variability. An application for early stage tumor quantification is shown. Methods: Using the commercially available software platform Definiens Developer, we developed an image analysis script to segment major organs from co-registered, dual-modality SPECT and CT image. The organs are detected in using a context-dependent approach which evolves the extracted mouse anatomical model from simple structures (e.g. body and lung) towards more challenging organs (e.g. kidney and heart). The analysis uses the CT information to extract the anatomy which provides further context for the SPECT analysis. The radiopharmaceutical uptake of the tumor was measured in a region refined by the anatomical model to reduce partial volume effects. The Definiens platform provided a rapid prototyping environment which reduced the development time for the image analysis solution to less than one week. Results: In a first evaluation, the body, bones, brain, kidneys, lungs, and bladder were successfully extracted using one single image analysis script. The uptake was measured automatically and exported to a database. The preliminary results are promising, in particular with respect of reproducibility within a single animal. This aspect is particular important for multiple time points pharmacokinetic studies. Conclusions: An image analysis routine was developed to enable automatic segmentation and measurement of many important anatomical features in pre-clinical SPECT/CT data sets encompassing a wide range of applications in oncology.(Abstract no. 38 for MipTec 2009, Basel, Oct 13 - 15, 2009)

Schwartz LH, Bogaerts J, Ford R, Shankar L, Therasse P, Gwyther S, Eisenhauer EA: Evaluation of lymph nodes with RECIST 1.1 Lymph nodes are common sites of metastatic disease in many solid tumours. Unlike most metastases, lymph nodes are normal anatomic structures and as such, normal lymph nodes will have a measurable size. Additionally, the imaging literature recommends that lymph nodes be measured in the short axis, since the short axis measurement is a more reproducible measurement and predictive of malignancy. Therefore, the RECIST committee recommends that lymph nodes be measured in their short axis and proposes measurement values and rules for categorising lymph nodes as normal or pathologic; either target or non-target lesions. Data for the RECIST warehouse are presented to demonstrate the potential change in response assessment following these rules. These standardised lymph node guidelines are designed to be easy to implement, focus target lesion measurements on lesions that are likely to be metastatic and prevent false progressions due to minimal change in size. (In: Euopean Journal of Cancer, Volume 45, Issue 2, 2009, pp 261-267)

Stoelzle T, Schwarb P, Trumpp A, Hynes NE: c-Myc affects mRNA translation, cell proliferation and progenitor cell function in the mammary gland BACKGROUND: The oncoprotein c-Myc has been intensely studied in breast cancer and mouse mammary tumor models, but relatively little is known about the normal physiological role of c-Myc in the mammary gland. Here we investigated functions of c-Myc during mouse mammary gland development using a conditional knockout approach. RESULTS: Generation of c-mycfl/fl mice carrying the mammary gland-specific WAPiCre transgene resulted in c-Myc loss in alveolar epithelial cells starting in mid-pregnancy. Three major phenotypes were observed in glands of mutant mice. First, c-Myc-deficient alveolar cells had a slower proliferative response at the start of pregnancy, causing a delay but not a block of alveolar development. Second, while milk composition was comparable between wild type and mutant animals, milk production was reduced in mutant glands, leading to slower pup weight-gain. Electron microscopy and polysome fractionation revealed a general decrease in translational efficiency. Furthermore, analysis of mRNA distribution along the polysome gradient demonstrated that this effect was specific for mRNAs whose protein products are involved in milk synthesis. Moreover, quantitative reverse transcription-polymerase chain reaction analysis revealed decreased levels of ribosomal RNAs and ribosomal protein-encoding mRNAs in mutant glands. Third, using the mammary transplantation technique to functionally identify alveolar progenitor cells, we observed that the mutant epithelium has a reduced ability to repopulate the gland when transplanted into NOD/SCID recipients. CONCLUSIONS: We have demonstrated that c-Myc plays multiple roles in the mouse mammary gland during pregnancy and lactation. c-Myc loss delayed, but did not block proliferation and differentiation in pregnancy. During lactation, lower levels of ribosomal RNAs and proteins were present and translation was generally decreased in mutant glands. Finally, the transplantation studies suggest a role for c-Myc in progenitor cell proliferation and/or survival. (In: BMC Biology, 2009, 7:63)

Vogt A, Cholewinski A, Shen X, Nelson SG, Lazo JS, Tsang M, Hukriede NA: Automated image-based phenotypic analysis in zebrafish embryos Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to using the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Definiens Cognition Network Technology. It reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. (In: Developmental Dynamics, March 2009, vol. 238, issue 3, pp. 656-663)

Yu H, Hoppin J, Harlin K, McDonald J, Kuehl P, Anderson T, Lackas C, Gershman B, Candelaria G, Hesterman JY, Norenberg JP: Implementation of a 3D Topographic Thinning Model for Assessing Aerosol Deposition of Radioactive Assays in Small Animal CT/SPECT Imaging Nuclear imaging techniques are often employed to assess the deposition of radiolabeled particles in the lung delivered via nebulizer to both humans and animal models. These imaging studies enable an assessment of the nebulizer properties as well as the lung function of the subject. Both planar and tomographic techniques have been used in such studies and a variety of lung models with relevant segmentation approaches have been used to quantify the properties of the distribution of the labeled particles. This work presents a detailed description of three different topographic thinning or ‘onion model’ approaches used to quantify deposition in SPECT scans of rodent lungs. The techniques developed here were created in conjunction with a large-scale (32 animal) inhalation study looking at the relationship between particle size and deposition. (Poster abstract presented at the Nuclear Science Symposium Medical Imaging Conference, Orlando, Oct 25-31, 2009)

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