| 1. |
- Dustler, Magnus, et al.
(författare)
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The characteristics of malignant breast tumors imaged using a prototype mechanical imaging system as an adjunct to mammography
- 2016
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Ingår i: Breast Imaging : 13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings - 13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783319415451 - 9783319415468 ; 9699, s. 282-288
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Konferensbidrag (refereegranskat)abstract
- Breast cancer is diagnosed by a combination of modalities. Measuring the elasto-mechanical properties of suspicious lesions, by e.g. ultrasound elastography, can help differentiate malignant from benign findings. Using a prototype Mechanical Imaging (MI) system as an adjunct to mammography, the aim of this study was to characterize tumors using MI and compare the readings to those from the contralateral breast. Thirteen bilateral MI sets from women with malignant breast lesions were included in this study, drawn from a larger set of 155 women recalled from screening. The results showed that mean lesion pressure was significantly greater than the mean pressure of the corresponding breast, 7.5 ± 7.0 kPa compared to 2.5 ± 1.6 kPa (P = 0.01). There was no evidence for a difference in mean pressure or standard deviation of the MI image between symptomatic and contralateral asymptomatic breasts (P = 0.24 and 0.68). The results support that it is possible to use MI to distinguish malignant cancers from normal breast tissue. Still, further investigations of the characteristics of benign lesions are necessary to ascertain the usefulness of the system.
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| 2. |
- Tingberg, Anders, et al.
(författare)
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Preface
- 2016
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Ingår i: Breast Imaging : 13th International Workshop, IWDM 2016 Malmö, Sweden, June 19 – 22, 2016 - 13th International Workshop, IWDM 2016 Malmö, Sweden, June 19 – 22, 2016. - Cham : Springer International Publishing. - 0302-9743. - 9783319415451 - 9783319415468 ; 9699
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Tingberg, Anders
(författare)
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Quantifying the quality of medical x-ray images. An evaluation based on normal anatomy for lumbar spine and chest radiography.
- 2000
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Optimisation in diagnostic radiology requires accurate methods for determination of patient absorbed dose and clinical image quality. Simple methods for evaluation of clinical image quality are at present scarce and this project aims at developing such methods. Two methods are used and further developed; fulfilment of image criteria (IC) and visual grading analysis (VGA). Clinical image quality descriptors are defined based on these two methods: image criteria score (ICS) and visual grading analysis score (VGAS), respectively. For both methods the basis is the Image Criteria of the “European Guidelines on Quality Criteria for Diagnostic Radiographic Images”. Both methods have proved to be useful for evaluation of clinical image quality. The two methods complement each other: IC is an absolute method, which means that the quality of images of different patients and produced with different radiographic tech-niques can be compared with each other. The separating power of IC is, however, weaker than that of VGA. VGA is the best method for comparing images produced with different radiographic techniques and has strong separating power, but the re-sults are relative, since the quality of an image is compared to the quality of a refer-ence image. The usefulness of the two methods has been verified by comparing the results from both of them with results from a generally accepted method for evaluation of clinical image quality, receiver operating characteristics (ROC). The results of the comparison between the two methods based on visibility of anatomical structures and the method based on detection of pathological structures (free-response forced error) indicate that the former two methods can be used for evaluation of clinical image quality as efficiently as the method based on ROC. More studies are, however, needed for us to be able to draw a general conclusion, including studies of other organs, using other radiographic techniques, etc. The results of the experimental evaluation of clinical image quality are compared with physical quantities calculated with a theoretical model based on a voxel phantom, and correlations are found. The results demonstrate that the computer model can be a useful tool in planning further experimental studies.
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| 4. |
- Jensen, Kristin, et al.
(författare)
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Quantitative Measurements Versus Receiver Operating Characteristics and Visual Grading Regression in CT Images Reconstructed with Iterative Reconstruction : A Phantom Study
- 2018
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Ingår i: Academic Radiology. - : ELSEVIER SCIENCE INC. - 1076-6332 .- 1878-4046. ; 25:4, s. 509-518
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Tidskriftsartikel (refereegranskat)abstract
- Rationale and Objectives: This study aimed to evaluate the correlation of quantitative measurements with visual grading regression (VGR) and receiver operating characteristics (ROC) analysis in computed tomography (CT) images reconstructed with iterative reconstruction. Materials and Methods: CT scans on a liver phantom were performed on CT scanners from GE, Philips, and Toshiba at three dose levels. Images were reconstructed with filtered back projection (FBP) and hybrid iterative techniques (ASiR, iDose, and AIDR 3D of different strengths). Images were visually assessed by five readers using a four- and five-grade ordinal scale for liver low contrast lesions and for 10 image quality criteria. The results were analyzed with ROC and VGR. Standard deviation, signal-to-noise ratios, and contrast to-noise ratios were measured in the images. Results: All data were compared to FBP. The results of the quantitative measurements were improved for all algorithms. ROC analysis showed improved lesion detection with ASiR and AIDR and decreased lesion detection with iDose. VGR found improved noise properties for all algorithms, increased sharpness with iDose and AIDR, and decreased artifacts from the spine with AIDR, whereas iDose increased the artifacts from the spine. The contrast in the spine decreased with ASiR and iDose. Conclusions: Improved quantitative measurements in images reconstructed with iterative reconstruction compared to FBP are not equivalent to improved diagnostic image accuracy.
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| 5. |
- Sandborg, Michael, 1961-, et al.
(författare)
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Demonstration of correlation between physical and clinical image quality measures in chest and lumbar spine imaging.
- 2000
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Ingår i: Digest of papers of the 2000 world congress on medical physics. CD-Rom Chicago July 23-28,2000. - : IEEE. - 0780364651 ; , s. 3078-3081 vol.4
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Konferensbidrag (refereegranskat)abstract
- Clinical and physical assessments of image quality are compared and the correlation between the two derived. Clinical assessment has been made by a group of expert radiologists who evaluated the fulfillment of the European Image Criteria for chest and lumbar spine radiography; yielding the so-called Image Criteria Score, ICS. Physical measures of image quality were calculated using a Monte Carlo model of the complete imaging system. This model includes a voxelised male anatomy and calculates contrast and signal-to-noise ratio of various anatomical details and a measure of useful dynamic range. Correlations between the ICS and the physical image quality measures were sought. Four lumbar spine and 16 chest imaging systems were evaluated and simulated with the model. The most useful physical quantities for chest radiography were the dynamic range and contrast of blood vessels in the retro-cardiac area. In lumbar spine, it was the signal-to-noise ratio of trabecular structures. The significant correlation is encouraging and shows that clinical image quality can be predicted provided the imaging conditions are well known and that relevant measures of physical image quality are used to assess the quality of the image
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| 6. |
- Sandborg, Michael, 1961-, et al.
(författare)
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Demonstration of correlations between clinical and physical image quality measures in chest and lumbar spine screen-film radiography
- 2001
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Ingår i: British Journal of Radiology. - : British Institute of Radiology. - 0007-1285 .- 1748-880X. ; 74:882, s. 520-528
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Tidskriftsartikel (refereegranskat)abstract
- The ability to predict clinical image quality from physical measures is useful for optimization in diagnostic radiology. In this work, clinical and physical assessments of image quality are compared and correlations between the two are derived. Clinical assessment has been made by a group of expert radiologists who evaluated fulfilment of the European image criteria for chest and lumbar spine radiography using two scoring methods: image criteria score (ICS) and visual grading analysis score (VGAS). Physical image quality measures were calculated using a Monte Carlo simulation model of the complete imaging system. This model includes a voxelized male anatomy and was used to calculate contrast and signal-to-noise ratio of various important anatomical details and measures of dynamic range. Correlations between the physical image quality measures on the one hand and the ICS and VGAS on the other were sought. 16 chest and 4 lumbar spine imaging system configurations were compared in frontal projection. A statistically significant correlation with clinical image quality was found in chest posteroanterior radiography for the contrast of blood vessels in the retrocardiac area and a measure of useful dynamic range. In lumbar spine anteroposterior radiography, a similar significant correlation with clinical image quality was found between the contrast and signal-to-noise ratio of the trabecular structures in the L1-L5 vertebrae. The significant correlation shows that clinical image quality can, at least in some cases, be predicted from appropriate measures of physical image quality.
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| 7. |
- Axelsson, Rebecca, et al.
(författare)
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Computer model of mechanical imaging acquisition for virtual clinical trials
- 2021
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Ingår i: Medical Imaging 2021 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE. - 1605-7422. - 9781510640191 ; 11595, s. 1-115950
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Konferensbidrag (refereegranskat)abstract
- Malignant breast tumours can be distinguished from benign lesions and normal tissue based on their mechanical properties. Our pilot studies have demonstrated the potential of using Mechanical Imaging (MI) combined with mammography to reduce recalls and false positives in breast cancer screening by more accurately identifying benign lesions. To enable further optimization of MI we propose a computer simulation of the MI acquisition, for use in a Virtual Clinical Trial (VCT) framework. VCTs are computer simulated clinical trials used to efficiently evaluate clinical imaging systems. A linear elastic finite element (FE) model of the breast under dynamic compression was implemented using an open-source FE solver. A spherical tumour (15 mm in diameter) was inserted into the simulated predominantly adipose breast. The location and stiffness of the tumour was varied. The average stress on the compressed breast surface was calculated and compared with the local average stress at the tumour location and the Relative Mean Pressure over lesion Area (RMPA) was calculated. Preliminary results were within a realistic range with an average stress on the breast (tumour) of 5.9-16.6 kPa which is in agreement with published values between 1.0 - 22.5 kPa. This corresponds to RMPA values of 0.96-2.15 depending on stiffness and location of the tumour. This can lead to more detailed validation of various MI acquisition schemes through VCTs before their use in clinical studies.
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| 8. |
- Barufaldi, Bruno, et al.
(författare)
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Virtual Clinical Trials in Medical Imaging System Evaluation and Optimisation
- 2021
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Ingår i: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 1742-3406 .- 0144-8420. ; 195:3-4, s. 363-371
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Tidskriftsartikel (refereegranskat)abstract
- Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.
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| 9. |
- Dahlblom, Victor, et al.
(författare)
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Breast cancer screening with digital breast tomosynthesis : comparison of different reading strategies implementing artificial intelligence
- 2023
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 33:5, s. 3754-3765
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Digital breast tomosynthesis (DBT) can detect more cancers than the current standard breast screening method, digital mammography (DM); however, it can substantially increase the reading workload and thus hinder implementation in screening. Artificial intelligence (AI) might be a solution. The aim of this study was to retrospectively test different ways of using AI in a screening workflow.METHODS: An AI system was used to analyse 14,772 double-read single-view DBT examinations from a screening trial with paired DM double reading. Three scenarios were studied: if AI can identify normal cases that can be excluded from human reading; if AI can replace the second reader; if AI can replace both readers. The number of detected cancers and false positives was compared with DM or DBT double reading.RESULTS: By excluding normal cases and only reading 50.5% (7460/14,772) of all examinations, 95% (121/127) of the DBT double reading detected cancers could be detected. Compared to DM screening, 27% (26/95) more cancers could be detected (p < 0.001) while keeping recall rates at the same level. With AI replacing the second reader, 95% (120/127) of the DBT double reading detected cancers could be detected-26% (25/95) more than DM screening (p < 0.001)-while increasing recall rates by 53%. AI alone with DBT has a sensitivity similar to DM double reading (p = 0.689).CONCLUSION: AI can open up possibilities for implementing DBT screening and detecting more cancers with the total reading workload unchanged. Considering the potential legal and psychological implications, replacing the second reader with AI would probably be most the feasible approach.KEY POINTS: • Breast cancer screening with digital breast tomosynthesis and artificial intelligence can detect more cancers than mammography screening without increasing screen-reading workload. • Artificial intelligence can either exclude low-risk cases from double reading or replace the second reader. • Retrospective study based on paired mammography and digital breast tomosynthesis screening data.
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| 10. |
- Dahlblom, Victor, et al.
(författare)
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Malmö Breast ImaginG database: objectives and development
- 2023
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Ingår i: Journal of Medical Imaging. - 2329-4302. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- PurposeWe describe the design and implementation of the Malmö Breast ImaginG (M-BIG) database, which will support research projects investigating various aspects of current and future breast cancer screening programs. Specifically, M-BIG will provide clinical data to: 1. investigate the effect of breast cancer screening on breast cancer prognosis and mortality; 2. develop and validate the use of artificial intelligence and machine learning in breast image interpretation; and 3. develop and validate image-based radiological breast cancer risk profiles.ApproachThe M-BIG database is intended to include a wide range of digital mammography (DM) and digital breast tomosynthesis (DBT) examinations performed on women at the Mammography Clinic in Malmö, Sweden, from the introduction of DM in 2004 through 2020. Subjects may be included multiple times and for diverse reasons. The image data are linked to extensive clinical, diagnostic, and demographic data from several registries.ResultsTo date, the database contains a total of 451,054 examinations from 104,791 women. During the inclusion period, 95,258 unique women were screened. A total of 19,968 examinations were performed using DBT, whereas the rest used DM.ConclusionsWe describe the design and implementation of the M-BIG database as a representative and accessible medical image database linked to various types of medical data. Work is ongoing to add features and curate the existing data.
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