| 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. |
- Timberg, Pontus, et al.
(författare)
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Breast density assessment using breast tomosynthesis images
- 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. 197-202
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Konferensbidrag (refereegranskat)abstract
- In this work we evaluate an approach for breast density assessment of digital breast tomosynthesis (DBT) data using the central projection image. A total of 348 random cases (both FFDM CC and MLO views and DBT MLO views) were collected using a Siemens Mammomat Inspiration tomosynthesis unit at Unilabs, Malmö. The cases underwent both BI-RADS 5th Edition labeling by radiologists and automated volumetric breast density analysis (VBDA) by an algorithm. Preliminary results showed an observed agreement of 70% (weighted Kappa, κ = 0.73) between radiologists and VBDA using FFDM images and 63% (κ = 0.62) for radiologists and VBDA using DBT images. Comparison between densities for FFDM and DBT resulted in high correlation (r = 0.94) and an observed agreement of 72% (κ = 0.76). The automated analysis is a promising approach using low dose central projection DBT images in order to get radiologist- like density ratings similar to results obtained from FFDM.
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| 3. |
- Ba, Alexandre, et al.
(författare)
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Inter-laboratory comparison of channelized hotelling observer computation
- 2018
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Ingår i: Medical Physics. - : Wiley. - 0094-2405 .- 2473-4209. ; 45:7, s. 3019-3030
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The task-based assessment of image quality using model observers is increasingly used for the assessment of different imaging modalities. However, the performance computation of model observers needs standardization as well as a well-established trust in its implementation methodology and uncertainty estimation. The purpose of this work was to determine the degree of equivalence of the channelized Hotelling observer performance and uncertainty estimation using an intercomparison exercise. Materials and Methods: Image samples to estimate model observer performance for detection tasks were generated from two-dimensional CT image slices of a uniform water phantom. A common set of images was sent to participating laboratories to perform and document the following tasks: (a) estimate the detectability index of a well-defined CHO and its uncertainty in three conditions involving different sized targets all at the same dose, and (b) apply this CHO to an image set where ground truth was unknown to participants (lower image dose). In addition, and on an optional basis, we asked the participating laboratories to (c) estimate the performance of real human observers from a psychophysical experiment of their choice. Each of the 13 participating laboratories was confidentially assigned a participant number and image sets could be downloaded through a secure server. Results were distributed with each participant recognizable by its number and then each laboratory was able to modify their results with justification as model observer calculation are not yet a routine and potentially error prone. Results: Detectability index increased with signal size for all participants and was very consistent for 6 mm sized target while showing higher variability for 8 and 10 mm sized target. There was one order of magnitude between the lowest and the largest uncertainty estimation. Conclusions: This intercomparison helped define the state of the art of model observer performance computation and with thirteen participants, reflects openness and trust within the medical imaging community. The performance of a CHO with explicitly defined channels and a relatively large number of test images was consistently estimated by all participants. In contrast, the paper demonstrates that there is no agreement on estimating the variance of detectability in the training and testing setting.
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| 4. |
- Bakic, Predrag R., et al.
(författare)
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Artifact reduction in simultaneous tomosynthesis and mechanical imaging of the breast
- 2019
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Ingår i: Medical Imaging 2019 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE. - 9781510625433 ; 10948
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Konferensbidrag (refereegranskat)abstract
- Mechanical imaging (MI) uses a pressure sensor array to estimate the stiffness of lesions. Recent clinical studies have suggested that MI combined with digital mammography may reduce false positive findings and negative biopsies by over 30%. Digital breast tomosynthesis (DBT) has been adopted progressively in cancer screening. The tomographic nature of DBT improves lesion visibility by reducing tissue overlap in reconstructed images. For maximum benefit, DBT and MI data should be acquired simultaneously; however, that arrangement produces visible artifacts in DBT images due to the presence of the MI sensor array. We propose a method for reducing artifacts during the DBT image reconstruction. We modified the parameters of a commercial DBT reconstruction engine and investigated the conspicuity of artifacts in the resultant images produced with different sensor orientations. The method was evaluated using a physical anthropomorphic phantom imaged on top of the sensor. Visual assessment showed a reduction of artifacts. In a quantitative test, we calculated the artifact spread function (ASF), and compared the ratio of the mean ASF values between the proposed and conventional reconstruction (termed ASF ratio, RASF). We obtained a mean RASF of 2.74, averaged between two analyzed sensor orientations (45° and 90°). The performance varied with the orientation and the type of sensor structures causing the artifacts. RASF for wide connection lines was larger at 45° than at 90° (5.15 vs. 1.00, respectively), while for metallic contacts RASF was larger at 90° than at 45° (3.31 vs. 2.21, respectively). Future work will include a detailed quantitative assessment, and further method optimization in virtual clinical trials.
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| 5. |
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| 6. |
- Diaz, Ivan, et al.
(författare)
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Derivation of an Observer Model Adapted to Irregular Signals Based on Convolution Channels
- 2015
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Ingår i: IEEE Transactions on Medical Imaging. - 1558-254X. ; 34:7, s. 1428-1435
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Tidskriftsartikel (refereegranskat)abstract
- Anthropomorphic model observers are mathe-matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.
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| 7. |
- Dustler, Magnus, et al.
(författare)
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Application of the fractal Perlin noise algorithm for the generation of simulated breast tissue
- 2015
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Ingår i: Medical Imaging 2015: Physics of Medical Imaging. - : SPIE. - 1996-756X .- 0277-786X. ; 9412, s. 94123-94123
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Konferensbidrag (refereegranskat)abstract
- Software breast phantoms are increasingly seeing use in preclinical validation of breast image acquisition systems and image analysis methods. Phantom realism has been proven sufficient for numerous specific validation tasks. A challenge is the generation of suitably realistic small-scale breast structures that could further improve the quality of phantom images. Power law noise follows the noise power characteristics of breast tissue, but may not sufficiently represent certain (e.g., non-Gaussian) properties seen in clinical breast images. The purpose of this work was to investigate the utility of fractal Perlin noise in generating more realistic breast tissue through investigation of its power spectrum and visual characteristics. Perlin noise is an algorithm that creates smoothly varying random structures of an arbitrary frequency. Through the use of a technique known as fractal noise or fractional Brownian motion (fBm), octaves of noise with different frequency are combined to generate coherent noise with a broad frequency range. fBm is controlled by two parameters - lacunarity and persistence - related to the frequency and amplitude of successive octaves, respectively. Average noise power spectra were calculated and beta parameters estimated in sample volumes of fractal Perlin noise with different combinations of lacunarity and persistence. Certain combinations of parameters resulted in noise volumes with beta values between 2 and 3, corresponding to reported measurements in real breast tissue. Different combinations of parameters resulted in different visual appearances. In conclusion, Perlin noise offers a flexible tool for generating breast tissue with realistic properties.
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| 8. |
- Dustler, Magnus, et al.
(författare)
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Can mechanical imaging increase the specificity of mammography screening?
- 2017
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 27:8, s. 3217-3225
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: This study aimed to investigate the effects of adding adjunct mechanical imaging to mammography breast screening. We hypothesized that mechanical imaging could detect increased local pressure caused by both malignant and benign breast lesions and that a pressure threshold for malignancy could be established. The impact of this on breast screening was investigated with regard to reductions in recall and biopsy rates. Methods: 155 women recalled from breast screening were included in the study, which was approved by the regional ethical review board (dnr 2013/620). Mechanical imaging readings were acquired of the symptomatic breast. The relative mean pressure on the suspicious area (RMPA) was defined and a threshold for malignancy was established. Results: Biopsy-proven invasive cancers had a median RMPA of 3.0 (interquartile range (IQR) = 3.7), significantly different from biopsy-proven benign at 1.3 (IQR = 1.0) and non-biopsied cases at 1.0 (IQR = 1.3) (P < 0.001). The lowest RMPA for invasive cancer was 1.4, with 23 biopsy-proven benign and 33 non-biopsied cases being below this limit. Had these women not been recalled, recall rates would have been reduced by 36% and biopsy rates by 32%. Conclusions: If implemented in a screening situation, this may substantially lower the number of false positives. Key Points: • Mechanical imaging is used as an adjunct to mammography in breast screening.• A threshold pressure can be established for malignant breast cancer.• Recalls and biopsies can be substantially reduced.
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| 9. |
- Dustler, Magnus, et al.
(författare)
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VOLUMETRIC LOCALISATION OF DENSE BREAST TISSUE USING BREAST TOMOSYNTHESIS DATA.
- 2016
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Ingår i: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 1742-3406 .- 0144-8420.
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Tidskriftsartikel (refereegranskat)abstract
- This study attempted to use combined data from reconstructed digital breast tomosynthesis (DBT) volumes and density estimation of projection images to localise dense tissue inside the breast, using the assumption that the breast can be treated as consisting of only two types of tissue: fibroglandular (dense) and adipose (fatty). To be able to verify results, software breast phantoms generated using fractal Perlin noise were employed. Projection images were created using the PENELOPE Monte Carlo package. Dense tissue volume was estimated from the central projection image. The density image was used to determine the number of dense voxels at each pixel location, which were then placed using the DBT image as a template. The method proved capable of accurately determining the composition of 75±5 % of voxels.
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| 10. |
- Förnvik, Daniel, et al.
(författare)
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ESTIMATES OF BREAST CANCER GROWTH RATE FROM MAMMOGRAMS AND ITS RELATION TO TUMOUR CHARACTERISTICS.
- 2016
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Ingår i: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 1742-3406 .- 0144-8420. ; 169, s. 151-157
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to investigate the growth rate of 31 consecutive invasive breast cancers based on volume measures on at least two serial mammograms and its relation to histopathological findings. The average tumour volume-doubling time in all invasive breast cancer subtypes was 282 d (range 46-749 d). Grade III breast cancers had a significantly shorter average tumour volume-doubling time of 105 d (range 46-157 d) compared with Grade I and II tumours (average of 296 d, range 147-531 d and average of 353 d, range 139-749 d, respectively) (p = 0.002). Multiple linear regression identified that tumour volume-doubling time was positively associated with patient age, histological grade and progesterone receptor expression and inversely associated with axillary lymph node involvement, human epidermal growth factor receptor 2 and Ki-67 expression (p < 0.001). In conclusion, tumour volume-doubling time as estimated on serial mammography may provide important prognostic information relevant for clinical decision-making.
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