Model observer for optimizing digital breast tomosynthesis for detection of multifocal and multicentric breast cancer

The goal of medical imaging is to acquire and display images of human anatomy and function such that they can be optimally interpreted by a trained observer, e.g., a radiologist. Start-of-art medical image quality is measured by the performance of an observer on a given clinical task. Since psychophysical studies are resource intensive, model observers are widely used as a surrogate in task-based assessment of image quality. Model observers are typically designed to detect at most one abnormality, e.g., a single lesion. However, in clinical practice, there may be multiple abnormalities in a single set of images, which can have a significant impact on treatment planning and outcomes. For example, patients with multifocal and multicentric breast cancer (MFMC), i.e., the presence of two or more tumor foci within the same breast, are more likely to undergo mastectomy rather than breast conservation therapy. Detecting multiple breast tumors is challenging because the prevalence of tumors varies significantly across breast regions, and radiologists do not know the number or location of tumors a priori. The vision of this dissertation is that digital breast tomosynthesis (DBT) has the potential to improve the detection of MFMC, and may offer advantages such as fewer false-positive findings, lower cost, and better accessibility. This dissertation focuses on the design and applications of a model observer to optimize DBT system geometries for detection of multiple breast tumors. This is significant and innovative because prior efforts to optimize DBT image quality only considered unifocal breast cancer scenarios. We highlight the following two main aspects of contributions in this dissertation: (1) We have developed a novel model observer that detects multiple abnormalities in anatomical backgrounds. (2) We have employed the extended 3D multi-lesion model observer to identify DBT system geometries that are most effective for the detection of MFMC. Our results demonstrate that the presence of more than one tumor present distinct challenges to DBT optimization, and that DBT geometries that yield images that are informative for the task of detecting unifocal breast cancer may not necessarily be informative for the task of detecting MFMC. We are validating the clinical relevance of our model observer studies with an ongoing human observer study with experienced breast imaging radiologists.Electrical and Computer Engineerin

Measurement of Tumor Extent and Effects of Breast Compression in Digital Mammography and Breast Tomosynthesis

Breast cancer is the most common form of cancer affecting women in the western countries. Today x-ray digital mammography (DM) of the breast is commonly used for early detection of breast cancer. However, the sensitivity of mammography is limited, mainly due to the fact that a 3D volume is projected down to a 2D image. This problem can be partially solved by a tomographic technique. Breast tomosynthesis (BT) reduces the detrimental effect of the projected anatomy. Tumor size is an important predictor of prognosis and treatment effect. We hypothesized that the tumor outline would be better defined in BT and therefore tumor measurement in BT would be more accurate compared with DM. The results showed that breast tumor size measured on BT correlated better with the size measured by the pathologists on the surgical specimens compared with measurement on DM. Breast compression is important in mammography both to improve image quality and to reduce the radiation dose to the breast, but it also has a negative consequence as some women refrain from mammography due to the pain associated with the examination. Since BT is a 3D technique, it was hypothesized that less breast compression force can be applied. The results indicated that less compression force is possible without significantly compromising the diagnostic quality of the image and that the patient comfort was improved. An applied breast compression force as used in mammography results in a pressure distribution over the breast. The pressure distribution was assessed using thin pressure sensors attached to the compression plate. The results showed that the pressure distribution was heterogeneous in appearance and varied widely between different breasts. In almost half of the subjects most of the pressure was over the juxtathoracic part of the breast and the pectoral muscle with little or no pressure over the rest of the breast. Another concern regarding breast compression is the question whether the resulting pressure might damage tumors, causing a shedding of malignant cells into the blood system. Peripheral venous blood samples were drawn before and after breast compression and analyzed for circulating tumor cells. The study found no elevated number of circulating cancer cells in peripheral blood after breast compression. Future analysis of samples from veins draining the breast are needed to study if circulating tumor cells are being trapped in the lung capillaries

Digital Breast Tomosynthesis : - the future screening tool for breast cancer?

Bakgrunn: Brystkreft er den vanligste kreftformen blant kvinner og en av de hyppigste årsakene til kreftdødsfall i Norge og globalt. Målsettingen med mammografiscreening er å oppdage brystkreft i et tidlig stadium og redusere dødeligheten av sykdommen. Studier har vist høyere deteksjon av screeningoppdagede krefttilfeller med digital brysttomosyntese som inkluderer ~200-250 bilder sammenlignet med standard digital mammografi (DM) med fire bilder. Vi utførte en randomisert kontrollert studie (RCT), Tomosyntese-studien i Bergen (To-Be1). Målsettingen med studien var å sammenligne tidligindikatorer i screening ved bruk av digital brysttomosyntese i kombinasjon med syntetiske 2D-bilder (DBT) versus standard DM. Avhandlingen inkluderer tre studier med følgende mål: Studie 1: Å sammenligne lesetid, stråledose, konsensus og tilbakekalling ved bruk av DBT og DM etter det første året av To-Be1. Studie 2: Å sammenligne tilbakekalling, falske positive screeningsresultater og screeningoppdaget kreft for kvinner med ulik mammografisk tetthet målt automatisk (Volpara tetthetsgrad, VDG 1-4) og med ulike screeningteknikker (DBT versus DM). Studie 3: Å undersøke fordeling av mammografiske funn hos kvinner tilbakekalt etter screening med DBT versus DM og analysere sammenhenger mellom mammografiske funn og det endelige resultatet av screeningundersøkelsen. Metode: Alle kvinner som deltok i screening utført i Bergen i løpet av 2016-2017 som en del av Mammografiprogrammet (n=32 976) ble invitert til å delta i To-Be1. Totalt aksepterte 89,3 % av kvinnene invitasjonen og ble randomisert til DBT eller DM. Etter uavhengig dobbelttyding med konsensus ble resultater etter DBT sammenlignet med DM. Mammografisk tetthet ble oppgitt som VDG 1-4, som er analog til kategoriene i BI-RADS´ 5. utgave. Radiologene klassifiserte mammografiske funn hos etterinnkalte kvinner etter en modifisert BI-RADS skala. Vi brukte deskriptive analyser og t-test for å sammenligne gjennomsnittsverdier, samt kji-kvadrat-test med tilhørende 95% konfidensintervall (KI) for å sammenligne kategorier. Log-binominale regresjonsmodeller ble brukt for å estimere relativ risiko. En p-verdi lavere enn 0,05 ble definert som statistisk signifikant. Vi brukte statistikkprogrammet STATA. Resultater: Studie 1: Gjennomsnittlig lesetid var 1:11 min:sek for DBT og 0:41 min:sek for DM i det første året av To-Be1. Det var ingen statistiske forskjeller i gjennomsnittlig stråledose for noen av tetthetskategoriene for DBT (2,96 mGy) versus DM (2,95 mGy). Tilbakekallingen var 3,0 % for DBT og 3,6 % for DM etter det første året med To-Be1. Studie 2: Etterundersøkelsesraten for kvinner med VDG 1 var 2,1% for DBT og 3,3% for DM, mens den var 3,2% for DBT og 4,3% for DM for de med VDG 2. Raten av falske positive screening resultater var 1,6% for DBT og 2,8% for DM for kvinner med VDG 1. For kvinner med VDG 2 var den 2,4% for DBT og 3,6 for DM. Ingen statistiske forskjeller i screeningoppdaget kreft ble funnet mellom DBT og DM for noen av tetthetskategoriene. Justert relativ risiko for tilbakekalling, falskt positivt screeningsresultat og screeningoppdaget kreft økte med VDG i DBT, mens det ikke ble funnet forskjeller i DM. Studie 3: Studien inkluderte 182 screeningdetekterte krefttilfeller (n=95 for DBT og n=87 for DM). Blant disse var 36,8% spikulerte masser for DBT mens det var 18,4% for DM. Kalk var det hyppigste mammografiske funnet for brystkrefttilfeller for de som var screenet med DM (23%). For DBT var andelen på 13,7%. Asymmetri, uskarp og skjult masse var mindre hyppig hos kvinner med et falsk positiv screening resultat etter screening med DBT versus DM. Konklusjon: Resultater fra To-Be1 indikerte at DBT var minst like god som DM når det gjelder etterundersøkelser og deteksjon av brystkreft, som betyr at DBT er trygt å bruke i screening. DBT var bedre egnet enn DM for kvinner med VDG 1 og 2 med hensyn til etterundersøkelsesrate og falske positive, mens deteksjon av brystkreft ikke var forskjellig. Det tok lengre tid å lese DBT enn DM bilder, og konsensus tok lengre tid med DBT. Mer kunnskap om forskjeller i mammografiske funn og sammenheng med screeningsresultater for DBT versus DM kan bidra til å ytterligere forbedre fordelene med DBT som et screeningverktøy.Background: Breast cancer is the most common cancer and one of the leading causes of cancer deaths in Norway and globally. Mammographic screening aims for early detection of breast cancer and reduced mortality from the disease. Studies have shown higher rates of screen-detected cancers for digital breast tomosynthesis including ~200-250 images compared to standard digital mammography (DM) including four images. We performed a randomized controlled trial (RCT), the Tomosynthesis trial in Bergen (To-Be1), were the aim was to compare early performance measures for digital breast tomosynthesis including synthesised 2D images (DBT) versus DM in screening. This thesis includes three studies with the following aims: Study 1: To compare preliminary results of reading time, radiation dose, consensus and recall for DBT and DM after the first year of To-Be1. Study 2: To compare recall, false positive screening results and screen-detected cancers by automated mammographic density (Volpara density grade, VDG 1-4) and screening technique (DBT versus DM). Study 3: To investigate distribution of mammographic features in women recalled after screening with DBT versus DM and assess associations between mammographic features and final outcome of the screening examination. Method: All women who attended the screening unit in Bergen during 2016-2017 as part of BreastScreen Norway (n=32 976) were invited to participate in To-Be1. In total, 89.3% of the women accepted the invitation and were randomized to undergo either DBT or DM. After independent double reading with consensus, results for DBT were compared with DM. Mammographic density were described by VDG 1-4 which are analogue to the categories in the BI-RADS 5th edition. The radiologists classified the mammographic features of recalled women according to a modified BI-RADS scale. We presented descriptive results and used t-tests to test for means, and chi-squared tests for categories with corresponding 95% confidence intervals (CI). Log-binominal regression models were used to estimate relative risks. A p-value lower than 0.05 was defined as statistically significant. We used STATA software. Results: Study 1: Mean reading time was 1:11 min:sec for DBT versus 0:41 min:sec for DM in the first year of To-Be1. Mean glandular dose did not differ statistically for women screened with DBT (2.96 mGy) versus DM (2.95 mGy). Recall was 3.0% for DBT and 3.6% for DM in the first year of To-Be1. Study 2: Recall rate for women with VDG 1 was 2.1% for DBT and 3.3% for DM, while it was 3.2% for DBT and 4.3% for DM for women with VDG 2. The rate of false positive screening results was 1.6% for DBT and 2.8% for DM for women with VDG 1. For women with VDG 2 it was 2.4% for DBT and 3.6% for DM. No statistical difference in screen-detected cancers was observed between DBT and DM in any density categories. Adjusted relative risk of recall, false positives and screen-detected cancers increased with VDG for DBT. No difference was found for DM. Study 3: The study included 182 screen detected cancers (n=95 DBT and n= 87 DM). 36.8% of those detected with DBT was spiculated mass, while it was 18.4 % for DM. Calcifications was the most frequent feature for breast cancer among those screened with DM (23.0%), which did not differ statistically from the 13.7% for DBT. Asymmetry, indistinct and obscured mass was less frequent in women with a false positive screening result after screening with DBT versus DM. Conclusion: Results from To-Be1 indicated DBT to be as least as good as DM in terms of recall and cancer detection, which means that DBT is safe for the women. DBT was superior to DM in women with VDG 1 and 2 (lower recall, fewer false positives, no difference in cancer detection). However, time spent on initial screen reading and on consensus was longer for DBT compared with DM. More knowledge of the differences in distribution of mammographic features and their association with screening outcome, might contribute to further improve the benefits of DBT as a screening tool for breast cancer.Doktorgradsavhandlin

The impact of simulated motion blur on breast cancer detection performance in full field digital mammography (FFDM)

Objective: Full-field Digital Mammography (FFDM) is employed in breast screening for the early detection of breast cancer. High quality, artefact free, diagnostic images are crucial to the accuracy of this process. Unwanted motion during the image acquisition phase and subsequent image blurring is an unfortunate occurrence in some FFDM images. The research detailed in this thesis seeks to understand the impact of motion blur on cancer detection performance in FFDM images using novel software to perform simulation of motion, an observer study to measure the lesion detection performance and physical measures to assess the impact of simulated motion blur on image characteristics of the lesions. Method: Seven observers (15±5 years’ reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for three conditions: no motion blur (0.0 mm) and two magnitudes of simulated motion blur (0.7 mm and 1.5 mm). Abnormal cases were biopsy proven. A free-response observer study was conducted to compare lesion detection performance for the three conditions. Equally weighted jackknife alternative free-response receiver operating characteristic (wJAFROC) was used as the figure of merit. A secondary analysis of data was deemed important to simulate ‘double reporting’. In this secondary analysis, six of the observers are combined with the seventh observer to evaluate the impact of combined free-response data for lesion detection and to assess if combined two observers data could reduce the impact of simulated motion blur on detection performance. To compliment this, the physical characteristics of the lesions were obtained under the three conditions in order to assess any change in characteristics of the lesions when blur is present in the image. The impact of simulated motion blur on physical characteristics of malignant masses was assessed using a conspicuity index; for microcalcifications, a new novel metric, known as dispersion index, was used. Results: wJAFROC analysis found a statistically significant difference in lesion detection performance for both masses (F (2,22) = 6.01, P=0.0084) and microcalcifications (F(2,49) = 23.14, P<0.0001). For both lesion types, the figure of merit reduced as the magnitude of simulated motion blur increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0mm v 0.7mm, and 0.0mm v 1.5mm) and all pairs for microcalcifications (0.0 mm v 0.7 mm, 0.0 mm v 1.5 mm, and 0.7 mm v 1.5 mm). No difference was detected between 0.7 mm and 1.5 mm for masses. For combined two observers’ data of masses, there was no statistically significant difference between single and combined free-response data for masses (F(1,6) = 4.04, p=0.1001, -0.031 (-0.070, 0.008) [treatment difference (95% CI)]. For combined data of microcalcifications, there was a statistically significant difference between single and combined free-response data (F(1,6) = 12.28, p=0.0122, -0.056 (-0.095, -0.017) [treatment difference (95% CI)]. Regarding the physical measures of masses, conspicuity index increases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=-6.158 (p<0.000); 0.0–1.5 mm t(22)=-6.273 (p<0.000); and 0.7–1.5 mm (t(22)=-6.231 (p<0.000). Lesion edge angle decreases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=3.232 (p<0.004); for 0.0–1.5 mm t(22)=6.592 (p<0.000); and 0.7–1.5mm t(22)=2.234 (p<0.036). For the grey level change there was no statistically significant difference as simulated motion blur increases to 0.7 and then to 1.5mm. For image noise there was a statistically significant difference, where noise reduced as simulated motion blur increased: 0.0–0.7 mm t(22)=22.95 (p<0.000); 0.0–1.5mm t(22)=24.66 (p<0.000); 0.7–1.5 mm t(22)=18.11 (p<0.000). For microcalcifications, simulated motion blur had a negative impact on the ‘dispersion index’. Conclusion: Mathematical simulations of motion blur resulted in a statistically significant reduction in lesion detection performance. This reduction in performance could have implications for clinical practice. Simulated motion blur has a negative impact on the edge angle of breast masses and a negative impact on the image characteristics of microcalcifications. These changes in the image lesion characteristics appear to have a negative effect on the visual identification of breast cancer

4D Digital Breast Phantom for Contrast-Enhanced Imaging

A fully simulated 4D digital breast phantom model is developed inthis work. The model is based on an anthropomorphic digital breast 3D phantom, which gives the user better control of the 4D phan- tom features when it comes to developing and optimizing contrast enhancement imaging techniques. The fourth dimension of the phan- tom features different time-varying enhancement patterns for differ- ent materials including fibro glandular tissue and mass tissue. Phys- iological parameters that capture the key characteristics of different types of masses, for example, wash-in and wash-=out rates indicating metabolism level, are employed in the model to simulate certain fun- damental features for categorizing mass types. A two-compartment model, a well-known model in the field of Pharmacokinetics, is used to depict the diffusion process of the contrast agent. Two methods are proposed to allow the simulation of the necrotic core with varying shapes. To explore the benefit of the 4D phantom, digital mammograms are simulated and studied by the Monte Carlo method. To perform the simulation, the contrast agent blood tissue mixture’s cross-section pa- rameters are generated by linear interpolation between the parameters of blood, contrast agent, and tissue (mass or fibro glandular tissue). With the contrast agent in the tissue, higher contrast is achieved be- tween fibro glandular tissue and mass tissue. The contrast is then further enhanced by the log scale subtraction between high and low- energy mammograms