Multi-pinhole Molecular Breast Tomosynthesis: from Simulation to Prototype

Beien Wang

Research output: ThesisDissertation (TU Delft)

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Breast cancer, being the most common cancer among females, is nowadays routinely diagnosed using X-ray mammography. Though this technique has proven its effectiveness in many cases, X-ray mammography has some disadvantages like reduced diagnostic sensitivity for dense breasts, need for strong breast compression and inability to assess tissues at the molecular level. 
Therefore, there is a need for alternative imaging modalities to improve breast cancer diagnosis. One option is breast scintigraphy, which images the distribution of radiolabelled molecules, called tracers, that concentrate in the tumours in breasts with a planar gamma detector. Different tracers react in different physiological processes with tumours. Therefore imaging a specific tracer can reveal the specific pathological process that is specific for a certain kind of breast tumour. Despite the fact that breast scintigraphy has been reported to have improved diagnostic sensitivity in dense breasts compared to X-ray mammography and does not require strong compression, it offers only 2D images and information on the third dimension is thus lost. In this research we proposed a molecular breast tomosynthesis scanner which provides 3D images of the radiotracers in the breast. In the proposed system, the patient would lie prone on a patient bed with a hole in which the breast is inserted. Subsequently, two gamma cameras equipped with multi-pinhole collimators (therefore the technique is called multi-pinhole molecular breast tomosynthesis, MP-MBT) scan the pendant breast from both sides. 
To estimate the performance of MP-MBT, the system was modelled in Monte Carlo simulations in a clinically realistic setting. The results assured us that it was worth building a prototype of MP-MBT to further investigate its imaging capability. Besides, voxelized raytracing (VRT) software developed earlier in our group to accelerate simulations and facilitate system optimisations was validated with the Monte Carlo simulation results. Subsequently, VRT was used in further studies in this project. 
The promising results of MP-MBT simulations partly relied on a gamma detector with high spatial linearity over the whole detector surface. However, conventional gamma detectors used in clinical practice have large dead edges, i.e. about 4 cm from the detector edges is unusable, and a detector with small dead edges would be very expensive, which may make MP-MBT a less competitive technology. Therefore, in order to have a gamma detector suitable for MP-MBT, we came up with a few different designs with NaI(Tl) scintillators and photomultiplier tube (PMT) array readouts and evaluated their performances with Monte Carlo simulations. From the simulation results, we eventually chose a design with a staggered layout of 15 square PMTs, among which two PMTs detected the optical photons from the scintillator through extra-long additional light-guides. This gamma detector was built in our lab, and it turned out to have only about 15 mm dead edge (mainly due to the 12 mm sealing). 
The customised gamma detector was equipped with a lead multi-pinhole collimator design based on previous research. The whole gamma camera was mounted on a robot arm to create a movable scanner. We calibrated the scanner with a point source and scanned a resolution phantom and a breast phantom to evaluate MP-MBT's performance. In the phantom study, the scanner showed the capability of detecting tumours down to 5 mm when a realistic tracer (technetium sestamibi) concentration was administered. 
However, the current prototype is still far from a device that can be used in the clinic and we have found several problems with MP-MBT, especially the noise pattern in the reconstructed images, which should be given special attention in the future research.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • Beekman, F.J., Supervisor
  • Goorden, M.C., Supervisor
Award date19 May 2020
Print ISBNs9789463662734
Publication statusPublished - 19 May 2020


  • pinhole collimator
  • gamma detector
  • Monte Carlo simulation
  • breast imaging
  • SPECT imaging
  • molecular imaging


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