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Photon-counting mammography was introduced commercially in 2003 and was the first widely available application of photon-counting detector technology in medical x-ray imaging. Photon-counting detectors are fast enough to register single photon events and can reduce patient dose and enable quantitative imaging.
Basic principle
Photon-counting image receptors are made up of a sensor and electronics. The sensor material is a solid-state semi-conductor (e.g. silicon [31,74,77–80]), which is depleted by a bias voltage. When a photon interacts in the material, charge is released and collected by electrodes on the sensor. The electrodes are in general connected to parallel channels in an application-specific integrated circuit (ASIC) [31,86,89,97–99][92]. Each channel comprises an amplifier and a shaper, which convert the charge to a pulse with a height proportional to the energy of the impinging photon. The pulse height is measured by comparators, generally referred to as energy thresholds, which are followed by corresponding counters. The counters register the sum of all events within a specific energy window and are generally referred to as energy bins. The lower-most threshold is put below the expected incident spectrum to prevent electronic noise from being counted, while still counting all photons.
Fig. 3 shows the basic principle of a photon-counting spectral detector according to the description above.
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Clinical applications
Dose efficiency
Photon-counting mammography allows for a reduction of patient dose while keeping image quality on par with conventional technologies, or, equivalently, improving image quality at equal dose. A study that compared photon-counting mammography to the state-wide average of the North Rhine-Westphalian mammography screening program in Germany reported a slightly improved diagnostic performance at a dose that was 40% of conventional technologies.[1]
Dose reduction in photon-counting mammography compared to energy-integrating detector technologies is mainly enabled by:
- Rejection of electronic noise: A low-energy threshold is put below the expected incident spectrum and prevents electronic noise from being counted.[2] It should be noted, however, that electronic noise will still be added onto the pulse height and to some extent influence the energy resolution.
- Equal weighting of photons: Energy-integrating detectors intrinsically assign a higher weight to high-energy photons because more charge is released in the detector. This weighting is opposite to optimal because low-energy photons carry more contrast information. Photon-counting detectors, on the other hand, intrinsically weigh all photons equally, which is closer to optimal.[3]
- Scatter rejection: The photon-counting mammography system uses a slit-scanning technique; the detector is made up of a number of thin lines and scanned across the object to acquire an image. The detector is equipped with matching pre- and post-patient collimators, which minimizes the acceptance angle while allowing for full detection of primary photons.[4] Anti-scatter grids used for conventional detectors suffer from a trade-off between rejection of scatter and detection of primary photons. It should be noted that a slit-scanning configuration is not intrinsic to photon-counting detectors, but it is often practical to make room for the large amount of electronics.
Energy weighting
Even though equal weighting of photons, intrinsic to photon-counting detectors, improves dose efficiency compared to energy-intergating detectors, a higher weighting of low-energy photons is generally optimal because x-ray contrast drops with increasing photon energy when the photo-electric effect dominates and away from any absorption edges, which holds true for mammography without contrast agents. Photon-counting detectors allow for measuring the energy of impinging photons and therefore enable optimal weighting for a given imaging case. This technique, generally referred to as energy weighting, was pioneered for mammography applications by Cahn et al.[3] At the limit of infinite energy resolution, energy weighting results in a CNR improvement of approximately 10% compared to equal weighting of photons,[3] whereas studies with realistic energy resolution report CNR improvements of a few percent.[5] The first results in clinical application were reported by Berglund et al. who was able to improve the CNR of clinical images by 2.2–5.2%, which translates to a potential dose reduction at a constant CNR in the range of 4.5%–11%.[6]
Spectral imaging
Tomosynthesis
Photon-counting breast tomosynthesis has been developed to a prototype state.[7][8] Tomosynthesis relies on a number of low-dose projections, which makes the influence of electronic noise higher than for conventional mammography, and photon-counting detectors with rejection of electronic noise are therefore beneficial with potentially higher improvements in dose efficiency than for conventional mammography.[9] Further, the slit-scanning technique is expected to provide additional benefit because scatter rejection based on conventional anti-scatter grids is challenging to implement at a range of projection angles.[10] However, slit-scanning tomosynthesis requires larger modifications of existing systems, and the technique has so far not been applied in wide-spread clinical use. Applications of spectral imaging that have been investigated for photon-counting tomosynthesis include breast-density measurement[11] and lesion characterization.[12]
Challenges
The main challenge of photon-counting detectors is pulse pileup [92, 101–103], which occurs when more than one photon interacts in a single detector channel within the time window for pulse detection, the so-called dead time. Pileup results in lost counts and reduced energy resolution because several pulses are counted as one, with a height that is a superposition of the true pulse heights and depends on the time difference between the events. Pileup will always be present in photon-counting detectors because of the Poisson distribution of X-ray photons (two events can occur arbitrarily close in time), but the speed of detector electronics has increased substantially during the past ten years, and acceptable pileup levels at CT count rates are coming within reach [104].
Another challenge ofphoton-counting detectors is cross-talk between adjacent channels, induced, for instance, by fluorescent X-rays or so- called charge sharing, which occurs when charge from a single photon interaction is collected by neighbouring electrodes and therefore de- tected as several events with distributed photon energy [82,90]. Such cross talk can be mitigated by anti-coincidence logic in the ASIC [92], which sorts out pulses in adjacent detector channels within a certain time window. The size of this time window is a compromise between efficiency of the technique and the probability of discriminating against true quasi-coincident events, so called chance coincidence. Chance co- incidence together with increased complexity of the electronics reduces the maximum count rate and increases power consumption, which are the main drawbacks of anti-coincidence logic. Coincident counts may be excluded all together, added to a high-energy bin (because charge sharing occurs with higher probability for high-energy photons) [31], or treated with more advanced schemes that include summation of the pulse height from adjacent detector channels and a probability- based localization of the impulse, such as implemented in the Medipix3 chip [105].
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Detector technologies
Photon-counting image receptors are roughly made up of a sensor and electronics. The sensor material is usually a solid-state semi- conductor, such as silicon [31,74,77–80]. The advantages of silicon include high charge-collection efficiency, ready availability of high- quality high-purity silicon crystals, and established methods for test and assembly driven by the semiconductor industry [81]. The main challenge is the relatively low photo-electric cross section, which limits the the detection efficiency and leads to a large fraction of Compton scatter in the detector. The low detection efficiency is often addressed by arranging the silicon wafers edge on [82,83]. Compton scatter degrades the energy response because the full photon energy is not deposited in a single detector channel and compensation may be necessary, for in- stance, by a separate energy threshold to sort out Compton events [81]. A key characteristic of a photon-counting spectral detector is its energy resolution. The energy resolution of the MicroDose detector ranges from 2.0–2.3 keV standard deviation in the range 20–40 keV, and is shown in Fig. 2(d) for monochromatic impulses at 20 keV, 30 keV, and 40 keV, derived from a fitted detector model [31]. Newer silicon detectors have improved the energy resolution to less than 2 keV in the 40–120 keV interval [78].
Several research groups and commercial companies are investigating cadmium telluride (CdTe) and cadmium–zinc telluride (CZT) as sensor materials for photon-counting CT [27–29,84–87], and for projection imaging [88,89]. The higher atomic number of these materials result in higher absorption and less detector scattering, but, on the other hand, the higher ??-fluorescent yield leads to degraded spectral response and cross-talk between detector elements [90,91]. Also, manufacturing of macro-sized crystals of these materials poses practical challenges, and the crystals generally suffer from lattice defects and impurities that lead to charge trapping. Charge trapping limits the charge-collection efficiency for individual events [90,92], and may also cause long-term polarization effects (build-up of space charge) [93], which reduces energy resolution and detector speed.
Other solid-state materials, such as gallium arsenide [94], and mer- curic iodide [95], are currently quite far from clinical implementation, but may be expanding in the future. Gas detectors have also been investigated [96], but gas is more difficult to handle than solid materials and have limited absorption efficiency.
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References
- ^ Weigel, Stefanie; Berkemeyer, Shoma; Girnus, Ralf; Sommer, Alexander; Lenzen, Horst; Heindel, Walter (2014-01-21). "Digital Mammography Screening with Photon-counting Technique: Can a High Diagnostic Performance Be Realized at Low Mean Glandular Dose?". Radiology. 271 (2): 345–355. doi:10.1148/radiol.13131181. ISSN 0033-8419.
- ^ Fredenberg, Erik; Lundqvist, Mats; Cederström, Björn; Åslund, Magnus; Danielsson, Mats (2010-01-21). "Energy resolution of a photon-counting silicon strip detector". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 613 (1): 156–162. doi:10.1016/j.nima.2009.10.152. ISSN 0168-9002.
- ^ a b c Cahn, R. N.; Cederström, B.; Danielsson, M.; Hall, A.; Lundqvist, M.; Nygren, D. (1999). "Detective quantum efficiency dependence on x-ray energy weighting in mammography". Medical Physics. 26 (12): 2680–2683. doi:10.1118/1.598807. ISSN 2473-4209.
- ^ Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats (2006). "Scatter rejection in multislit digital mammography". Medical Physics. 33 (4): 933–940. doi:10.1118/1.2179122. ISSN 2473-4209.
- ^ Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats (2010-03-18). "Observer model optimization of a spectral mammography system". Medical Imaging 2010: Physics of Medical Imaging. 7622. International Society for Optics and Photonics: 762210. doi:10.1117/12.845480.
- ^ Berglund, Johan; Johansson, Henrik; Lundqvist, Mats; Cederström, Björn; Fredenberg, Erik (2014/08). "Energy weighting improves dose efficiency in clinical practice: implementation on a spectral photon-counting mammography system". Journal of Medical Imaging. 1 (3): 031003. doi:10.1117/1.JMI.1.3.031003. ISSN 2329-4302. PMC 4478791. PMID 26158045.
{{cite journal}}: Check date values in:|date=(help)CS1 maint: PMC format (link) - ^ Berggren, Karl; Cederström, Björn; Lundqvist, Mats; Fredenberg, Erik (2018). "Cascaded systems analysis of shift-variant image quality in slit-scanning breast tomosynthesis". Medical Physics. 45 (10): 4392–4401. doi:10.1002/mp.13116. ISSN 2473-4209.
- ^ Fredenberg, Erik; Lundqvist, Mats; Åslund, Magnus; Hemmendorff, Magnus; Cederström, Björn; Danielsson, Mats (2009-03-13). "A photon-counting detector for dual-energy breast tomosynthesis". Medical Imaging 2009: Physics of Medical Imaging. 7258. International Society for Optics and Photonics: 72581J. doi:10.1117/12.813037.
- ^ Berggren, Karl; Cederström, Björn; Lundqvist, Mats; Fredenberg, Erik (2018). "Characterization of photon-counting multislit breast tomosynthesis". Medical Physics. 45 (2): 549–560. doi:10.1002/mp.12684. ISSN 2473-4209.
- ^ Berggren, Karl; Cederström, Björn; Lundqvist, Mats; Fredenberg, Erik (2018). "Technical Note: Comparison of first- and second-generation photon-counting slit-scanning tomosynthesis systems". Medical Physics. 45 (2): 635–638. doi:10.1002/mp.12735. ISSN 2473-4209.
- ^ Fredenberg, Erik; Berggren, Karl; Bartels, Matthias; Erhard, Klaus (2016). Tingberg, Anders; Lång, Kristina; Timberg, Pontus (eds.). "Volumetric Breast-Density Measurement Using Spectral Photon-Counting Tomosynthesis: First Clinical Results". Breast Imaging. Lecture Notes in Computer Science. Cham: Springer International Publishing: 576–584. doi:10.1007/978-3-319-41546-8_72. ISBN 978-3-319-41546-8.
- ^ Cederström, Björn; Fredenberg, Erik; Berggren, Karl; Erhard, Klaus; Danielsson, Mats; Wallis, Matthew (2017-03-09). "Lesion characterization in spectral photon-counting tomosynthesis". Medical Imaging 2017: Physics of Medical Imaging. 10132. International Society for Optics and Photonics: 1013205. doi:10.1117/12.2253966.