Characterization of the Detection Module of the INSERT SPECT/MRI Clinical System

Occhipinti, Michele; Carminati, Marco; Busca, P.; Butt, Arslan Dawood; Montagnani, G. L.; Trigilio, Paolo; Piemonte, C.; Ferri, Alessandro; Gola, A.; Bükki, Tamás; Czeller, M.; Nyitrai, Z.; Papp, Z.; Nagy, Kálmán; Fiorini, C.

doi:10.1109/trpms.2018.2864792

Cited by 20 publications

(19 citation statements)

References 38 publications

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“…7. The planar spatial resolution here obtained is consistent with intrinsic spatial resolution of the module (~1 mm, [11]) and with the collimator minification (~8, [9]). The tomographic reconstruction of the capillaries, shows an average extrinsic resolution of about 8 mm [6][7], thus matching the target of 10 mm.…”

Section: Spatial Resolutionsupporting

confidence: 85%

“…The average energy resolution is ~17% at 140 keV. It is worse than previous measurements [11]. The large variability among the modules suggests that there might be a deterioration of the crystal, of the optical resin or of the SiPMs.…”

Section: B Energy Resolutionmentioning

confidence: 58%

“…The detection modules [11], all the electronics and the RF coils have been already individually characterized, especially in terms of mutual compatibility with MRI [12]. However, the W Fig.…”

Section: Instrument Designmentioning

confidence: 99%

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A SiPM-Based Clinical MRI-Compatible SPECT Insert

Carminati

D’Adda

Morahan

et al. 2019

2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

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Section: Spatial Resolutionsupporting

confidence: 85%

Section: B Energy Resolutionmentioning

confidence: 58%

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A SiPM-Based Clinical MRI-Compatible SPECT Insert

Carminati

D’Adda

Morahan

et al. 2019

2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

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“…Complex collimator designs, such as multiple pin-hole [52] and slit-slat collimators [63], could also bring sensitivity gains while maintaining acceptable spatial resolution. Such efforts could be matched with improvements to intrinsic spatial resolution and semi-conductor readout [64]. While complex collimator designs are an area of interest, whether this technology can be extended to larger fields-of-view rather than small field-of-view application, such as in the brain, is to be determined.…”

Section: Status Go Hardwarementioning

confidence: 99%

“…For example, the threshold sits below the preferred 208 keV imaging window of Lutetium-177 [67], and well below the upper 364 keV energy window of Iodine-131. To allow faster SPECT acquisitions using a ring detector, semiconductors optimal for these higher energies may be required, or possibly using scintillation crystals with traditional or solid-state readout [64,68].…”

Section: Detectorsmentioning

confidence: 99%

What scans we will read: imaging instrumentation trends in clinical oncology

et al. 2020

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Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized noninvasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", andthrough the wider adoption of advanced analysis, including machine learning approaches and a "big data" conceptmove to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multidimensional data from multiple sources, which mandate the use of advanced and interactive visualization and

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