The development of radiation detectors capable of delivering spatial information about gamma-ray interactions was one of the key enabling technologies for nuclear medicine imaging and, eventually, single-photon emission computed tomography (SPECT). The continuous sodium iodide scintillator crystal coupled to an array of photomultiplier tubes, almost universally referred to as the Anger Camera after its inventor, has long been the dominant SPECT detector system. Nevertheless, many alternative materials and configurations have been investigated over the years. Technological advances as well as the emerging importance of specialized applications, such as cardiac and preclinical imaging, have spurred innovation such that alternatives to the Anger Camera are now part of commercial imaging systems. Increased computing power has made it practical to apply advanced signal processing and estimation schemes to make better use of the information contained in the detector signals. In this review we discuss the key performance properties of SPECT detectors and survey developments in both scintillator and semiconductor detectors and their readouts with an eye toward some of the practical issues at least in part responsible for the continuing prevalence of the Anger Camera in the clinic.

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SPECT detectors: the Anger Camera and beyond.

Secondary radiation emission induced by nuclear reactions is correlated to the path of ions in matter. Therefore, such penetrating radiation can be used for in vivo control of hadrontherapy treatments, for which the primary beam is absorbed inside the patient. Among secondary radiations, prompt-gamma rays were proposed for real-time verification of ion range. Such a verification is a desired condition to reduce uncertainties in treatment planning. For more than a decade, efforts have been undertaken worldwide to promote prompt-gamma-based devices to be used in clinical conditions. Dedicated cameras are necessary to overcome the challenges of a broad- and high-energy distribution, a large background, high instantaneous count rates, and compatibility constraints with patient irradiation. Several types of prompt-gamma imaging devices have been proposed, that are either physically-collimated or electronically collimated (Compton cameras). Clinical tests are now undergoing. Meanwhile, other methods than direct prompt-gamma imaging were proposed, that are based on specific counting using either time-of-flight or photon energy measurements. In the present article, we make a review and discuss the state of the art for all techniques using prompt-gamma detection to improve the quality assurance in hadrontherapy.

Prompt-gamma monitoring in hadrontherapy: A review

This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.

A review on medical imaging synthesis using deep learning and its clinical applications.

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Positron emission tomography (PET) is the most sensitive of all medical imaging modalities for quantitatively probing biologic processes at the molecular level. However, spatial resolution in PET is significantly inferior to that of other imaging modalities that can provide exquisite images of the anatomy, such as X-ray computed tomography (CT) or magnetic resonance (MR) imaging. It has been one of the outstanding challenges of the last decade to combine PET with these complementary imaging modalities in order to synergistically exploit the benefits of each modality and to enhance the role of PET in pre-clinical research as well as in clinical routine and research. The simple juxtaposition of tomographs around a common axial bed, such as with current PET/CT technology, is very successful in allowing sequential acquisition of PET and anatomical data. However, novel imaging combinations are being considered that would enable simultaneous, or at least concurrent, dual-modality imaging through combined PET/MR or PET/CT. The development of these new integrated instruments creates new bewildering challenges for PET detection systems, which, in addition to the ability to measure annihilation radiation in PET, must satisfy several other critical requirements.

Novel detector technology for clinical PET

The current generation of total-body positron emission tomography (PET) scanners offer significant sensitivity increase with an extended axial imaging extent. With the large volume of lutetium-based scintillation crystals that are used as detector elements in these scanners, there is an increased flux of background radiation originating from 176Lu decay in the crystals and higher sensitivity for detecting it. Combined with the ability of scanning the entire body in a single bed position, this allows more effective utilization of the lutetium background as a transmission source for estimating 511 keV attenuation coefficients. In this study, utilization of the lutetium background radiation for attenuation correction in total-body PET was studied using Monte Carlo simulations of a 3D whole-body XCAT phantom in the uEXPLORER PET scanner, with particular focus on ultralow-dose PET scans that are now made possible with these scanners. Effects of an increased acceptance angle, reduced scan durations, and Compton scattering on PET quantification were studied. Furthermore, quantification accuracy of lutetium-based attenuation correction was compared for a 20-min scan of the whole body on the uEXPLORER, a one-meter-long, and a conventional 24-cm-long scanner. Quantification and lesion contrast were minimally affected in both long axial field-of-view scanners and in a whole-body 20-min scan, the mean bias in all analyzed organs of interest were within a ±10% range compared to ground-truth activity maps. Quantification was affected in certain organs, when scan duration was reduced to 5 min or a reduced acceptance angle of 17° was used. Analysis of the Compton scattered events suggests that implementing a scatter correction method for the transmission data will be required, and increasing the energy threshold from 250 keV to 290 keV can reduce the computational costs and data rates, with negligible effects on PET quantification. Finally, the current results can serve as groundwork for transferring lutetium-based attenuation correction into research and clinical practice.

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Lutetium background radiation in total-body PET—A simulation study on opportunities and challenges in PET attenuation correction

1394 Objectives: Dynamic PET provides more accurate quantitative information and richer disease information than static PET. However, routine clinical application of dynamic PET imaging is limited by invasive arterial blood sampling (or manually annotated image-derived blood activity) for use as an input function. This study aimed to develop a deep learning-based method to directly estimate the input function from dynamic PET data without any manual assistance.
 Methods: Our study consists of two clinical datasets. The first group of data includes dynamic FDG scans performed on the United Imaging uMI 510 PET/CT system in the Chinese PLA General Hospital. 35 subjects (25 male, 10 females; 13 healthy; age 15-73y) were scanned. Image-derived blood activity was used as input function. The second dataset (n= 26 healthy subjects) includes 90-min dynamic brain data after bolus injection of 11C-DPA-713(DPA) performed on a Siemens HRRT PET system at Johns Hopkins University. All DPA PET data in this study were acquired from individuals with high affinity binding genotype for the 18 kDa translocator protein target and included input function data acquired through arterial blood sampling and radiometabolite measurements. There were 30 dynamic frames in each scan. The input function value for each dynamic frame was interpolated from the measured input function curve. Each dataset was split into 3 parts: 70% as training set, 20% as validation set and 10% as test set. Two deep learning networks, namely the raw model and the fine-tuned model were investigated. The raw model contains a down-sampling convolutional module to extract image features and a fully connected regression module to predict the input function. The 3-D dynamic image and reference image are stacked to form a two-channel 4-D input. For FDG tracer, the reference image refers to image reconstructed from data acquired in 0 to 20 minutes scan. For DPA, the mean image of all dynamic images served as the reference image. L1-loss is chosen as the loss function based on controlled experiment results. In the fine-tuned model, the 1-D vector acquired from the convolutional module are concatenated with medical information including patient’s age, weight, height, injected dose, frame time. Data augmentation methods such as random center crop & resize, rotation, translation and scaling were used in training fine-tuned model. The input function for DPA was normalized according to its integral value before reconstruction. Indirect voxel-based reconstruction methods were used: Patlak analysis with start time (t*) of 20 minutes for Ki (FDG) and Logan analysis with t* of 30 minutes for VT (DPA). To investigate the performance of the proposed method, the root mean square error (RMSE) was calculated between the parametric images reconstructed with true and predicted input function.
 Results: The predicted input function shows similarity in shape to the standard input function. The prediction error in early stage was larger than in later stage, especially for the peak values in early stage. The fine-tuned model enhances prediction accuracy in the early stage, while the improvement in later stage was not obvious. The visual quality of reconstructed Ki and VT parametric image of the fine-tuned model was apparently better than that of raw model. The RMSE of the fine-tuned model was much lower than the raw model.
 Conclusions: The proposed fine-tuned deep learning-based method was able to estimate the input function directly from dynamic images. The high accuracy of the reconstructed parametric image using the predicted input function supports pursuit of this method for clinical application. In future work we will investigate to further improve the accuracy of the predicted input function.
Support: The research was supported by the National Natural Science Foundation of China (No. 81727807, No.11575096, No. 11605008) and National Key Research and Development (R&D) Plan of China (Grant ID. 2019YFF0302503 and 2016YFC0105405).

Direct Estimation of Input Function Based on Fine-tuned Deep Learning Method in Dynamic PET Imaging

In this work, a new readout electronics system based on an eight-channel readout ASIC is developed for PET detector using PMT-quadrant-sharing (PQS) design A PQS detector module consists of a 9×9 L YSO crystal block (21×21×10mm3 each crystal) coupled to four PMTs We propose a compact design of readout electronics with time based readout ASIC and Time-Digital-Convertor (TDC) programmed in Field-Programmable-Gated-Array (FPGA) The function of the ASIC is to convert both signal charge and timing information into digital timing pulses which will be processed by back-end TDC In this way, highly flexible and low cost electronics is developed because the traditional Analog-Digital-Convertor (ADC) and Constant-Fraction-Discriminator (CFD) are replaced Preliminary tests show that the ASIC has demonstrated good linearity and uniformity To test the performance of our ASIC based electronics, we compared it with a traditional high speed ADC based data acquisition system which was previously developed in our lab Crystal flood map was acquired on both acquisition systems and the crystals were clearly identifiable A coincidence timing resolution of about 18 ns was achieved, which can be furthered improved through time walk error correction We conclude that the proposed electronics is feasible for PQS PET detectors

Readout electronics development based on an ASIC for PET detector using PMT-quadrant-sharing

The invention provides a neutron gamma online discrimination method and a corresponding neutron gamma detector. The neutron gamma online discrimination method comprises the following steps of optimizing to obtain an optimal integral time combination of a dual-energy window integral method; acquiring and processing the electric pulse signals obtained by detecting the neutrons and gamma radiation toform the electric pulse signals, realizing the online real-time discrimination of the neutrons and the gamma pulse signals by utilizing the double-energy-window integral method and the optimal integral time combination, and discriminating the neutrons and gamma signals by adopting a pulse shape discrimination factor Rpsd. According to the discrimination method and the neutron gamma detector, theneutron and gamma discrimination is carried out by using the dual-energy window method for optimizing the integral time for individuals, the dependence of the overall performance of the detector on individual differences of crystals and devices is reduced, the online discrimination of neutrons and gamma rays is realized, and the false alarm rate of neutron detection is greatly reduced. Moreover, according to the neutron gamma detector, the neutrons and gamma rays are detected by adopting a single sensor device, the whole detection system is greatly simplified, and the size and power consumption of an instrument are reduced.

Neutron gamma detector based on physical integration and neutron gamma online discrimination method

https://www.acsu.buffalo.edu/~rutaoyao/2010_tianyu_TsinghuaScienceTechnology.pdf

Tianyu Ma

Papers

Lutetium background radiation in total-body PET—A simulation study on opportunities and challenges in PET attenuation correction

Direct Estimation of Input Function Based on Fine-tuned Deep Learning Method in Dynamic PET Imaging

Readout electronics development based on an ASIC for PET detector using PMT-quadrant-sharing

Neutron gamma detector based on physical integration and neutron gamma online discrimination method

Quantitative accuracy assessment and optimization of SPECT geometrical calibration