The impact of regional 99mTc-HMPAO single-photon-emission computed tomography (SPECT) imaging on clinician diagnostic confidence in a mixed cognitive impairment sample
“…Imabayashi et al reported a 12% improvement in quantitative accuracy when using quantification [14]. Semi-quantitative SPECT has also been shown by Prosser et al to be valued by referring clinicians and to improve clinician diagnostic confidence [29]. The use of quantification is crucial for optimising the diagnostic performance of perfusion SPECT and is recommended by the EANM guidelines [9,30].…”
Objectives
With disease-modifying therapies in development for neurological disorders, quantitative brain imaging techniques become increasingly relevant for objective early diagnosis and assessment of response to treatment. The aim of this study was to evaluate the use of Brain SPECT and PET scans in the UK and explore drivers and barriers to using quantitative analysis through an online survey.
Methods
A web-based survey with 27 questions was used to capture a snapshot of brain imaging in the UK. The survey included multiple-choice questions assessing the availability and use of quantification for DaTscan, Perfusion SPECT, FDG PET and Amyloid PET. The survey results were reviewed and interpreted by a panel of imaging experts.
Results
Forty-six unique responses were collected and analysed, with 84% of responses from brain imaging sites. Within these sites, 88% perform DaTscan, 50% Perfusion SPECT, 48% FDG PET, and 33% Amyloid PET, while a few sites use other PET tracers. Quantitative Brain analysis is used in 86% of sites performing DaTscans, 40% for Perfusion SPECT, 63% for FDG PET and 42% for Amyloid PET. Commercial tools are used more frequently than in-house software.
Conclusion
The survey showed variations across the UK, with high availability of DaTscan imaging and quantification and lower availability of other SPECT and PET scans. The main drivers for quantification were improved reporting confidence and diagnostic accuracy, while the main barriers were a perception of a need for an appropriate database of healthy controls and a lack of training, time, and software availability.
“…Imabayashi et al reported a 12% improvement in quantitative accuracy when using quantification [14]. Semi-quantitative SPECT has also been shown by Prosser et al to be valued by referring clinicians and to improve clinician diagnostic confidence [29]. The use of quantification is crucial for optimising the diagnostic performance of perfusion SPECT and is recommended by the EANM guidelines [9,30].…”
Objectives
With disease-modifying therapies in development for neurological disorders, quantitative brain imaging techniques become increasingly relevant for objective early diagnosis and assessment of response to treatment. The aim of this study was to evaluate the use of Brain SPECT and PET scans in the UK and explore drivers and barriers to using quantitative analysis through an online survey.
Methods
A web-based survey with 27 questions was used to capture a snapshot of brain imaging in the UK. The survey included multiple-choice questions assessing the availability and use of quantification for DaTscan, Perfusion SPECT, FDG PET and Amyloid PET. The survey results were reviewed and interpreted by a panel of imaging experts.
Results
Forty-six unique responses were collected and analysed, with 84% of responses from brain imaging sites. Within these sites, 88% perform DaTscan, 50% Perfusion SPECT, 48% FDG PET, and 33% Amyloid PET, while a few sites use other PET tracers. Quantitative Brain analysis is used in 86% of sites performing DaTscans, 40% for Perfusion SPECT, 63% for FDG PET and 42% for Amyloid PET. Commercial tools are used more frequently than in-house software.
Conclusion
The survey showed variations across the UK, with high availability of DaTscan imaging and quantification and lower availability of other SPECT and PET scans. The main drivers for quantification were improved reporting confidence and diagnostic accuracy, while the main barriers were a perception of a need for an appropriate database of healthy controls and a lack of training, time, and software availability.
“…Given the existing literature on SPECT in the differential diagnosis of dementias [22][23][24], subjects were filtered for the following labels assigned to their scan's outgoing impressions: dementia, AD, frontotemporal dementia (FTD), cognitive impairment, and neurodegenerative processes. Subjects also had these labels if such processes could not be ruled out during the read.…”
Aim:
Quantitative analysis of brain single photon emission computed tomography (SPECT) perfusion imaging is dependent on normative datasets that are challenging to produce. This study investigated the combination of SPECT neuroimaging from a large clinical population rather than small numbers of controls. The authors hypothesized this “population template” would demonstrate noninferiority to a control dataset, providing a viable alternative for quantifying perfusion abnormalities in SPECT neuroimaging.
Methods:
A total of 2, 068 clinical SPECT scans were averaged to form the “population template”. Validation was three-fold. First, the template was imported into SPECT brain analysis software, MIMneuro®, and compared against its control dataset of 90 individuals through its region and cluster analysis tools. Second, a cohort of 100 cognitively impaired subjects was evaluated against both the population template and MIMneuro®’s normative dataset to compute region-based metrics. Concordance and intraclass correlation coefficients, mean square deviations, total deviation indices, and limits of agreement were derived from these data to measure agreement and test for noninferiority. Finally, the same patients were clinically read in CereMetrix® to confirm that expected perfusion patterns appeared after comparison to the template.
Results:
MIMneuro®’s default threshold for normality is ± 1.65 z-score and this served as our noninferiority margin. Direct comparison of the template to controls produced no regions that exceeded this threshold and all clusters identified were far from statistically significant. Agreement measures revealed consistency between the softwares and that CereMetrix® results were noninferior to MIMneuro®, albeit with proportional bias. Visual analysis also confirmed that expected perfusion patterns appeared when individual scans were compared to the population template within CereMetrix®.
Conclusions:
The authors demonstrated a population template was noninferior to a smaller control dataset despite inclusion of abnormal scans. This suggests that our patient-based population template can serve as an alternative for identifying and quantifying perfusion abnormalities in brain SPECT.
“…ELISA and neuroimaging have been the common methods to study on detection of Aβ42 and other biomarkers [16,17]. Besides, numerous other techniques/methods have been improved for Aβ42 quantification such as fluorescent microscopy, quantum dot nanoprobes, nanomaterials, mass spectrometry, immobilized metal affinity chromatography and meta-analysis, Positron Emission Tomography (PET), Photon and Single-Photon Emission Computed Tomography, Regular and Functional Magnetic Resonance Imaging (MRI) [18][19][20][21][22]. Laboratory tests include genetic tests, biomarker detections, and CSF analysis [23].…”
A novel fiber optic biosensor was purposed for a new approach to monitor amyloid beta protein fragment 1-42 (Aβ42) for Alzheimer’s Disease (AD) early detection. The sensor was fabricated by etching a part of fiber from single mode fiber loop in pure hydrofluoric acid solution and utilized as a Local Optical Refractometer (LOR) to monitor the change Aβ42 concentration in Artificial Cerebrospinal Fluid (ACSF). The Fiber Loop Ringdown Spectroscopy (FLRDS) technique is an ultra-sensitive measurement technique with low-cost, high sensitivity, real-time measurement, continuous measurement and portability features that was utilized with a fiber optic sensor for the first time for the detection of a biological signature in an ACSF environment. Here, the measurement is based on the total optical loss detection when specially fabricated sensor heads were immersed into ACSF solutions with and without different concentrations of Aβ42 biomarkers since the bulk refractive index change was performed. Baseline stability and the reference ring down times of the sensor head were measured in the air as 0.87% and 441.6 μs 3.9 μs, respectively. Afterward, the total optical loss of the system was measured when the sensor head was immersed in deionized water, ACSF solution, and ACSF solutions with Aβ42 in different concentrations. The lowest Aβ42 concentration of 2 ppm was detected by LOR. Results showed that LOR fabricated by single-mode fibers for FLRDS system design are promising candidates to be utilized as fiber optic biosensors after sensor head modification and have a high potential for early detection applications of not only AD but possibly also several fatal diseases such as diabetes and cancer.
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