caliPER: A software for blood-free parametric Patlak mapping using PET/MRI input function

Dassanayake, Praveen; Cui, Lumeng; Finger, Elizabeth; Kewin, Matthew; Hadaway, Jennifer; Soddu, Andrea; Jakoby, Bjoern; Zuehlsdorf, Sven; Lawrence, Keith St.; Moran, Gerald R.; Anazodo, Udunna

doi:10.1016/j.neuroimage.2022.119261

Cited by 12 publications

(12 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, there may be systemic errors in the estimates of the RCs (27). Additionally, partial volume errors in objects approaching the intrinsic spatial resolution of the PET/MRI contribute to signals outside the boundaries of the vials, which are amplified by overlap of high-density components in the µ map and included in the total-cadaver measurement.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Attenuation Correction for PET/MRI to Measure Tracer Activity Surrounding Total Knee Arthroplasty

Bourdon

Koudys

Lanting

et al. 2022

Preprint

View full text Add to dashboard Cite

Background. Positron emission tomography (PET) in combination with magnetic resonance imaging (MRI) could allow inflammatory complications near total knee arthroplasty (TKA) to be studied early in their development. However, attenuation of the PET signal by the metal TKA implants imparts substantial error into measurements of tracer activity, and conventional MR-based attenuation correction (AC) methods have large signal voids in the vicinity of metal implants. Purpose. To evaluate a segmentation-based AC approach to measure tracer uptake from PET/MRI scans near TKA implants. Methods. A TKA implant (Triathlon, Stryker, Mahwah, USA) was implanted into a cadaver. Four vials were filled with [ 18 F]fluorodeoxyglucose with known activity concentration (4.68 MBq total, 0.76 MBq/mL) and inserted into the knee. Images of the knee were acquired using a 3T PET/MRI system (Biograph mMR, Siemens Healthcare, Erlangen, Germany). Models of the implant components were registered to the MR data using rigid-body transformations and the other tissue classes were manually segmented. These segments were used to create the segmentation-based map and complete the AC. Percentage error of the resulting measured activities was calculated by comparing the measured and known amounts of activity in each vial. Results. The original AC resulted in a percentage error of 64.1% from the known total activity. Errors in the individual vial activities ranged from 40.2% to 82.7%. Using the new segmentation-based AC, the percentage error of the total activity decreased to 3.55%. Errors in the individual vials were less than 15%. Conclusions. The segmentation-based AC technique dramatically reduced the error in activity measurements that result from PET signal attenuation by the metal TKA implant. This approach may be useful to enhance the reliability of PET/MRI measurements for numerous applications.

show abstract

Section: Discussionmentioning

confidence: 99%

“…In a previous experiment, PET recovery coefficients (RC) were measured using a modified NEMA IEC Body Phantom containing acrylic cylinders with inner diameters ranging from 5 to 30 mm filled with a known activity concentration (27). The RC curve was fit to an equation describing RC as a function of diameter (28).…”

Section: Attenuation Correction µ Mapsmentioning

confidence: 99%

Attenuation Correction for PET/MRI to Measure Tracer Activity Surrounding Total Knee Arthroplasty

Bourdon

Koudys

Lanting

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The MDIFs were assessed in comparison to AIFs using retrospective data from animal experiments [20] To obtain the MDIF, a semi-automatic procedure was used to define a VOI encompassing the brain in each anatomical slice. The final WB VOI, which was the composite of all the slices, was transferred to the dynamic [ 18 F]FDG-PET images to extract the WB TAC.…”

Section: Animal Studymentioning

confidence: 99%

“…For visual comparison, an IDIF was extracted from the feeding arteries for two representative subjects using the semi-automated software caliPER (parametric Patlak mapping using PET/MRI input function). Details can be found elsewhere [20]. Briefly, masks were generated on a time-of-flight MR image and semi-automatically transferred to the dynamic PET image, followed by extracting the time-varying activity concentration from the petrous segment of the internal carotid arteries.…”

Section: Human Studymentioning

confidence: 99%

“…PVE corrections can be facilitated by combining magnetic resonance imaging (MRI) angiography of the feeding arteries [16], but PET and MRI misalignments can introduce errors in the IDIF, which require sophisticated registration methods [17]; and complex vessel segmentation approaches can limit applicability [18]. Alternatively, hybrid PET/MR imaging allows for simultaneous acquisition of both functional and anatomical information, reducing misalignment errors [19,20] and facilitating PVE correction [21,22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous estimation of a model-derived input function for quantifying cerebral glucose metabolism with [18F]FDG PET

Narciso

Dassanayake

Liu

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Quantification of cerebral glucose metabolism by dynamic [ 18 F]FDG PET is often limited to the cerebral metabolic rate of glucose (CMRGlu) due to the challenges associated with obtaining microparameters at the voxelwise level (e.g., noise, choice of parameter estimation method, and input function quality). Efforts to avoid invasive arterial sampling include the simultaneous estimation (SIME) approach, which models the image-derived input function (IDIF) by series of exponentials with coefficients obtained by fitting time activity curves (TACs) from multiple volumes-of-interest. A limitation of SIME is the assumption that the input function can be modelled accurately by a series of exponentials. Alternatively, we propose a SIME approach based on the two-tissue compartment model to extract a high signal-to-noise ratio (SNR) modelderived input function (MDIF) from the whole-brain TAC. The purpose of this study is to present the MDIF approach and its implementation in the analysis of animal and human data. Methods: Simulations were performed to assess the MDIF approach in terms of accuracy, by evaluating a range of temporal resolutions; and precision, by adding noise to simulated TACs. The derived MDIFs were compared to the gold standard using retrospective data from animal experiments ( n = 5). Retrospective data from neurologically healthy volunteers ( n = 18) were used to extract macro- and microparameters from dynamic [ 18 F]FDG PET data. Results: Simulations demonstrated that extracting the MDIF from a whole-brain TAC requires using a sampling rate sufficient to minimize truncation errors. The MDIF approach improved the precision of estimated [ 18 F]FDG microparameters compared to the original SIME method. Good agreement between MDIFs and measured AIFs was found in the animal experiments. Similarly, the ratio of the area under the curve for MDIF to IDIF in the human experiments was 1.05 ± 0.11, resulting in agreement in grey matter CMRGlu: 24.2 ± 3.5 and 24.4 ± 3.8 mL/100 g/min for MDIF and IDIF, respectively. The MDIF method was superior in characterizing the first pass of [ 18 F]FDG. Groupwise macro- and microparameter voxelwise images obtained with the MDIF showed the expected patterns. Conclusions: A model-driven SIME method was proposed to derive high SNR input functions. Simulations indicate that [ 18 F]FDG rate constants obtained with the MDIF had higher precision than corresponding estimates from the original IDIF SIME approach, which is attributed to the MDIF method requiring fewer fitting parameters to characterize the input function.

show abstract

Simultaneous PET/MR Imaging of Dementia

Catana

2023

Molecular Imaging of Neurodegenerative Disorders

View full text Add to dashboard Cite

caliPER: A software for blood-free parametric Patlak mapping using PET/MRI input function

Cited by 12 publications

References 29 publications

Attenuation Correction for PET/MRI to Measure Tracer Activity Surrounding Total Knee Arthroplasty

Attenuation Correction for PET/MRI to Measure Tracer Activity Surrounding Total Knee Arthroplasty

Simultaneous estimation of a model-derived input function for quantifying cerebral glucose metabolism with [18F]FDG PET

Simultaneous PET/MR Imaging of Dementia

Contact Info

Product

Resources

About