Clinical NECR in 18F-FDG PET scans: optimization of injected activity and variable acquisition time. Relationship with SNR

Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system

To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated "sufficient image quality" and 117 images rated "insufficient image quality". The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Variability in PET image quality and quantification measured with a permanently filled 68Ge-phantom: a multi-center study

BACKGROUND

This study evaluated, as a snapshot, the variability in quantification and image quality (IQ) of the clinically utilized PET [¹⁸F]FDG whole-body protocols in Finland using a NEMA/IEC IQ phantom permanently filled with ⁶⁸Ge.

METHODS

The phantom was imaged on 14 PET-CT scanners, including a variety of models from two major vendors. The variability of the recovery coefficients (RC_max, RC_mean and RC_peak) of the hot spheres as well as percent background variability (PBV), coefficient of variation of the background (COV_BG) and accuracy of corrections (AOC) were studied using images from clinical and standardized protocols with 20 repeated measurements. The ranges of the RCs were also compared to the limits of the EARL ¹⁸F standards 2 accreditation (EARL2). The impact of image noise on these parameters was studied using averaged images (AVIs).

RESULTS

The largest variability in RC values of the routine protocols was found for the RC_max with a range of 68% and with 10% intra-scanner variability, decreasing to 36% when excluding protocols with suspected cross-calibration failure or without point-spread-function (PSF) correction. The RC ranges of individual hot spheres in routine or standardized protocols or AVIs fulfilled the EARL2 ranges with two minor exceptions, but fulfilling the exact EARL2 limits for all hot spheres was variable. RC_peak was less dependent on averaging and reconstruction parameters than RC_max and RC_mean. The PBV, COV_BG and AOC varied between 2.3-11.8%, 9.6-17.8% and 4.8-32.0%, respectively, for the routine protocols. The RC ranges, PBV and COV_BG were decreased when using AVIs. With AOC, when excluding routine protocols without PSF correction, the maximum value dropped to 15.5%.

CONCLUSION

The maximum variability of the RC values for the [¹⁸F]FDG whole-body protocols was about 60%. The RC ranges of properly cross-calibrated scanners with PSF correction fitted to the EARL2 RC ranges for individual sphere sizes, but fulfilling the exact RC limits would have needed further optimization. RC_peak was the most robust RC measure. Besides COV_BG, also RCs and PVB were sensitive to image noise.

Impact of Region-of-Interest Delineation on Stability and Reproducibility of Liver SNR Measurements in 68 Ga-PSMA PET/CT

Objective  This study aims to assess the impact of various regions of interest (ROIs) and volumes of interest (VOIs) delineations on the reproducibility of liver signal-to-noise-ratio (SNRliver) measurements, as well as to find the most reproducible way to estimate it in gallium-68 positron emission tomography ( ⁶⁸ Ga-PET) imaging. We also investigated the SNRliver-weight relationship for these ROIs and VOIs delineations. Methods  A cohort of 40 patients (40 males; mean weight: 76.5 kg [58-115 kg]) with prostate cancer were included. ⁶⁸ Ga-PET/CT imaging (mean injected activity: 91.4 MBq [51.2 MBq to 134.1 MBq] was performed on a 5-ring bismuth germanium oxide-based Discovery IQ PET/CT using ordered subset expectation maximization image reconstruction algorithm. Afterward, circular ROIs and spherical VOIs with two different diameters of 30 and 40 mm were drawn on the right lobe of the livers. The performance of the various defined regions was evaluated by the average standardized uptake value (SUV _mean ), standard deviation (SD) of the SUV (SUV _SD ), SNR _liver , and SD of the SNR _liver metrics. Results  There were no significant differences in SUV _mean among the various ROIs and VOIs ( p  > 0.05). On the other hand, the lower SUV _SD was obtained by spherical VOI with diameter of 30 mm. The largest SNR _liver was obtained by ROI (30 mm). The SD of SNR _liver with ROI (30 mm) was also the largest, while the lowest SD of SNR _liver was observed for VOI (40 mm). There is a higher correlation coefficient between the patient-dependent parameter of weight and the image quality parameter of SNRliver for both VOI (30 mm) and VOI (40 mm) compared to the ROIs. Conclusion  Our results indicate that SNR _liver measurements are affected by the size and shape of the respective ROIs and VOIs. The spherical VOI with a 40 mm diameter leads to more stable and reproducible SNR measurement in the liver.

Semi-Quantitative [18F]FDG-PET/CT ROC-Analysis-Based Cut-Offs for Aortitis Definition in Giant Cell Arteritis

[18F]fluorodeoxyglucose-positron emission tomography/computed tomography ([18F]FDG-PET/CT) is used to diagnose large vessel vasculitis in giant cell arteritis (GCA). We aimed to define a semi-quantitative threshold for identifying GCA aortitis from aortic atheroma or the control. Contrast enhanced computed tomography (CECT) was used as the reference imaging for aortic evaluation and to define aortitis, aortic atheroma and control aortas. [18F]FDG-PET/CT was performed on 35 GCA patients and in two different control groups (aortic atheroma (n = 70) and normal control (n = 35)). Aortic semi-quantitative features were compared between the three groups. GCA patients without aortitis on CECT were excluded. Of the GCA patients, 19 (54.3%) were not on glucocorticoids (GC) prior to [18F]FDG-PET/CT. The SUVmax, TBRblood and TBRliver aortic values were significantly higher in the GCA aortitis group than in the aortic atheroma and control groups (p < 0.001). Receiver operating characteristic curve analyses brought to light quantitative cut-off values allowing GCA aortitis diagnosis with optimal sensitivity and specificity versus control or aortic atheroma patients for each PET-based feature analyzed. Considering the overall aorta, a SUVmax threshold of 3.25 and a TBRblood threshold of 1.75 had a specificity of 83% and 75%, respectively, a sensitivity of 81% and 81%, respectively, and the area under the ROC curve (AUC) was 0.86 and 0.83, respectively, for aortitis detection compared to control groups in GCA cases with GC. A SUVmax threshold of 3.45 and a TBRblood threshold of 1.97 had a specificity of 90% and 93%, respectively, a sensitivity of 89% and 89%, respectively, with an AUC of 0.89 and 0.96, respectively, for aortitis detection compared to the control in GC-free GCA cases. Discriminative thresholds of SUVmax and TBRblood for the diagnosis of GCA aortitis were established using CECT as the reference imaging.

Relating18F-FDG image signal-to-noise ratio to time-of-flight noise-equivalent count rate in total-body PET using the uEXPLORER scanner

Objective.This work assessed the relationship between image signal-to-noise ratio (SNR) and total-body noise-equivalent count rate (NECR)-for both non-time-of-flight (TOF) NECR and TOF-NECR-in a long uniform water cylinder and 14 healthy human subjects using the uEXPLORER total-body PET/CT scanner.Approach.A TOF-NEC expression was modified for list-mode PET data, and both the non-TOF NECR and TOF-NECR were compared using datasets from a long uniform water cylinder and 14 human subjects scanned up to 12 h after radiotracer injection.Main results.The TOF-NECR for the uniform water cylinder was found to be linearly proportional to the TOF-reconstructed image SNR²in the range of radioactivity concentrations studied, but not for non-TOF NECR as indicated by the reducedR²value. The results suggest that the use of TOF-NECR to estimate the count rate performance of TOF-enabled PET systems may be more appropriate for predicting the SNR of TOF-reconstructed images.Significance.Image quality in PET is commonly characterized by image SNR and, correspondingly, the NECR. While the use of NECR for predicting image quality in conventional PET systems is well-studied, the relationship between SNR and NECR has not been examined in detail in long axial field-of-view total-body PET systems, especially for human subjects. Furthermore, the current NEMA NU 2-2018 standard does not account for count rate performance gains due to TOF in the NECR evaluation. The relationship between image SNR and total-body NECR in long axial FOV PET was assessed for the first time using the uEXPLORER total-body PET/CT scanner.

Specific features to differentiate Giant cell arteritis aortitis from aortic atheroma using FDG-PET/CT

Aortic wall ¹⁸F-fluorodeoxyglucose (FDG)-uptake does not allow differentiation of aortitis from atheroma, which is problematic in clinical practice for diagnosing large vessel vasculitis giant-cell arteritis (GCA) in elderly patients. The purpose of this study was to compare the FDG uptake characteristics of GCA aortitis and aortic atheroma using positron emission tomography/FDG computed tomography (FDG-PET/CT). This study compared FDG aortic uptake between patients with GCA aortitis and patients with aortic atheroma; previously defined by contrast enhanced CT. Visual grading according to standardized FDG-PET/CT interpretation criteria and semi-quantitative analyses (maximum standardized uptake value (SUV_max), delta SUV (∆SUV), target to background ratios (TBR)) of FDG aortic uptake were conducted. The aorta was divided into 5 segments for analysis. 29 GCA aortitis and 66 aortic atheroma patients were included. A grade 3 FDG uptake of the aortic wall was identified for 23 (79.3%) GCA aortitis patients and none in the atheroma patient group (p < 0.0001); grade 2 FDG uptake was as common in both populations. Of the 29 aortitis patients, FDG uptake of all 5 aortic segments was positive for 21 of them (72.4%, p < 0.0001). FDG uptake of the supra-aortic trunk was identified for 24 aortitis (82.8%) and no atheromatous cases (p < 0.0001). All semi-quantitative analyses of FDG aortic wall uptake (SUV_max, ∆SUV and TBRs) were significantly higher in the aortitis group. ∆SUV was the feature with the largest differential between aortitis and aortic atheroma. In this study, GCA aortitis could be distinguished from an aortic atheroma by the presence of an aortic wall FDG uptake grade 3, an FDG uptake of the 5 aortic segments, and FDG uptake of the peripheral arteries.

From a PMT-based to a SiPM-based PET system: a study to define matched acquisition/reconstruction parameters and NEMA performance of the Biograph Vision 450

Background

The purpose of this work was to propose an approach based on noise measurement to adapt present clinical acquisition and reconstruction parameters adapted to a PMT-based system (Biograph mCT) to a SiPM-based system (Biograph Vision 450) sharing identical geometrical properties. The NEMA performance (NEMA) of the recently released Biograph Vision 450 PET/CT (Vision) was also derived.

Methods

All measurements were conducted on Vision and Biograph mCT with TrueV (mCT). A full NEMA-based performance was derived for Vision only. The adaptation of acquisition and reconstruction parameters from mCT to Vision was done using the NEMA image quality phantom. The noise level reached using mCT was set as the reference value for six different numbers of net true coincidences. The noise level computed using Vision was matched to the reference noise level (within 0.01%) using a different reconstruction set-up to determine the potential reduction of count numbers for the same noise level.

Results

Vision sensitivity was 9.1 kcps/MBq for a timing resolution of 213 ps at 5.3 kBq/mL. The NEMA-based CR for the 10-mm sphere was better than 75% regardless the reconstruction set-up studied. The mCT reference noise properties could be achieved using Vision with a scan time reduction (STR) of 1.34 with four iterations and a 440 × 440 matrix size (or STR = 1.89 with a 220 × 220 matrix size) together with a 3D CR improvement of 53% for the 10-mm sphere (24% using 220 × 220).

Conclusion

The Vision exhibited improved NEMA performances compared to mCT. Using the proposed approach, the time acquisition could be divided by almost two, while keeping the same noise properties as that of mCT with a marked improvement of contrast recovery.

The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution

OBJECTIVES

The present study aims to assess the impact of acquisition time, different iterative reconstruction protocols as well as image context (including contrast levels and background activities) on the measured spatial resolution in PET images.

METHODS

Discovery 690 PET/CT scanner was used to quantify spatial resolutions in terms of full width half maximum (FWHM) as derived (i) directly from capillary tubes embedded in air and (ii) indirectly from 10 mm-diameter sphere of the NEMA phantom. Different signal-to-background ratios (SBRs), background activity levels and acquisition times were applied. The emission data were reconstructed using iterative reconstruction protocols. Various combinations of iterations and subsets (it × sub) were evaluated.

RESULTS

For capillary tubes, improved FWHM values were obtained for higher it × sub, with improved performance for PSF algorithms relative to non-PSF algorithms. For the NEMA phantom, by increasing acquisition times from 1 to 5 min, intrinsic FWHM for reconstructions with it × sub 32 (54) was improved by 15.3% (13.2%), 15.1% (13.8%), 14.5% (12.8%) and 13.7% (12.7%) for OSEM, OSEM + PSF, OSEM + TOF and OSEM + PSF + TOF, respectively. Furthermore, for all reconstruction protocols, the FWHM improved with more impact for higher it × sub.

CONCLUSION

Our results indicate that PET spatial resolution is greatly affected by SBR, background activity and the choice of the reconstruction protocols.

Image quality evaluation in a modern PET system: impact of new reconstructions methods and a radiomics approach

The present work investigates the influence of different biological and physical parameters on image quality (IQ) perception of the abdominal area in a modern PET scanner, using new reconstruction algorithms and testing the utility of a radiomics approach. Scans of 112 patients were retrospectively included. Images were reconstructed using both OSEM + PSF and BSRM methods, and IQ of the abdominal region was subjectively evaluated. First, 22 IQ related parameters were obtained (including count rate and biological or mixed parameters) and compared to the subjective IQ scores by means of correlations and logistic regression. Second, an additional set of radiomics features was extracted, and a model was constructed by means of an elastic-net regression. For the OSEM + PSF and especially for the BSRM reconstructions, IQ parameters presented only at best moderated correlations with the subjective IQ. None of the studied parameters presented a good predictive power for IQ, while a simple radiomics model increased the performance of the IQ prediction. These results suggest the necessity of changing the standard parameters to evaluate IQ, particularly when a BSRM algorithm is involved. Furthermore, it seems that a simple radiomics model can outperform the use of any single parameter to assess IQ.

Two novel PET image restoration methods guided by PET-MR kernels: Application to brain imaging

PURPOSE

Post-reconstruction positron emission tomography (PET) image restoration methods that take advantage of available anatomical information can play an important role in accurate quantification of PET images. However, when using anatomical information, the resulting PET image may lose resolution in certain regions where the anatomy does not agree with the change in functional activity. In this work, this problem is addressed by using both magnetic resonance (MR) and filtered PET images to guide the denoising process.

METHODS

In this work, two novel post-reconstruction methods for restoring PET images using the subject's registered T1-weighted MR image are proposed. The first method is based on a representation of the image using basis functions extracted from T1-weighted MR and filtered PET image. The coefficients for these basis functions are estimated using a sparsity-penalized least squares objective function. The second method is a noniterative fast method that uses guided kernel filtering in combination with twicing to restore the noisy PET image. When applied after conventional PVE correction, these methods can be considered as voxel-based MR-guided partial volume effect (PVE) correction methods.

RESULTS

Using simulation analyses of [ 18 F]FDG PET images of the brain with lesions, the proposed methods are compared to other denoising methods through different figures of merit. The results show promising improvements in image quality as well as reduction in bias and variance of the lesions. We also show the application of the proposed methods on real [ 18 F]FDG data.

CONCLUSION

Two methods for restoring PET images were proposed. The methods were evaluated on simulation and real brain images. Most MR-guided PVE correction methods are only based on segmented T1-weighted images and their accuracy is very sensitive to segmentation errors, especially in regions of abnormalities and lesions. However, both proposed methods can use the T1-weighted image without segmentation. The simplicity and the very low computational cost of the second method make it suitable for clinical applications and large data studies. The proposed methods can be naturally extended to PVE correction and denoising of other functional modalities using corresponding anatomical information.

A clinical evaluation of the impact of the Bayesian penalized likelihood reconstruction algorithm on PET FDG metrics

PURPOSE

The aim of this study was to evaluate the impact of using the Bayesian penalized likelihood (BPL) algorithm on a bismuth germanium oxide positron emission tomography (PET)/computed tomography (CT) system for F-FDG PET/CT exams in case of low injected activity and scan duration.

MATERIALS AND METHODS

F-FDG respiratory gated PET/CT performed on 102 cancer patients, injected with ∼2 MBq/kg of F-FDG, were reconstructed using two algorithms: ordered subset expectation maximization (OSEM) and BPL. The signal-to-noise ratio (SNR) was calculated as the ratio of mean standard uptake value (SUV) over the standard deviation in a reference volume defined automatically in the liver. The peak SUV and volumes were also measured in lesions larger than 2 cm thanks to the automated segmentation method.

RESULTS

On 85 respiratory gated patients, the median SNR was significantly higher with BPL (P<0.0001) and it is even better when the BMI of the patient increases (odds ratio=1.26).For the 55 lesions, BPL significantly increased the SUVpeak [difference: (-0.5; 1.4), median=0.4, P<0.0001] compared with OSEM in 83.6% of the cases. With BPL, the volume was lower in 61.8% of the cases compared with OSEM, but this was not statistically significant.

CONCLUSION

The BPL algorithm improves the image quality and lesion contrast and appears to be particularly appropriate for patients with a high BMI as it improves the SNR. However, it will be important for patient follow-up or multicenter studies to use the same algorithm and preferably BPL.

Significant dose reduction is feasible in FDG PET/CT protocols without compromising diagnostic quality

PURPOSE

To reduce the radiation dose to patients by optimizing oncological FDG PET/CT protocols.

METHODS

The baseline PET/CT protocol in our institution for oncological PET/CT examinations consisted of the administration of 5.18 MBq/kg of FDG and a CT acquisition with a reference current-time product of 120 mAs. In 2016, FDG activity was reduced to 4.44 and 3.70 MBq/kg and reference CT current-time-product was reduced to 100 and 80 mAs. 322 patients scanned with different protocols were retrospectively evaluated. For each patient, effective dose was calculated. The overall image quality was subjectively rated by the referring physician on a 4-point scale (IQ score: 1 excellent, 2 good, 3 poor but interpretable, 4 poor not interpretable). Image quality was quantitatively evaluated measuring noise in the liver.

RESULTS

CT Results: Effective dose was progressively reduced from 9.5 ± 2.8 to 8.0 ± 2.3 and 6.2 ± 1.5 mSv (p < 0.001). A mean dose reduction of 34.9% was achieved. There was a significant degradation of IQ score (p < 0.05) and noise (p < 0.001). Nevertheless, the number of poor quality studies (IQ score >2) did not increase. PET Results: Effective dose was gradually reduced from 6.5 ± 1.4 to 5.7 ± 1.3 and 5.0 ± 1.0 mSv (p < 0.001). Average dose reduction was 23.4%. IQ score (p < 0.05) and noise (p < 0.001) significantly degraded for lower activity protocols. However, all images with reduced activity were scored as interpretable (IQ score ≤ 3).

CONCLUSIONS

A significant radiation dose reduction of 28.7% was reached. Despite a slight reduction in image quality, the new regime was successfully implemented with readers reporting unchanged clinical confidence.

Towards enhanced PET quantification in clinical oncology

Positron emission tomography (PET) has, since its inception, established itself as the imaging modality of choice for the in vivo quantitative assessment of molecular targets in a wide range of biochemical processes underlying tumour physiology. PET image quantification enables to ascertain a direct link between the time-varying activity concentration in organs/tissues and the fundamental parameters portraying the biological processes at the cellular level being assessed. However, the quantitative potential of PET may be affected by a number of factors related to physical effects, hardware and software system specifications, tracer kinetics, motion, scan protocol design and limitations in current image-derived PET metrics. Given the relatively large number of PET metrics reported in the literature, the selection of the best metric for fulfilling a specific task in a particular application is still a matter of debate. Quantitative PET has advanced elegantly during the last two decades and is now reaching the maturity required for clinical exploitation, particularly in oncology where it has the capability to open many avenues for clinical diagnosis, assessment of response to treatment and therapy planning. Therefore, the preservation and further enhancement of the quantitative features of PET imaging is crucial to ensure that the full clinical value of PET imaging modality is utilized in clinical oncology. Recent advancements in PET technology and methodology have paved the way for faster PET acquisitions of enhanced sensitivity to support the clinical translation of highly quantitative four-dimensional (4D) parametric imaging methods in clinical oncology. In this report, we provide an overview of recent advances and future trends in quantitative PET imaging in the context of clinical oncology. The pros/cons of the various image-derived PET metrics will be discussed and the promise of novel methodologies will be highlighted.

Optimization of a shorter variable-acquisition time for legs to achieve true whole-body PET/CT images

The present study aimed to qualitatively and quantitatively evaluate PET images as a function of acquisition time for various leg sizes, and to optimize a shorter variable-acquisition time protocol for legs to achieve better qualitative and quantitative accuracy of true whole-body PET/CT images. The diameters of legs to be modeled as phantoms were defined based on data derived from 53 patients. This study analyzed PET images of a NEMA phantom and three plastic bottle phantoms (diameter, 5.68, 8.54 and 10.7 cm) that simulated the human body and legs, respectively. The phantoms comprised two spheres (diameters, 10 and 17 mm) containing fluorine-18 fluorodeoxyglucose solution with sphere-to-background ratios of 4 at a background radioactivity level of 2.65 kBq/mL. All PET data were reconstructed with acquisition times ranging from 10 to 180, and 1200 s. We visually evaluated image quality and determined the coefficient of variance (CV) of the background, contrast and the quantitative %error of the hot spheres, and then determined two shorter variable-acquisition protocols for legs. Lesion detectability and quantitative accuracy determined based on maximum standardized uptake values (SUV_max) in PET images of a patient using the proposed protocols were also evaluated. A larger phantom and a shorter acquisition time resulted in increased background noise on images and decreased the contrast in hot spheres. A visual score of ≥ 1.5 was obtained when the acquisition time was ≥ 30 s for three leg phantoms, and ≥ 120 s for the NEMA phantom. The quantitative %errors of the 10- and 17-mm spheres in the leg phantoms were ± 15 and ± 10%, respectively, in PET images with a high CV (scan < 30 s). The mean SUV_max of three lesions using the current fixed-acquisition and two proposed variable-acquisition time protocols in the clinical study were 3.1, 3.1 and 3.2, respectively, which did not significantly differ. Leg acquisition time per bed position of even 30-90 s allows axial equalization, uniform image noise and a maximum ± 15% quantitative accuracy for the smallest lesion. The overall acquisition time was reduced by 23-42% using the proposed shorter variable than the current fixed-acquisition time for imaging legs, indicating that this is a useful and practical protocol for routine qualitative and quantitative PET/CT assessment in the clinical setting.

Quantification accuracy of neuro-oncology PET data as a function of emission scan duration in PET/MR compared to PET/CT

OBJECTIVES

To evaluate and compare the effect of reduced acquisition time, as a surrogate of injected activity, on the PET quantification accuracy in PET/CT and PET/MR imaging.

METHODS

Twenty min ¹⁸F-FDG phantom measurements and 10min ¹⁸F-FET brain scans were acquired in a Biograph-True-Point-True-View PET/CT (n=8) and a Biograph mMR PET/MR (n=16). Listmode data were repeatedly split into frames of 1min to 10min length and reconstructed using two different reconstruction settings of a 3D-OSEM algorithm: with post-filtering ("OSEM"), and without post-filtering but with resolution recovery ("PSF"). Recovery coefficients (RC_max, RC_A50) and standard uptake values (SUV_max, SUV_A50) were evaluated.

RESULTS

RC_max (phantom) and SUV_max (patients) increased significantly when reducing the frame duration. Significantly lower deviations were observed for RC_A50 and SUV_A50, respectively, making them more appropriate to compare PET studies at different number of counts. No statistical significant differences were observed when using post-filtering and reducing the frame time to 4min (RC_A50, reference 20min, phantom) and to 3min (SUV_A50, reference 10min, patients).

CONCLUSIONS

For hybrid aminoacid brain imaging, frame duration (or injected activity) can potentially be reduced to 30% of the standard used in clinical routine without significant changes on the quantification accuracy of the PET images if adequate reconstruction settings and quantitative measures are used. Frame times below 4min in the NEMA phantom are not advisable to obtain quantitative and reproducible measures.