Quantitative effects of acquisition duration and temporal resolution on the measurement accuracy of prostate dynamic contrast-enhanced MRI data: a phantom study

Knight, Silvin P.; Browne, Jacinta E.; Meaney, James F.; Fagan, Andrew

doi:10.1007/s10334-017-0619-y

Cited by 9 publications

(8 citation statements)

References 32 publications

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“…In the present study, it was found that T res had a strong effect of on certain phenomenological AIF curve‐shape features, namely: TTP1 , TTP2 , P1 , P2 , and Wash‐in Slope (0– TTP1 ), and these errors in AIF measurement were shown to propagate though to errors in certain PK parameter estimations. K trans and k ep values were both strongly affected by the T res , particularly at T res values > 15 s. T res had little effect on the measurement of the AIF Wash‐out Slope (60–360 s), as well as v e estimations; this is in line with previously published works . The use of a LLS regime to fit the standard Tofts model, rather than the more traditionally used NLS approach, was found to almost double the accuracy of K trans estimates, and provided an increase in K trans (intrasession) and k ep (intra‐ and intersession) precision of ~4%.…”

Section: Discussionsupporting

confidence: 86%

“…K trans and k ep values were both strongly affected by the T res , particularly at T res values > 15 s. T res had little effect on the measurement of the AIF Wash-out Slope (60-360 s), as well as v e estimations; this is in line with previously published works. [38][39][40] The use of a LLS regime to fit the standard Tofts model, rather than the more traditionally used NLS approach, was found to almost double the accuracy of K trans estimates, and provided an increase in K trans (intrasession) and k ep (intra-and intersession) precision of~4%. The accuracy of the LLS approach was also shown to have lower dependence on the T res used.…”

Section: Discussionmentioning

confidence: 97%

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DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits

2019

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Purpose To quantify the effects of DCE acquisition and pharmacokinetic modeling processing methodologies on the absolute accuracy and precision of derived pharmacokinetic (PK) parameter values using a novel anthropomorphic phantom test device in which “ground truth” values were known a priori. Methods Ground truth arterial input function (AIF), tumor, and healthy tissue contrast agent concentration‐time curves (CTCs) were established within the phantom and repeatedly measured on a 3T MRI scanner with varying temporal resolution (Tres = 1.22–30.6 s). Ground truth CTCs, Ktrans, ve, and kep values were directly compared to measured values as a function of Tres, with and without the application of voxel‐wise flip‐angle corrections applied to the data and PK modeling performed using linear and nonlinear forms of the standard Tofts model. Results Measurement of the AIF was strongly affected by the Tres used (AIF curve‐shape feature errors: 3%–222% for Tres: 1.22–30.6 s), which directly translated to errors in the derived Ktrans, ve, and kep values of 1%–24%, 2%–5%, and 1%–26% respectively across this Tres range (flip‐angle correction applied). Further appreciable improvements in accuracy and precision arising from the use of flip angle corrections and nonlinear least squares fitting were quantified and used to identify optimal acquisition and analysis methodologies for which measurement errors could be constrained below threshold levels. Conclusion This quantitative study provides insight into how errors in AIF measurement propagate to errors in PK parameter outputs. Absolute quantification of the accuracy and precision of MR‐measured CTCs, and resultant PK parameter values, allowed for an optimal temporal resolution to be defined commensurate with maintaining Ktrans, ve, and kep measurement errors below 5% and 10% levels. An appreciable gain in PK parameter estimation accuracy at the analysis stage was also demonstrated using flip‐angle corrections and a linear approach to PK model fitting.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 97%

DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits

2019

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“…Finally, the data were downsampled by discarding frames without changing the image quality. In practice, the longer scan time could be used to improve the SNR, spatial resolution and/or field of view. Larsson et al chose to downsample by averaging frames, leading to improved SNR, and found errors within 15% for temporal resolutions faster than 20 s with the ETM on 101 DCE‐MRI examinations.…”

Section: Discussionmentioning

confidence: 99%

An extended reference region model for DCE‐MRI that accounts for plasma volume

Ahmed

Levesque

2018

NMR in Biomedicine

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The reference region model (RRM) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides pharmacokinetic parameters without requiring the arterial input function. A limitation of the RRM is that it assumes that the blood plasma volume in the tissue of interest is zero, but this is often not true in highly vascularized tissues, such as some tumours. This study proposes an extended reference region model (ERRM) to account for tissue plasma volume. Furthermore, ERRM was combined with a two-fit approach to reduce the number of fitting parameters, and this was named the constrained ERRM (CERRM). The accuracy and precision of RRM, ERRM and CERRM were evaluated in simulations covering a range of parameters, noise and temporal resolutions. These models were also compared with the extended Tofts model (ETM) on in vivo glioblastoma multiforme data. In simulations, RRM overestimated K by over 10% at v = 0.01 under noiseless conditions. In comparison, ERRM and CERRM were both accurate, with CERRM showing better precision when noise was included. On in vivo data, CERRM provided maps that had the highest agreement with ETM, whilst also being robust at temporal resolutions as poor as 30 s. ERRM can provide pharmacokinetic parameters without an arterial input function in tissues with non-negligible v where RRM provides inaccurate estimates. The two-fit approach, named CERRM, further improves on the accuracy and precision of ERRM.

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“…No difference was found in the AUC of the ROC curve for the two protocols that diagnosed TZ lesions, although prior research found a higher specificity and accuracy for PI-RADS v2 [28][29][30][31]. Whether DCE could be used in microvascular anatomy and functional evaluation to improve the detection specificity and accuracy for TZ lesions needs further study [32][33][34][35].…”

Section: Diagnostic Performance Comparison In Tzmentioning

confidence: 86%

Diagnostic Performance of PI-RADS v2, Proposed Adjusted PI-RADS v2 and Biparametric Magnetic Resonance Imaging for Prostate Cancer Detection: A Preliminary Study

et al. 2021

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Purpose: To evaluate the diagnostic performance of PI-RADS v2, proposed adjustments to PI-RADS v2 (PA PI-RADS v2) and biparametric magnetic resonance imaging (MRI) for prostate cancer detection. Methods: A retrospective cohort of 224 patients with suspected prostate cancer was included from January 2016 to November 2018. All the patients underwent a multi-parametric MR scan before biopsy. Two radiologists independently evaluated the MR examinations using PI-RADS v2, PA PI-RADS v2, and a biparametric MRI protocol, respectively. Receiver operating characteristic (ROC) curves for the three different protocols were drawn. Results: In total, 90 out of 224 cases (40.18%) were pathologically diagnosed as prostate cancer. The area under the ROC curves (AUC) for diagnosing prostate cancers by biparametric MRI, PI-RADS v2, and PA PI-RADS v2 were 0.938, 0.935, and 0.934, respectively. For cancers in the peripheral zone (PZ), the diagnostic sensitivity was 97.1% for PI-RADS v2/PA PI-RADS v2 and 96.2% for biparametric MRI. Moreover, the specificity was 84.0% for biparametric MRI and 58.0% for PI-RADS v2/PA PI-RADS v2. For cancers in the transition zone (TZ), the diagnostic sensitivity was 93.4% for PA PI-RADS v2 and 88.2% for biparametric MRI/PI-RADS v2. Furthermore, the specificity was 95.4% for biparametric MRI/PI-RADS v2 and 78.0% for PA PI-RADS v2. Conclusions: The overall diagnostic performance of the three protocols showed minimal differences. For lesions assessed as being category 3 using the biparametric MRI protocol, PI-RADS v2, or PA PI-RADS v2, it was thought prostate cancer detection could be improved. Attention should be paid to false positive results when PI-RADS v2 or PA PI-RADS v2 are used.

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Quantitative effects of acquisition duration and temporal resolution on the measurement accuracy of prostate dynamic contrast-enhanced MRI data: a phantom study

Abstract: Errors in measured wash-in, wash-out, K , and v parameters were minimised using T ≤ 8.1 s and AD ≥ 360 s, with large errors recorded outside of this range.

Cited by 9 publications

References 32 publications

DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits

DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits

An extended reference region model for DCE‐MRI that accounts for plasma volume

Diagnostic Performance of PI-RADS v2, Proposed Adjusted PI-RADS v2 and Biparametric Magnetic Resonance Imaging for Prostate Cancer Detection: A Preliminary Study

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