Prostate Cancer Diffusion-Weighted Magnetic Resonance Imaging: Does the Choice of Diffusion-Weighting Level Matter?

Evaluation of multiplexed sensitivity encoding diffusion-weighted imaging in detecting uterine lesions: Image quality optimization

PURPOSE

To compare the image quality of multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) and single-shot echo-planar imaging (SS-EPI-DWI) techniques in uterine MRI.

METHODS

Eighty-eight eligible patients underwent MUSE-DWI and SS-EPI-DWI examinations simultaneously using a 3.0 T MRI system. Two radiologists independently performed quantitative and qualitative analysis of the two groups of images using a double-blind method. The weighted Kappa test was used to evaluate the interobserver agreement. Wilcoxon's rank sum test was used for qualitative parameters, and paired t-test was used for quantitative parameters. Spearman rank correlation analysis was used to obtained correlation between pathological results and mean apparent diffusion coefficient (ADC) value.

RESULTS

The qualitative and quantitative analysis of the images by the two radiologists were in good or excellent agreement, with weighted kappa value ranging from 0.636 to 0.981. The scores of total subjective image quality (15.4 ± 0.99) and signal-to-noise ratio (158.99 ± 60.71) of MUSE-DWI were significantly higher than those of SS-EPI-DWI (12.93 ± 1.62 P < 0.001; 130.23 ± 48.29 P < 0.05). It effectively reduced image distortion and artifact, and had better lesion conspicuity. There was no significant difference in contrast-to-noise ratio score and average ADC values between the two DWI sequences. The average ADC values of the two DWI sequences were highest in the normal uterus group and lowest in the endometrial cancer group, with statistically significant differences among groups (P < 0.01). In addition, the average ADC values of the two DWI sequences were negatively correlated with the type of lesions, decreasing with the malignancy of the lesions (r = -0.805 P < 0.01, r = -0.815 P < 0.01).

CONCLUSION

Compared to SS-EPI-DWI, MUSE-DWI can significantly reduce distortion, artifacts, and fuzziness in MRI of uterine lesions, which is more conducive to lesion detection.

Using deep learning to optimize the prostate MRI protocol by assessing the diagnostic efficacy of MRI sequences

PURPOSE

To explore diagnostic deep learning for optimizing the prostate MRI protocol by assessing the diagnostic efficacy of MRI sequences.

METHOD

This retrospective study included 840 patients with a biparametric prostate MRI scan. The MRI protocol included a T2-weighted image, three DWI sequences (b50, b400, and b800 s/mm2), a calculated ADC map, and a calculated b1400 sequence. Two accelerated MRI protocols were simulated, using only two acquired b-values to calculate the ADC and b1400. Deep learning models were trained to detect prostate cancer lesions on accelerated and full protocols. The diagnostic performances of the protocols were compared on the patient-level with the area under the receiver operating characteristic (AUROC), using DeLong's test, and on the lesion-level with the partial area under the free response operating characteristic (pAUFROC), using a permutation test. Validation of the results was performed among expert radiologists.

RESULTS

No significant differences in diagnostic performance were found between the accelerated protocols and the full bpMRI baseline. Omitting b800 reduced 53% DWI scan time, with a performance difference of + 0.01 AUROC (p = 0.20) and -0.03 pAUFROC (p = 0.45). Omitting b400 reduced 32% DWI scan time, with a performance difference of -0.01 AUROC (p = 0.65) and + 0.01 pAUFROC (p = 0.73). Multiple expert radiologists underlined the findings.

CONCLUSIONS

This study shows that deep learning can assess the diagnostic efficacy of MRI sequences by comparing prostate MRI protocols on diagnostic accuracy. Omitting either the b400 or the b800 DWI sequence can optimize the prostate MRI protocol by reducing scan time without compromising diagnostic quality.

Normal Brain and Brain Tumor ADC: Changes Resulting From Variation of Diffusion Time and/or Echo Time in Pulsed-Gradient Spin Echo Diffusion Imaging

OBJECTIVES

Increasing gradient performance on modern magnetic resonance imaging scanners has profoundly reduced the attainable diffusion and echo times for clinically available pulsed-gradient spin echo (PGSE) sequences. This study investigated how this may impact the measured apparent diffusion coefficient (ADC), which is considered an important diagnostic marker for differentiation between normal and abnormal brain tissue and for therapeutic follow-up.

MATERIALS AND METHODS

Diffusion time and echo time dependence of the ADC were evaluated on a high-performance 3 T magnetic resonance imaging scanner. Diffusion PGSE brain scans were performed in 10 healthy volunteers and in 10 brain tumor patients using diffusion times of 16, 40, and 70 ms, echo times of 60, 75, and 104 ms at 3 b-values (0, 100, and 1000 s/mm 2 ), and a maximum gradient amplitude of 68 mT/m. A low gradient performance system was also emulated by reducing the diffusion encoding gradient amplitude to 19 mT/m. In healthy subjects, the ADC was measured in 6 deep gray matter regions and in 6 white matter regions. In patients, the ADC was measured in the solid part of the tumor.

RESULTS

With increasing diffusion time, a small but significant ADC increase of up to 2.5% was observed for 6 aggregate deep gray matter structures. With increasing echo time or reduced gradient performance, a small but significant ADC decrease of up to 2.6% was observed for 6 aggregate white matter structures. In tumors, diffusion time-related ADC changes were inconsistent without clear trend. For tumors with diffusivity above 1.0 μm 2 /ms, with prolonged echo time, there was a pronounced ADC increase of up to 12%. Meanwhile, for tumors with diffusivity at or below 1.0 μm 2 /ms, no change or a reduction was observed. Similar results were observed for gradient performance reduction, with an increase of up to 21%. The coefficient of variation determined in repeat experiments was 2.4%.

CONCLUSIONS

For PGSE and the explored parameter range, normal tissue ADC changes seem negligible. Meanwhile, observed tumor ADC changes can be relevant if ADC is used as a quantitative biomarker and not merely assessed by visual inspection. This highlights the importance of reporting all pertinent timing parameters in ADC studies and of considering these effects when building scan protocols for use in multicenter investigations.

Quantitative diffusion MRI in prostate cancer: Image quality, what we can measure and how it improves clinical assessment

Diffusion-weighted imaging is a dependable method for detection of clinically significant prostate cancer. In prostate tissue, there are several compartments that can be distinguished from each other, based on different water diffusion decay signals observed. Alterations in cell architecture, such as a relative increase in tumor infiltration and decrease in stroma, will influence the observed diffusion signal in a voxel due to impeded random motion of water molecules. The amount of restricted diffusion can be assessed quantitatively by measuring the apparent diffusion coefficient (ADC) value. This is traditionally calculated using a monoexponential decay formula represented by the slope of a line produced between the logarithm of signal intensity decay plotted against selected b-values. However, the choice and number of b-values and their distribution, has a significant effect on the measured ADC values. There have been many models that attempt to use higher-order functions to better describe the observed diffusion signal decay, requiring an increased number and range of b-values. While ADC can probe heterogeneity on a macroscopic level, there is a need to optimize advanced diffusion techniques to better interrogate prostate tissue microstructure. This could be of benefit in clinical challenges such as identifying sparse tumors in normal prostate tissue or better defining tumor margins. This paper reviews the principles of diffusion MRI and novel higher order diffusion signal analysis techniques to improve the detection of prostate cancer.

Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator

Background and purpose

Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated.

Materials and methods

Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints.

Results

Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL.

Conclusions

The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.

Improving diagnostic efficacy of primary prostate cancer with combined 99mTc-PSMA SPECT/CT and multiparametric-MRI and quantitative parameters

Purpose

This prospective study aimed to evaluate the difference between 99mTc-PSMA single-photon emission computed tomography (SPECT)/CT and multiparametric magnetic resonance imaging (mpMRI) in the detection of primary prostate cancer (PCa).

Materials and methods

Fifty-six men with suspected PCa between October 2019 and November 2022 were prospectively enrolled in this study. The median age of the patients was 70 years (range, 29-87 years). Patients were divided into high-(Gleason score>7, n=31), medium- (Gleason score=7, n=6) and low-risk groups (Gleason score < 7, n=6). All patients underwent 99mTc-PSMA SPECT/CT and mpMRI at an average interval of 3 days (range, 1-7 days). The maximum standardized uptake value (SUVmax), the minimum apparent diffusion coefficient (ADCmin), and their ratio (SUVmax/ADCmin) were used as imaging parameters to distinguish benign from malignant prostatic lesions.

Results

Of the 56 patients, 12 were pathologically diagnosed with a benign disease, and 44 were diagnosed with PCa. 99mTc-PSMA SPECT/CT and mpMRI showed no significant difference in the detection of primary PCa (kappa =0.401, P=0.002), with sensitivities of 97.7% (43/44) and 90.9% (40/44), specificities of 75.0% (9/12) and 75.0% (9/12), and AUC of 97.4% and 95.1%, respectively. The AUC of SUVmax/ADCmin was better than those of SUVmax or ADCmin alone. When SUVmax/ADCmin in the prostatic lesion was >7.0×103, the lesion was more likely to be malignant. When SUVmax/ADCmin in the prostatic lesion is >27.0×103, the PCa patient may have lymph node and bone metastases. SUVmax was positively correlated with the Gleason score (r=0.61, P=0.008), whereas ADCmin was negatively correlated with the Gleason score (r=-0.35, P=0.023). SUVmax/ADCmin was positively correlated with the Gleason score (r=0.59, P=0.023). SUVmax/ADCmin was the main predictor of the high-risk group, with an optimal cut-off value of 15.0×103.

Conclusions

The combination of 99mTc-PSMA SPECT/CT and mpMRI can improve the diagnostic efficacy for PCa compared with either modality alone; SUVmax/ADCmin is a valuable differential diagnostic imaging parameter.

Truly reproducible uniform estimation of the ADC with multi-b diffusion data- Application in prostate diffusion imaging

PURPOSE

The ADC is a well-established parameter for clinical diagnostic applications, but lacks reproducibility because it is also influenced by the choice diffusion weighting level. A framework is evaluated that is based on multi-b measurement over a wider range of diffusion-weighting levels and higher order tissue diffusion modeling with retrospective, fully reproducible ADC calculation.

METHODS

Averaging effect from curve fitting for various model functions at 20 linearly spaced b-values was determined by means of simulations and theoretical calculations. Simulation and patient multi-b image data were used to compare the new approach for diffusion-weighted image and ADC map reconstruction with and without Rician bias correction to an active clinical trial protocol probing three non-zero b-values.

RESULTS

Averaging effect at a certain b-value varies for model function and maximum b-value used. Images and ADC maps from the novel procedure are on-par with the clinical protocol. Higher order modeling and Rician bias correction is feasible, but comes at the cost of longer computation times.

CONCLUSIONS

Application of the new framework makes higher order modeling more feasible in a clinical setting while still providing patient images and reproducible ADC maps of adequate quality.

Reproducibility of apparent diffusion coefficient measurement in normal prostate peripheral zone at 1.5T MRI

PURPOSE

The purpose of this study was to quantify the influence of factors of variability on apparent diffusion coefficient (ADC) estimation in the normal prostate peripheral zone (PZ).

MATERIALS AND METHODS

Fifty healthy volunteers underwent in 2017 (n = 17) or 2020 (n = 33) two-point (0, 800 s/mm²) prostate diffusion-weighted imaging in the morning on 1.5 T scanners A and B from different manufacturers. Additional five-point (50, 150, 300, 500, 800 s/mm²) acquisitions were performed on scanner B in the morning and evening. ADC was measured in PZ at midgland using ADC maps reconstructed with various b-value combinations. ADC distributions from 2017 and 2020 were compared using Wilcoxon rank sum test. ADC obtained in the same volunteers were compared using Bland Altman methodology. The 95% confidence interval upper limit of the repeatability/reproducibility coefficient defined the lowest detectable ADC difference.

RESULTS

Forty-nine participants with a mean age of 24.6 ± 3.8 [SD] years (range: 21-37 years) were finally included. ADC distributions from 2017 and 2020 were not significantly different and were combined. Despite high individual variability, there was no significant bias (10 × 10^-6 mm²/s, P = 0.58) between ADC measurements made on both scanners. On scanner B, differences in lowest b-values chosen within the 0-500 s/mm² range for two-point ADC computation induced significant biases (56-109 × 10^-6 mm²/s, P < 0.0001). ADC was significantly lower in the morning (bias: 33 × 10^-6 mm²/s, P = 0.006). The number of b-values had little influence on ADC values. The lowest detectable ADC difference varied from 85 × 10^-6 to 311 × 10^-6 mm²/s across scanners, b-value combinations and periods of the day.

CONCLUSIONS

The MRI scanner, the lowest b-value used and the period of the day induce substantial variability in ADC computation.

Brain diffusion MRI with multiplexed sensitivity encoding for reduced distortion in a pediatric patient population

BACKGROUND

Diffusion-weighted imaging (DWI) is a valuable tool for routine imaging of the pediatric brain. However, the commonly used single-shot (ss) echo-planar imaging (EPI) DWI sequence is prone to geometric distortions and T₂*-blurring. This study aimed to investigate in a pediatric population the benefits of using multiplexed sensitivity-encoding (MUSE) without and with reversed polarity gradients (RPG) instead.

METHODS

This retrospective study compared image quality, geometric distortions, and diffusion values between three different approaches for DWI (ssEPI, MUSE, and RPG-MUSE) in 14 patients (median age = 4 (0.6-15) years, 11 males). Distortion levels were quantified and compared in two brain regions, i.e., the brain stem and the temporal lobes, using the Dice Coefficient and the Hausdorff Distance, with T₂-weighted images as reference. Expected geometrical distortion was further evaluated by comparing the effective echo spacing between the DWI sequences. Apparent diffusion coefficient (ADC) values were determined in the genu of the corpus callosum and the optic nerves. Two raters graded overall image quality and image distortions on a Likert scale.

RESULTS

Distortion levels assessed with Dice coefficient and Hausdorff distance were significantly lower for MUSE (p < 0.05) and RPG-MUSE (p < 0.01) compared to ssEPI. No significant difference in ADC values was observed between methods. The RPG-MUSE method was graded by one rater as significantly higher in overall image quality than ssEPI (p < 0.05) and by both raters as significantly lower in levels of image distortions than both MUSE (p < 0.05) and ssEPI (p < 0.05). These results were in agreement with the reduced effective echo spacing was that was attained with MUSE and RPG-MUSE.

CONCLUSION

For imaging of the pediatric brain, MUSE and even more so RPG-MUSE offers both improved geometric fidelity and image quality compared to ssEPI.