Repeatability of Quantitative Diffusion-Weighted Imaging Metrics in Phantoms, Head-and-Neck and Thyroid Cancers: Preliminary Findings

Validation of quantitative magnetic resonance imaging techniques in head and neck healthy structures involved in the salivary and swallowing function: Accuracy and repeatability

Background and Purpose

Radiation-induced damage to the organs at risk (OARs) in head-and-neck cancer (HNC) patient can result in long-term complications. Quantitative magnetic resonance imaging (qMRI) techniques such as diffusion-weighted imaging (DWI), DIXON for fat fraction (FF) estimation and T2 mapping could potentially provide a spatial assessment of such damage. The goal of this study is to validate these qMRI techniques in terms of accuracy in phantoms and repeatability in-vivo across a broad selection of healthy OARs in the HN region.

Materials and Methods

Scanning was performed at a 3 T diagnostic MRI scanner, including the calculation of apparent diffusion coefficient (ADC) from DWI, FF and T2 maps. Phantoms were scanned to estimate the qMRI techniques bias using Bland-Altman statistics. Twenty-six healthy subjects were scanned twice in a test-retest study to determine repeatability. Repeatability coefficients (RC) were calculated for the parotid, submandibular, sublingual and tubarial salivary glands, oral cavity, pharyngeal constrictor muscle and brainstem. Additionally, a linear mixed-effect model analysis was used to evaluate the effect of subject-specific characteristics on the qMRI values.

Results

Bias was 0.009x10-3 mm2/s for ADC, -0.7 % for FF and -7.9 ms for T2. RCs ranged 0.11-0.25x10-3 mm2/s for ADC, 1.2-6.3 % for FF and 2.5-6.3 ms for T2. A significant positive linear relationship between age and the FF and T2 for some of the OARs was found.

Conclusion

These qMRI techniques are feasible, accurate and repeatable, which is promising for treatment response monitoring and/or differentiating between healthy and unhealthy tissues due to radiation-induced damage in HNC patients.

Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners

BACKGROUND

The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy.

PURPOSE

To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners.

STUDY TYPE

Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings.

POPULATION/PHANTOMS

NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils.

ASSESSMENT

SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts.

STATISTICAL TESTS

QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level.

RESULTS

The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3  mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3  mm2 /sec with up to 0.2 × 10-3  mm2 /sec of bias.

DATA CONCLUSION

ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Delivering a Quantitative Imaging Agenda

In a digital image, each voxel contains quantitative information dependent on the technique used to generate the image [...].

Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers

INTRODUCTION

Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms.

METHODS

Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom.

RESULTS

In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE.

CONCLUSION

MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.

Validating the accuracy of multispectral metal artifact suppressed diffusion-weighted imaging

BACKGROUND

Diffusion-weighted imaging (DWI) provides quantitative measurement of random water displacement in tissue as calculated by the apparent diffusion coefficient (ADC). While heavily utilized in stroke and oncology applications, DWI is a promising tool to map microstructural changes in musculoskeletal applications including evaluation of synovial reactions resulting from total hip arthroplasty (THA). One major challenge facing the application of DWI in THA is the significant artifacts related to the conventional echo-planar imaging (EPI) readout used. Multispectral imaging (MSI) techniques, including the multiacquisition with variable resonance image combination (MAVRIC), have been shown to effectively reduce metallic susceptibility artifacts around total joint replacements to render clinically useful images. Recently, a 2D periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) FSE acquisition that incorporates a diffusion preparation pulse with 2D-MAVRIC has been developed to mitigate both distortion and dropout artifacts. While there have been some preliminary assessments of DWI-MAVRIC, the repeatability of DWI-MAVRIC and the effects of key parameters, such as the number of spectral bins, are unknown.

PURPOSE

To evaluate the quantitative accuracy of DWI-MAVRIC as compared to conventional diffusion sequences.

METHODS

A diffusion phantom with different reference diffusivities (ADC = 113-1123 μm2 /s) was used. Scans were performed on two 1.5T MRI scanners. DWI-EPI and DWI-MAVRIC were acquired in both the axial and coronal planes. Three spatial offsets (0 cm, 10 cm left, and 10 cm right off iso-center) were used to evaluate effects of off-isocenter positioning. To assess intraday and interday repeatability, DWI-EPI and DWI-MAVRIC acquisitions were repeated on one scanner at same-day and 9-month intervals. To assess inter-scanner repeatability, DWI-EPI and DWI-MAVRIC acquisitions were compared between two scanners. ADC maps were generated with and without gradient nonlinearity correction (GNC). Linear regression, correlation, and error statistics were determined between calculated and reference ADC values. Bland-Altman plots were generated to evaluate intraday, interday, and interscanner repeatability.

RESULTS

DWI-MAVRIC had excellent correlation to reference values but at reduced linearity (r = 1.00, slope = 0.91-0.94) as compared to DWI-EPI (r = 1.00, slope = 0.99-1.01). A greater than 5% ADC bias was observed at the lowest ADC values, predominantly in the DWI-MAVRIC scans. ADC values did not vary with DWI-MAVRIC parameters. DWI-EPI acquisitions had intraday, interday, and interscanner repeatability of 3.18 μm2 /s, 19.2 μm2 /s, and 20.2 μm2 /s, respectively. DWI-MAVRIC acquisitions had inferior intraday, interday, and interscanner repeatability of 13.3 μm2 /s, 44.7 μm2 /s, 110 μm2 /s, respectively. Lower ADC errors were found at isocenter, as compared to the left and right positions. GNC reduced the absolute error by 0.31% ± 0.89%, 3.6% ± 1.4%, 0.65% ± 2.4% for the center, left, and right positions, respectively.

CONCLUSIONS

DWI-MAVRIC provides good linearity with respect to reference values and good intra- and interday repeatability.

Repeatability of diffusion-weighted magnetic resonance imaging in head and neck cancer at a 1.5 T MR-Linac

BACKGROUND AND PURPOSE

Functional information acquired through diffusion-weighted magnetic resonance imaging (DW-MRI) may be beneficial for personalized head and neck cancer (HNC) radiotherapy. Technical validation is required before DW-MRI based radiotherapy interventions can be realized clinically. The aim of this study was to assess the repeatability of apparent diffusion coefficients (ADC) derived from DW-MRI in HNC using echo-planar imaging (EPI) on a 1.5 T MR-Linac.

MATERIAL AND METHODS

A total of eleven HNC patients underwent test/retest DW-MRI scans at least once per week during fractionated radiotherapy at the MR-Linac. An EPI DW-MRI test scan (b=0, 150, 500 s/mm²) was acquired before the start of adaptive MR-guided radiotherapy in addition to an identical retest scan after irradiation. Volumes-of-interest (VOI) were defined manually for parotid (PTs) and submandibular glands (SMs), gross tumor volume (GTV) and lymph nodes (LNs). Mean ADC was calculated for all VOI in all test/retest scans. Absolute/relative repeatability coefficients (RCs/relRCs) as well as intraclass correlation coefficients (ICCs) were determined for all VOI.

RESULTS

A total of 81 datasets were analyzed. Mean test ADC values were 1380/1416, 950/1010, 1520 and 1344·10^-6 mm²/s for left/right SM and PT, GTV and LNs, respectively. Accordingly, RC (relRC) values were determined as 271/281 (19.4/21.8%) and 138/155 (13.3/15.2%), 457 (31.3%) and 310·10^-6 mm²/s (23.5%). ICC resulted in 0.80/0.87, 0.97/0.94, 0.75 and 0.83 for left/right SM and PT, GTV and LNs, respectively.

CONCLUSION

The repeatability of ADC derived from EPI DW-MRI at the 1.5 T MR-Linac appears reasonable to be used for future biologically adapted MR-guided radiotherapy.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness

BACKGROUND

Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease.

PURPOSE

To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms.

STUDY TYPE

Prospective.

POPULATION

Thirty-three patients prospectively imaged prior to prostatectomy.

FIELD STRENGTH/SEQUENCE

3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence.

ASSESSMENT

Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC).

STATISTICAL TEST

Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant.

RESULTS

The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size.

DATA CONCLUSION

We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

Conformance of a 3T Radiotherapy MRI Scanner to the QIBA Diffusion Profile

Purpose

To assess the technical performance of the apparent diffusion coefficient (ADC) on a dedicated 3T radiotherapy scanner, using a standardized phantom and sequences. Investigations into factors that could impact the technical performance of ADC in the clinic were also completed, including changing the slice‐encoded imaging direction and the reference sample ADC value.

Methods

ADC acquisitions were performed monthly on an isotropic diffusion phantom over 1 year. Measurements of ADC %bias, coefficients of variation for short‐/long‐term repeatability and precision (CV_ST/CV_LT and CV_P), and b‐value dependency (Dep_b) were calculated. The measurements were then assessed according to the Quantitative Imaging Biomarker Alliance (QIBA) Diffusion Profile specifications.

Results

The average of all measurements over the year was within Profile recommended ranges. This included when testing was performed in different imaging directions, and on samples that had different ADC reference values (0.4–1.1 μm²/ms). Results in the axial plane for the central water vial included a bias of +0.05%, CV_ST /CV_LT/CV_P = 0.1%/ 0.9%/0.4% and Dep_b = 0.4%.

Conclusions

The technical performance of ADC on a radiotherapy dedicated MRI scanner over the course of 12 months was considered conformant to the QIBA Profile. Quantifying these metrics and factors that may affect the performance is essential in progressing the use of ADC clinically: ensuring that the observed change of ADC in a tissue is due to a physiological response and not measurement variability.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma

RATIONALE AND OBJECTIVES

Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression.

MATERIALS AND METHODS

We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRM_rFLAIR+), decreased (PRM_rFLAIR-), or unchanged (PRM_rFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRM_rFLAIR between weeks 10 and 20 and continuously until the PRM_rFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection.

RESULTS

Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRM_rFLAIR+ (PFS: p <0.01; OS: p <0.001). PRM_rFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRM_rFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001).

CONCLUSION

PRM_rFLAIR may provide an early biomarker of disease progression in glioblastoma.

Longitudinal Monitoring of Simulated Interstitial Fluid Pressure for Pancreatic Ductal Adenocarcinoma Patients Treated with Stereotactic Body Radiotherapy

Simple Summary

High vessel permeability, poor perfusion, low lymphatic drainage, and dense abundant stroma elevate interstitial fluid pressures (IFP) in pancreatic ductal adenocarcinoma (PDAC). The present study aims to monitor longitudinal changes in simulated tumor IFP and velocity (IFV) values using a dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) approach in PDAC. Nine PDAC patients underwent DCE-MRI acquisition on a 3-Tesla MRI scanner at pre-treatment (TX (0)), immediately after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation using the Starling Principle of fluid exchange and Darcy velocity–pressure relationship was solved in COMSOL Multiphysics software to generate IFP and IFV parametric maps using relevant tumor tissue physiological parameters. Initial results suggest that after validation, IFP and IFV can be imaging biomarkers of early response to therapy that may guide precision medicine in PDAC.

Abstract

The present study aims to monitor longitudinal changes in simulated tumor interstitial fluid pressure (IFP) and velocity (IFV) values using dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) in pancreatic ductal adenocarcinoma (PDAC) patients. Nine PDAC patients underwent MRI, including DCE-MRI, on a 3-Tesla MRI scanner at pre-treatment (TX (0)), after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation, incorporating the Starling Principle of fluid exchange, Darcy velocity, and volume transfer constant (K^trans), was solved in COMSOL Multiphysics software to generate IFP and IFV maps. Tumor volume (V_t), K^trans, IFP, and IFV values were compared (Wilcoxon and Spearman) between the time- points. D2-TX K^trans values were significantly different from pre-TX and D1-TX (p < 0.05). The D1-TX and pre-TX mean IFV values exhibited a borderline significant difference (p = 0.08). The IFP values varying <3.0% between the three time-points were not significantly different (p > 0.05). V_t and IFP values were strongly positively correlated at pre-TX (ρ = 0.90, p = 0.005), while IFV exhibited a strong negative correlation at D1-TX (ρ = −0.74, p = 0.045). V_t, K^trans, IFP, and IFV hold promise as imaging biomarkers of early response to therapy in PDAC.

Application of Community Detection Algorithm to Investigate the Correlation between Imaging Biomarkers of Tumor Metabolism, Hypoxia, Cellularity, and Perfusion for Precision Radiotherapy in Head and Neck Squamous Cell Carcinomas

The present study aimed to investigate the correlation at pre-treatment (TX) between quantitative metrics derived from multimodality imaging (MMI), including 18F-FDG-PET/CT, 18F-FMISO-PET/CT, DW- and DCE-MRI, using a community detection algorithm (CDA) in head and neck squamous cell carcinoma (HNSCC) patients. Twenty-three HNSCC patients with 27 metastatic lymph nodes underwent a total of 69 MMI exams at pre-TX. Correlations among quantitative metrics derived from FDG-PET/CT (SUL), FMSIO-PET/CT (K1, k3, TBR, and DV), DW-MRI (ADC, IVIM [D, D*, and f]), and FXR DCE-MRI [Ktrans, ve, and τi]) were investigated using the CDA based on a "spin-glass model" coupled with the Spearman's rank, ρ, analysis. Mean MRI T2 weighted tumor volumes and SULmean values were moderately positively correlated (ρ = 0.48, p = 0.01). ADC and D exhibited a moderate negative correlation with SULmean (ρ ≤ -0.42, p < 0.03 for both). K1 and Ktrans were positively correlated (ρ = 0.48, p = 0.01). In contrast, Ktrans and k3max were negatively correlated (ρ = -0.41, p = 0.03). CDA revealed four communities for 16 metrics interconnected with 33 edges in the network. DV, Ktrans, and K1 had 8, 7, and 6 edges in the network, respectively. After validation in a larger population, the CDA approach may aid in identifying useful biomarkers for developing individual patient care in HNSCC.

Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group

Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.

Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial

Mean tumor apparent diffusion coefficient (ADC) of breast cancer showed excellent repeatability but only moderate predictive power for breast cancer therapy response in the ACRIN 6698 multicenter imaging trial. Previous single-center studies have shown improved predictive performance for alternative ADC histogram metrics related to low ADC dense tumor volume. Using test/retest (TT/RT) 4 b-value diffusion-weighted imaging acquisitions from pretreatment or early-treatment time-points on 71 ACRIN 6698 patients, we evaluated repeatability for ADC histogram metrics to establish confidence intervals and inform predictive models for future therapy response analysis. Histograms were generated using regions of interest (ROIs) defined separately for TT and RT diffusion-weighted imaging. TT/RT repeatability and intra- and inter-reader reproducibility (on a 20-patient subset) were evaluated using wCV and Bland–Altman limits of agreement for histogram percentiles, low-ADC dense tumor volumes, and fractional volumes (normalized to total histogram volume). Pearson correlation was used to reveal connections between metrics and ROI variability across the sample cohort. Low percentiles (15th and 25th) were highly repeatable and reproducible, wCV < 8.1%, comparable to mean ADC values previously reported. Volumetric metrics had higher wCV values in all cases, with fractional volumes somewhat better but at least 3 times higher than percentile wCVs. These metrics appear most sensitive to ADC changes around a threshold of 1.2 μm²/ms. Volumetric results were moderately to strongly correlated with ROI size. In conclusion, Lower histogram percentiles have comparable repeatability to mean ADC, while ADC-thresholded volumetric measures currently have poor repeatability but may benefit from improvements in ROI techniques.

Diffusion-Weighted and Dynamic Contrast-Enhanced MRI Derived Imaging Metrics for Stereotactic Body Radiotherapy of Pancreatic Ductal Adenocarcinoma: Preliminary Findings

We aimed to assess longitudinal changes in quantitative imaging metric values obtained from diffusion-weighted (DW-) and dynamic contrast-enhanced magnetic resonance imaging (DCE)-MRI at pre-treatment (TX[0]), immediately after the first fraction of stereotactic body radiotherapy (D1-TX[1]), and 6 weeks post-TX (Post-TX[2]) in patients with pancreatic ductal adenocarcinoma. Ten enrolled patients (n = 10) underwent DW- and DCE-MRI examinations on a 3.0 T scanner. The apparent diffusion coefficient, ADC (mm²/s), was derived from DW imaging data using a monoexponential model. The tissue relaxation rate, R _1t, time-course data were fitted with a shutter-speed model, which provides estimates of the volume transfer constant, K ^trans (min^-1), extravascular extracellular volume fraction, v_e , and mean lifetime of intracellular water protons, τ _i (seconds). Wilcoxon rank-sum test compared the mean values, standard deviation, skewness, kurtosis, and relative percentage (r, %) changes (Δ) in ADC, K ^trans, v_e , and τ _i values between the magnetic resonance examinations. rADC_Δ2-0 values were significantly greater than rADC_Δ1-0 values (P = .009). rK ^trans _Δ2-0 values were significantly lower than rK ^trans _Δ1-0 values (P = .048). rv_{e Δ2-1} and rv_eΔ2-0 values were significantly different (P = .016). rτ _{i Δ2-1} values were significantly lower than rτ _{i Δ2-0} values (P = .008). For group comparison, the pre-TX mean and kurtosis of ADC (P = .18 and P = .14), skewness and kurtosis of K ^trans values (P = .14 for both) showed a leaning toward significant difference between patients who experienced local control (n = 2) and failed early (n = 4). DW- and DCE-MRI-derived quantitative metrics could be useful biomarkers to evaluate longitudinal changes to stereotactic body radiotherapy in patients with pancreatic ductal adenocarcinoma.

Apparent diffusion coefficient measurement using thin-slice diffusion-weighted magnetic resonance imaging: assessment of measurement errors and repeatability

We investigated the measurement error and repeatability of the apparent diffusion coefficient (ADC) obtained using thin-slice imaging. Diffusion-weighted images of an ice-water phantom were acquired using 1.5-T and 3.0-T scanners with 1-, 3-, and 5-mm thickness. ADC maps were generated at b = 0 and 1000 mm²/s using five consecutive scans. Measurement errors were assessed with accuracy and precision. Repeatability was assessed using the within-subject coefficient of variation. The ADC accuracy of both scanners agreed with the ADC of water at 0 °C. At 1-mm, precisions were 2.9% and 8.4% for the 3.0-T and 1.5-T scanners, respectively. The repeatabilities of 1-mm thickness were 1.3% and 3.4% in the 3.0-T and 1.5-T scanners, respectively. The 3.0-T scanner showed acceptable measurement errors and moderate repeatability compared with Quantitative Imaging Biomarkers Alliance recommendation. A 3.0-T scanner can be used for reliable ADC measurement, even with a 1-mm thickness at a reasonable scan time.

Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck: Bayesian probability versus neural network

Purpose

The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least‐squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM‐NET, and a version of the neural network modified to increase consistency, IVIM‐NET_mod.

Methods

Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient Dt, perfusion fraction fp, and pseudo‐diffusion coefficient Dp) from each fit method were determined in the tonsils and in the pterygoid muscles. Within‐subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance.

Results

The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of Dt in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM‐NET, and 11.2% for IVIM‐NET_mod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM‐NET were 15% for both Dt and fp, and 94% for Dp; for IVIM‐NET_mod, these values improved to 5%, 9%, and 62%, respectively.

Conclusion

Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck.

Diffusion and Perfusion MRI Predicts Response Preceding and Shortly After Radiosurgery to Brain Metastases: A Pilot Study

BACKGROUND AND PURPOSE

To determine the ability of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict long-term response of brain metastases prior to and within 72 hours of stereotactic radiosurgery (SRS).

METHODS

In this prospective pilot study, multiple b-value DWI and T1-weighted DCE-MRI were performed in patients with brain metastases before and within 72 hours following SRS. Diffusion-weighted images were analyzed using the monoexponential and intravoxel incoherent motion (IVIM) models. DCE-MRI data were analyzed using the extended Tofts pharmacokinetic model. The parameters obtained with these methods were correlated with brain metastasis outcomes according to modified Response Assessment in Neuro-Oncology Brain Metastases criteria.

RESULTS

We included 25 lesions from 16 patients; 16 patients underwent pre-SRS MRI and 12 of 16 patients underwent both pre- and early (within 72 hours) post-SRS MRI. The perfusion fraction (f) derived from IVIM early post-SRS was higher in lesions demonstrating progressive disease than in lesions demonstrating stable disease, partial response, or complete response (q = .041). Pre-SRS extracellular extravascular volume fraction, v_e , and volume transfer coefficient, K^trans , derived from DCE-MRI were higher in nonresponders versus responders (q = .041).

CONCLUSIONS

Quantitative DWI and DCE-MRI are feasible imaging methods in the pre- and early (within 72 hours) post-SRS evaluation of brain metastases. DWI- and DCE-MRI-derived parameters demonstrated physiologic changes (tumor cellularity and vascularity) and offer potentially useful biomarkers that can predict treatment response. This allows for initiation of alternate therapies within an effective time window that may help prevent disease progression.

Quantitative Imaging Enters the Clinical Arena: A Personal Viewpoint

The National Cancer Institute's Quantitative Imaging Network (QIN) has thrived over the past 12 years with an emphasis on the development of image-based decision support software tools for improving measurements of imaging metrics. An overarching goal has been to develop advanced tools that could be translated into clinical trials to provide for improved prediction of response to therapeutic interventions. This article provides an overview of the successes in development and translation of new algorithms into the clinical workflow by the many research teams of the Quantitative Imaging Network.