Apparent Diffusion Coefficient Quantification Research Articles

Abstract PS05-04: [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity

Abstract Introduction: Molecular imaging of human epidermal receptor 2 (HER2) aims to overcome limitations of traditional HER2 assessment through biopsy, including invasiveness and inability to detect intra and inter-tumoral spatial heterogeneity. Prior human studies suggest that [89Zr]Trastuzumab-positron emission tomography (PET) imaging can effectively differentiate HER2 lesions (Dehdashti et al, Breast Cancer Res. Treat. 2018). Commonly, CT complements PET for anatomical reference, however, integrating MRI enables the sensitivity of soft-tissue contrast required for anatomic and morphological breast imaging and can provide for quantitative multiparametric characterization. Diffusion weighted-MRI (DW-MRI) contributes to tumor characterization by assessing intratumoral cellularity via the apparent diffusion coefficient (ADC), and can be combined with molecular expression from HER2-PET. We present preliminary results in 13 patients with HER2 PET/MRI to define tumor and normal tissue imaging metrics. Methods: A phase II clinical trial assessing the feasibility of [89Zr]trastuzumab-PET with simultaneous quantitative DW-MRI to enhance understanding of tumor heterogeneity in patients with HER2-positive metastatic breast cancer. 13 patients (ages 40-70; mean 60) with HER2-positive breast cancer based on prior biopsy underwent whole-body [89Zr]trastuzumab-PET/MR imaging (5 ± 1 days post-injection of radiopharmaceutical) during the course of HER2-directed therapy. Normal organ and tumor regions of interest (ROI) were identified on concurrently acquired whole-body T1-weighted MRI for ADC (cellularity) and standardized uptake value (SUV, PET uptake) mean quantification. Tumor presence was confirmed via bone scintigraphy, FDG-PET/CT, or contrast-enhanced MRI. Non-parametric T-tests compared lesions to normal organs. Lesions greater than 30 mm in diameter underwent multiparametric intratumoral habitat analysis. Using the median HER2 values, tumors were evaluated for heterogeneity of high and low HER2 expression in conjunction with ADC. Long-term treatment response evaluation is ongoing. Results: Mean [89Zr]trastuzumab uptake, SUV, and ADC values for normal tissue were summarized in Table 1. All tumors demonstrated higher overall uptake of [89Zr]trastuzumab (bone: p=0.019, brain: p=0.014, breast: p=0.069, juxtapulmonary: p=0.026) and increased ADCmean values (bone: p=0.002, brain: p=0.5, breast: p=0.03, juxtapulmonary: p=0.037), in comparison to matched normal organs. Notably, one of five patients with a breast lesion, who completely responded to HER2 targeted therapy, exhibited the highest breast lesion SUVmean. Brain and lymph node lesions demonstrated intratumoral heterogeneity of HER2 expression. Conclusion: Our study demonstrates the potential value of quantitative MRI along with molecular imaging to characterize metastatic HER2+ breast cancer and evaluate intratumoral heterogeneity. We underscore the importance of standardizing processing techniques and contribute to this effort by summarizing [89Zr]trastuzumab uptake and cellularity values of normal physiological uptake. Higher SUVmean and ADC mean values observed in lesions, compared to normal tissue, highlight their potential roles in intratumoral classification. While studies have shown the utility of [89 Zr]trastuzumab-PET/CT, our findings demonstrate that integrated DW-MRI can aid in tumor classification. Table 1: Physiological 89Zr-Trastuzumab Uptake (SUVmean) and Apparent Diffusion Coefficient (ADCmean) in Healthy Tissues Citation Format: Ameer Mansur, Moozhan Nikpanah, Johnathan McConathy, Erica Stringer-Reasor, Gabrielle Rocque, Ahmed Elkhanany, Katia Khoury, Nusrat Jahan, Suzanne Lapi, Anna Sorace. [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-04.

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

Background and purposeDiffusion 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 methodsAccuracy 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. ResultsPhantom 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. ConclusionsThe acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.

Diffusion-weighted Imaging of the Abdomen during a Single Breath-hold Using Simultaneous-multislice Echo-planar Imaging.

This multi-scanner study aimed to investigate the validity of single breath-hold (BH) diffusion-weighted imaging (DWI) using simultaneous-multislice (SMS) echo-planar imaging in multiple abdominal organs to enable faster acquisition and reliable quantification of apparent diffusion coefficient (ADC). SNR, geometric distortion (GD), and ADC in a phantom; the ADC in the liver, renal cortex, paraspinal muscle, spleen, and pancreas; and the signal intensity ratio of the portal vein-to-muscle (SIRPV-M) in healthy volunteers were compared between BH- and respiratory-triggered (RT) DWI with b-values of 0 and 800 s/mm2 in two different MRI scanners. The phantom study showed that the SNR of BH-DWI was significantly lower than that of the RT-DWI (P < 0.05 for both scanners), whereas the GD and ADC of BH-DWI did not differ significantly from those of the RT-DWI (P = 0.09-0.60). In the volunteer study, the scan times were 23 seconds for BH-DWI and 184±33 seconds for RT-DWI, respectively. The ADC of the liver in BH-DWI was significantly lower than that in RT-DWI (P < 0.05 for both scanners), whereas there were no significant differences in the ADCs of the renal cortex, paraspinal muscle, spleen, or pancreas between BH-DWI and RT-DWI (P = 0.07-0.86). The SIRPV-M in BH-DWI was significantly smaller than in RT-DWI (P < 0.05 for both scanners). The proposed method enables the acquisition of abdominal diffusion-weighted images in a single BH.

High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques.

To compare objective and subjective image quality, lesion conspicuity, and apparent diffusion coefficient (ADC) of high-resolution multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) with conventional DWI (c-DWI) and reduced FOV DWI (rFOV-DWI) in prostate MRI. Forty-seven patients who underwent prostate MRI, including c-DWI, rFOV-DWI, and MUSE-DWI, were retrospectively evaluated. SNR and ADC of normal prostate tissue and contrast-to-noise ratio (CNR) and ADC of prostate cancer (PCa) were measured and compared between the three sequences. Image quality and lesion conspicuity were independently graded by two radiologists using a 5-point scale and compared between the three sequences. The SNR of normal prostate tissue was significantly higher with rFOV-DWI than with the other two DWI techniques (P ≤ 0.01). The CNR of the PCa was significantly higher with rFOV-DWI than with MUSE-DWI (P < 0.05). The ADC of normal prostate tissue measured by rFOV-DWI was lower than that measured by MUSE-DWI and c-DWI (P < 0.01), while there was no difference in the ADC of cancers. In the qualitative analysis, MUSE-DWI showed significantly higher scores than rFOV-DWI and c-DWI for visibility of anatomy and overall image quality in both readers, and significantly higher scores for distortion in one of the two readers (P < 0.001). There was no difference in lesion conspicuity between the three sequences. High-resolution MUSE-DWI showed higher image quality and reduced distortion compared to c-DWI, while maintaining a wide FOV and similar ADC quantification, although no difference in lesion conspicuity was observed.

Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging

ObjectivesTo prospectively compare image quality and apparent diffusion coefficient (ADC) quantification for reduced field-of-view (rFOV)- and multi-shot echo-planar imaging (msEPI)-based diffusion weighted imaging (DWI), using single-shot echo-planar-imaging (ssEPI) DWI as the reference. MethodsUnder IRB approval and after informed consent, msEPI, rFOV, and ssEPI DWI acquisitions were prospectively added to clinical prostate MRI exams at 3.0 T. Image distortion was quantitatively evaluated by root-mean-squared displacement (dr.m.s.). Histogram-based quantitative ADC parameters were compared in a sub-set of patients for proven sites of prostate cancer and matched non-cancerous prostate. Three radiologists also independently evaluated the DWI sequences for subjective image quality and distortion/artifact on a 5-point Likert scale. ResultsTwenty-five patients were included (15 with proven sites of cancer). Average dr.m.s. demonstrated a small but statistically significant reduction in distortion for both rFOV and msEPI relative to ssEPI. Quantitative ADC parameters for prostate tumors demonstrated no significant difference across the 3 DWI acquisitions and each acquisition demonstrated a statistically significant decrease in mean ADC for tumor compared to normal prostate. Qualitative reader assessment demonstrated favorable image quality for rFOV and msEPI, more notable for msEPI. ConclusionsrFOV and msEPI DWI techniques achieved reduction in image distortion, improvement in image quality, and maintained reproducible ADC quantification compared to the standard ssEPI.

The Diagnostic Role of Normalized and Mean Apparent Diffusion Coefficient in Differentiation between Pancreatic Lesions

Background: Diffusion-weighted magnetic resonance imaging (DWI) with quantification ofapparent diffusion coefficient (ADC) values is well established in the diagnosis of a variety of abdominal abnormalities. Regarding pancreatic disease, several investigators have shown that DWI with ADC measurement helps detect and characterize focal pancreatic lesions, as well as assess the severity of other pancreatic conditions. Objective: The study aimed to evaluate the diagnostic role of both normalized and mean apparent diffusion coefficient in discrimination between pancreatic lesions. Patients and Methods: Thirty-one participants presented with pancreatic lesions using clinical examination and ultrasound. Dynamic contrast MRI abdomen with diffusion-weighted MR imaging (DWI) on a 1.5-Tesla MRI machine was done. Mean ADC and normalized ADC (as the ratio of ADC of the lesion to the adjacent normal pancreas) were measured and compared. Results: Our study reported a mean ADC cut value of ≤1.47 while the cut-off value for normalized ADC was ≤ 0.96. Normalized ADC revealed a higher sensitivity 92.31%, specificity 88.89%, PPV 85.71, NPV 94.12%, accuracy 90.32%, positive likelihood ratio 8.31 and negative likelihood ratio 0.09 as compared to mean ADC, which revealed sensitivity 84.62%, specificity 77.78%, PPV 73.33%, NPV 87.5%, accuracy 80.65%, positive likelihood ratio 3.81 and negative likelihood ratio 0.2 respectively. Conclusion: Measuring the mean and normalized ADC value in pancreatic focal lesions can significantly differentiate between benign and malignant pancreatic lesions. However, normalized ADC has a higher sensitivity, specificity, PPV, and NPV than mean ADC value and could be used to differentiate between pancreatic lesions with higher accuracy than mean ADC.

Cytotoxic Edema Associated with Hemorrhage Predicts Poor Outcome after Traumatic Brain Injury.

Magnetic resonance imaging (MRI) is used rarely in the acute evaluation of traumatic brain injury (TBI) but may identify findings of clinical importance not detected by computed tomography (CT). We aimed to characterize the association of cytotoxic edema and hemorrhage, including traumatic microbleeds, on MRI obtained within hours of acute head trauma and investigated the relationship to clinical outcomes. Patients prospectively enrolled in the Traumatic Head Injury Neuroimaging Classification study (NCT01132937) with evidence of diffusion-related findings or hemorrhage on neuroimaging were included. Blinded interpretation of MRI for diffusion-weighted lesions and hemorrhage was conducted, with subsequent quantification of apparent diffusion coefficient (ADC) values. Of 161 who met criteria, 82 patients had conspicuous hyperintense lesions on diffusion-weighted imaging (DWI) with corresponding regions of hypointense ADC in proximity to hemorrhage. Median time from injury to MRI was 21 (10-30) h. Median ADC values per patient grouped by time from injury to MRI were lowest within 24 h after injury. The ADC values associated with hemorrhagic lesions are lowest early after injury, with an increase in diffusion during the subacute period, suggesting transformation from cytotoxic to vasogenic edema during the subacute post-injury period. Of 118 patients with outcome data, 60 had Glasgow Outcome Scale Extended scores ≤6 at 30/90 days post-injury. Cytotoxic edema on MRI (odds ratio [OR] 2.91 [1.32-6.37], p = 0.008) and TBI severity (OR 2.51 [1.32-4.74], p = 0.005) were independent predictors of outcome. These findings suggest that in patients with TBI who had findings of hemorrhage on CT, patients with DWI/ADC lesions on MRI are more likely to do worse.

Diffusion and quantification of diffusion of prostate cancer.

For assessing a cancer treatment, and for detecting and characterizing cancer, Diffusion-weighted imaging (DWI) is commonly used. The key in DWI's use extracranially has been due to the emergence of of high-gradient amplitude and multichannel coils, parallelimaging, and echo-planar imaging. The benefit has been fewer motion artefacts and high-quality prostate images.Recently, new techniques have been developed to improve the signal-to-noise ratio of DWI with fewer artefacts, allowing an increase in spatial resolution. For apparent diffusion coefficient quantification, non-Gaussian diffusion models have been proposed as additional tools for prostate cancer detection and evaluation of its aggressiveness. More recently, radiomics and machine learning for prostate magnetic resonance imaging have emerged as novel techniques for the non-invasive characterisation of prostate cancer. This review presents recent developments in prostate DWI and discusses its potential use in clinical practice.

Study of Diffusion Weighted Imaging in Magnetic Resonance Imaging: Quantification of Apparent Diffusion Coefficient (ADC) from b-value in Agarose

Diffusion Magnetic Resonance Imaging (MRI) is one of the promising methods to observe molecular structure and diffusion properties of materials and tissues inside human body. The experiments with diffusion MRI had been conducted on 11 agarose gel inside tubes with the solution percentages of 0% - 5% with an increment of 0.5% to obtain apparent diffusion coefficient (ADC) of agarose gel. Images were acquired using 1.5 Tesla MRI machine with a spin-echo sequence. The parameters used are TR 5000 ms, TE 50 ms, b-value with variations of (10, 50, 75, 125, 250, 500, 750, and 1000) s/mm2, slice thickness 5 mm and field of view 36 mm × 36 mm. Image processing was carried out using ImageJ software to determine the average signal intensity for each sample. After signal intensities from all variations of b-value were obtained, the linear curve fitting with b-value was performed using Matlab to obtain ADC. From the experimental results, it is found that the signal intensity decreases with increasing b-value and ADC of agarose gel is not linearly proportional to agarose concentration.

Comparison and evaluation of distortion correction techniques on an MR-guided radiotherapy system.

To evaluate two distortion correction techniques for diffusion-weighted single-shot echo-planar imaging (DW-ssEPI) on a 0.35T magnetic resonance-guided radiotherapy (MRgRT) system. The effects of sequence optimization through enabling parallel imaging (PI) and selecting appropriate bandwidth on spatial distortion were first evaluated on the 0.35T MRgRT system using a spatial integrity phantom. Field map (FM) and reversed gradient (RG) corrections were then performed on the optimized protocol to further reduce distortion. An open-source toolbox was used to quantify the spatial displacement before and after distortion correction. To evaluate ADC accuracy and repeatability of the optimized protocol, as well as impacts of distortion correction on ADC values, the optimized protocol was scanned twice on a diffusion phantom. The calculated ADC values were compared with reference ADCs using paired t-test. Intraclass correlation coefficient (ICC) between the two repetitions, as well as between before and after FM/RG correction was calculated to evaluate ADC repeatability and effects of distortion correction. Six patients were recruited to assess the in-vivo performance. The optimal distortion correction technique was identified by visual assessment. To quantify distortion reduction, tumor and critical structures were contoured on the turbo spin echo (TSE) image (reference image), the DW-ssEPI image, and the distortion corrected images independently by two radiation oncologists. Mean distance to agreement (MDA) and DICE coefficient between contours on the reference images and the diffusion images were calculated. Tumor apparent diffusion coefficient (ADC) values from the original DW-ssEPI images and the distortion corrected images were compared using Bland-Altman analysis. Sequence optimization played a vital role in improving the spatial integrity, and spatial distortion was proportional to the total readout time. Before the correction, distortion of the optimized protocol (PI and high bandwidth) was 1.50±0.89mm in a 100mm radius and 2.21±1.39mm in a 175mm radius for the central plane. FM corrections reduced the distortions to 0.42±0.27mm and 0.67±0.49mm respectively, and RG reduced distortion to 0.40±0.22mm and 0.64±0.47mm, respectively. The optimized protocol provided accurate and repeatable ADC quantification on the diffusion phantom. The calculated ADC values were consistent before and after FM/RG correction. For the patient study, the FM correction was unable to reduce chemical shift artifacts whereas the RG method successfully mitigated the chemical shift. MDA reduced from 2.52±1.29mm to 1.11±0.72mm after the RG correction. The DICE coefficient increased from 0.80±0.13 to 0.91±0.06. A Bland-Altman plot showed that there was a good agreement between ADC measurements before and after application of the RG correction. Two distortion correction techniques were evaluated on a commercial low-field MRgRT system. Overall, the RG correction was able to drastically improve spatial distortion and preserve ADC accuracy.

ADC measurements on the Unity MR-linac – A recommendation on behalf of the Elekta Unity MR-linac consortium

Background and purposeDiffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. Materials and methodsSignal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. ResultsOn the Unity system, a maximum b-value of 500 s/mm2 should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. ConclusionWe provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.

Diffusion MRI with quantification of ADC value in characterization of benign and malignant hepatic lesions and their correlation with cyto-histopathology

Diffusion weighted Imaging (DWI) is a useful noninvasive tool in MRI as it can be performed quickly and does not require contrast injection. In addition to it, DWI imaging and apparent diffusion coefficient (ADC) quantification not only can add additional anatomical data about the lesion but can also help in characterization of focal liver lesions into malignant or benign. The study attempts to establish a cut off value of ADC differentiating a benign from malignant lesion.32 patients with age group of 40-85 years with 46 diagnosed focal liver lesions on CT and MRI were included in the study. MRI was performed using 1.5 Tesla GE Healthcare HDxT machine. Conventional sequences followed by diffusion weighted sequences were acquired. Quantitative analysis was derived from ADC maps with calculation of ADC values. ADC values of the hepatic lesions were compared with histopathology as reference standard and analyzed statistically. In this study, 25 focal lesions in 18 patients had histopathological diagnosis of malignant pathology and had mean ADC value 1.13(x10mm/s) and 21 lesions in 14 patients with histopathological diagnosis of benign pathology had ADC value of 1.63(x10mm/s). Statistically significant difference between ADC value of benign and malignant lesions was found.: The study proclaimed that DWI with ADC quantification be used as an additional non invasive MRI tool to differentiate benign and malignant hepatic lesions with a sensitivity of 85.7%, specificity of 88%, PPV of 88% and NPV of 85.7%

Diffusion-Weighted MR Imaging of Primary and Secondary Lung Cancer: Predictive Value for Response to Transpulmonary Chemoembolization and Transarterial Chemoperfusion.

To examine predictive value of apparent diffusion coefficient (ADC) in diffusion-weighted imaging (DWI) for response of patients with primary and secondary lung neoplasms undergoing transpulmonary chemoembolization (TPCE) and transarterial chemoperfusion (TACP) treatment. Thirty-one patients (mean age ± SD 64 ± 12.4 y) with 42 lung target lesions (13 primary and 29 secondary) underwent DWI and subsequent ADC analysis on a 1.5T MR imaging scanner before and 30.3 days ± 6.4 after first session of TPCE or TACP. After 3.1 treatment sessions ± 1.4 performed in 2- to 4-week intervals, morphologic response was analyzed by comparing tumor diameter and volume before and after treatment on unenhanced T1-weighted MR images. On a per-lesion basis, response was classified according to Response Evaluation Criteria In Solid Tumors. Threshold ADC increase of 20.7% indicated volume response with 88% sensitivity and 78% specificity (area under the curve [AUC]= 0.84). Differences between ADC changes in volume response groups were significant (P= .002). AUC for volume response predicted by ADC before treatment was 0.77. Median ADC before treatment and mean ADC change were 1.09× 10-3 mm2/second and 0.36× 10-3 mm2/second ± 0.23, 1.45× 10-3 mm2/second and 0.14× 10-3 mm2/second ± 0.16, and 1.30× 10-3 mm2/second and 0.06× 10-3 mm2/second ± 0.19 in partial response, stable disease, and progressive disease groups. In primary lung cancer lesions, strong negative correlation of ADC change with change in diameter (ρ=-.87, P < .001) and volume (ρ=-.66, P= .016) was found. In metastases, respective correlation coefficients were ρ=-.18 (P= .356) and ρ=-.35 (P= .061). ADC quantification shows considerable diagnostic value for predicting response and monitoring TPCE and TACP treatment of patients with primary and secondary lung neoplasms.

Qualitative and quantitative comparison of image quality between single-shot echo-planar and interleaved multi-shot echo-planar diffusion-weighted imaging in female pelvis

ObjectivesTo qualitatively and quantitatively compare the image quality between single-shot echo-planar (SS-EPI) and multi-shot echo-planar (IMS-EPI) diffusion-weighted imaging (DWI) in female pelvisMethodsThis was a prospective study involving 80 females who underwent 3.0T pelvic magnetic resonance imaging (MRI). SS-EPI and IMS-EPI DWI were acquired with 3 b values (0, 400, 800 s/mm2). Two independent reviewers assessed the overall image quality, artifacts, sharpness, and lesion conspicuity based on a 5-point Likert scale. Regions of interest (ROI) were placed on the endometrium and the gluteus muscles to quantify the signal intensities and apparent diffusion coefficient (ADC). Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and geometric distortion were quantified on both sequences. Inter-rater agreement was assessed using κ statistics and Kendall test. Qualitative scores were compared using Wilcoxon signed-rank test and quantitative parameters were compared with paired t test and Bland-Altman analysis.ResultsIMS-EPI demonstrated better image quality than SS-EPI for all aspects evaluated (SS-EPI vs. IMS-EPI: overall quality 3.04 vs. 4.17, artifacts 3.09 vs. 3.99, sharpness 2.40 vs. 4.32, lesion conspicuity 3.20 vs. 4.25; p < 0.001). Good agreement and correlation were observed between two reviewers (SS-EPI κ 0.699, r 0.742; IMS-EPI κ 0.702, r 0.789). IMS-EPI showed lower geometric distortion, SNR, and CNR than SS-EPI (p < 0.050). There was no significant difference in the mean ADC between the two sequences.ConclusionIMS-EPI showed better image quality with lower geometric distortion without affecting the quantification of ADC, though the SNR and CNR decreased due to post-processing limitations.Key Points• IMS-EPI showed better image quality than SS-EPI.• IMS-EPI showed lower geometric distortion without affecting ADC compared with SS-EPI.• The SNR and CNR of IMS-EPI decreased due to post-processing limitations.

Pathologic Correlation of Cellular Imaging Using Apparent Diffusion Coefficient Quantification in Patients with Brain Metastases After Gamma Knife Radiosurgery

To evaluate the role of apparent diffusion coefficient (ADC) in differentiating radiation necrosis (RN) from recurrent tumor after Gamma Knife radiosurgery (GKRS) for brain metastases (BMs). Forty-one patients with BM who underwent surgical intervention after GKRS at Cleveland Clinic (2006-2017) were included in this retrospective study. The ADC values of the growing lesions and the contralateral hemisphere were calculated using picture archiving and communication system. These values were correlated to the percentage of RN identified on pathologic evaluation of the surgical specimen. The median age of the patients was 59 years (range, 25-86 years), and lung cancer (63.4%) was the most common malignancy. Median initial (pre-GKRS) target volume of the lesions was 5.4 cc (range, 0.135-45.6 cc), and median GKRS dose was 18.0 Gy. Surgical resection or biopsy was performed at a median of 176 days after GKRS. Two variables were statistically significant predictors of predominate RN (75%-100%) in the surgical specimen: 1) ADC of the lesion on the preresection magnetic resonance imaging (MRI) and 2) initial pre-GKRS target volume. ADC >1.5× 10-3 mm2/s within the lesion on MRI predicted significant RN on pathologic evaluation of the lesion (P < 0.05). Similarly, when the target volume before GKRS was large (>10 cc), the risk of identifying significant necrosis in the pathologic specimen was elevated (P < 0.05). Our data suggest that the combination of lesion ADC on MRI prior to surgical intervention and the initial target volume can predict RN with reasonable accuracy.

Apparent Diffusion Coefficient Assessment of Brain Development in Normal Fetuses and Ventriculomegaly

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19-38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values=50,200,700s/mm^2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC between normal and VM cases and between second and third trimester in different brain regions. Correlation between ADC and GA was assessed with linear and quadratic regression analysis. Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains (p<0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p<0.02). ADC values in centrum semiovale, thalamus, cerebellum and pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA was found in basal ganglia and occipital white matter of normal brains and in frontal white matter of VM (p<0.02). ADC values in all fetal brain regions were lower than those reported in literature where DWI with b=0 was performed. Conversely, they were in agreement with the results of other authors who measured perfusion and diffusion contributions separately. By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities associated with VM.

Accuracy, criteria, and clinical significance of visual assessment on diffusion-weighted imaging and apparent diffusion coefficient quantification for diagnosing acute appendicitis.

To assess the accuracy, criteria, and clinical significance of diffusion-weighted imaging (DWI) signal intensity and apparent diffusion coefficient (ADC) quantification for diagnosing acute appendicitis. Fifty-one patients with right lower abdominal pain [uncomplicated appendicitis (n = 25), complicated appendicitis (n = 10), and non-appendicitis (n = 16)] who underwent MR examination were enrolled in this retrospective study. Two radiologists independently measured appendiceal diameter and wall thickness. They assessed whether a wall defect, an abscess, extraluminal air, or an appendicolith was present on axial T2WI; evaluated intensity on DWI using a 5-point scale; and determined the ADC values of the appendix and peri-appendiceal tissue. Statistical analysis was performed to assess imaging findings for the diagnosis of appendicitis and complicated appendicitis. Cut-off values were determined using receiver operating characteristic analysis. For diagnosing acute appendicitis, the accuracy improved from 78.4% using only T2WI to 86.3% using combined T2WI and DWI for reader 1 and from 82.4 to 86.3% for reader 2. For the appendix, the cut-off ADC values that diagnosed appendicitis were 1.41 × 10-3 and 1.26 × 10-3 mm2/s with accuracies of 78.4% and 76.5%, respectively. For the peri-appendiceal tissue, these values of 1.03 × 10-3 and 0.91 × 10-3 mm2/s differentiated between uncomplicated and complicated appendicitis with an accuracy of 97.1%. Combined DWI and T2WI provided high accuracy for diagnosing appendicitis. The inflamed appendix had lower ADC value than the normal appendix. The peri-appendiceal tissue presenting low ADC value was a notable finding of complicated appendicitis.

Improved accuracy of apparent diffusion coefficient quantification using a fully automatic noise bias compensation method: Preliminary evaluation in prostate diffusion weighted imaging.

Noise in diffusion magnetic resonance imaging can introduce bias in apparent diffusion coefficient (ADC) quantification. Previous studies proposed methods that are site-specific techniques as research tools with limited availability and typically require manual intervention, not completely ready to use in the clinical environment. The purpose of this study was to develop a fully automatic computational method to correct noise bias in ADC quantification and perform a preliminary evaluation in the clinical prostate diffusion weighted imaging (DWI). Using a pseudo replica approach for the noise map calculation as well as a direct mapping and a stepwise Chebychev polynomial modelling approach for the ADC fitting, a fully automatic noise-bias-compensated ADC calculation method was proposed and implemented both on the scanner and offline. The proposed method was validated in a computer simulation and a standardized diffusion phantom with ground-truth values. Two in vivo studies were performed to evaluate the proposed method in the clinical environment. The first in vivo study performed acquisitions using a clinically routine prostate DWI protocol on 29 subjects to evaluate the consistency between simulated and empirical results. In the second in vivo study, prostate ADC values of 14 subjects were compared between data acquired with external coils only and reconstructed with the proposed method vs. acquired with external combined with endorectal coils and reconstructed with the conventional method. In statistical analyses, p < 0.05 was regarded as significantly different. In the computer simulation, the proposed method showed smaller error percentage than the other methods and was significantly different (p < 2.2 × 10-16). With low signal-to-noise ratio (SNR), the conventional method underestimated ADC values compared to the ground truth values of the diffusion phantom, while the results of the proposed method were more consistent with the ground truth values. Statistical analyses showed no significant differences between measured and simulated results in the first in vivo study (p = 0.5618). Data from the second in vivo study showed that agreement between ADC measured with external coils only and combined coils was improved for the proposed method (mean bias: 0.04 × 10-3 mm2/s, 95% confidence interval (CI) = [-0.01, 0.09] × 10-3 mm2/s, p = 0.187), compared to the conventional method (mean bias: -0.12 × 10-3 mm2/s, 95% CI = [-0.17, -0.06] × 10-3 mm2/s, p < 0.0001). The proposed method compensates noise bias in low-SNR diffusion-weighted acquisitions and results show improved ADC quantification accuracy in the prostate. This method may be suitable for both clinical imaging and research utilizing ADC quantification.

Prognostic value of ADC quantification for clinical outcome in uterine cervical cancer treated with concurrent chemoradiotherapy.

To investigate the prognostic value of diffusion-weighted imaging (DWI) in predicting clinical outcome in patients with cervical cancer after concurrent chemoradiotherapy (CCRT). We enrolled 124 cervical cancer patients who received definitive CCRT and underwent 3T-MRI before and 1month after initiating treatment. The mean apparent diffusion coefficient (ADC) value was measured on the tumor and the changes in ADC percentage (ΔADCmean) between the two time points were calculated. The Cox proportion hazard model was used to evaluate the associations between imaging or clinical variables and progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS). In multivariate analysis, ΔADCmean was the only independent predictor of PFS (hazard ratio [HR] = 0.2379, p = 0.005), CSS (HR = 0.310, p = 0.024), and OS (HR = 0.217, p = 0.002). Squamous cell carcinoma antigen, histology, and pretreatment tumor size were significantly independent predictors of PFS. Tumor size response was significantly independent predictor of CSS and OS. Using the cutoff values of ΔADCmean, the PFS was significantly lower for ΔADCmean < 27.8% (p = 0.001). The CSS and OS were significantly lower for ΔADCmean < 16.1% (p = 0.002 and p < 0.001, respectively). The percentage change in tumor ADC may be a useful predictor of disease progression and survival in patients with cervical cancer treated with CCRT. • DWI is widely used as a potential marker of tumor viability. • Percentage change in tumor ADC (ΔADC mean ) was an independent marker of PFS, CSS, and OS. • Survival was better in patients with ≥ ΔADC mean cutoff value than with < the cutoff value.

Arterial spin labelling and diffusion-weighted imaging in paediatric brain tumours.

BackgroundDiffusion- and perfusion-weighted MRI are valuable tools for measuring the cellular and vascular properties of brain tumours. This has been well studied in adult patients, however, the biological features of childhood brain tumours are unique, and paediatric-focused studies are less common. We aimed to assess the diagnostic utility of apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) and cerebral blood flow (CBF) values derived from arterial spin labelling (ASL) in paediatric brain tumours.MethodsWe performed a meta-analysis of published studies reporting ADC and ASL-derived CBF values in paediatric brain tumours. Data were combined using a random effects model in order to define typical parameter ranges for different histological tumour subtypes and WHO grades. New data were also acquired in a ‘validation cohort’ at our institution, in which ADC and CBF values in treatment naïve paediatric brain tumour patients were measured, in order to test the validity of the findings from the literature in an un-seen cohort. ADC and CBF quantification was performed by two radiologists via manual placement of tumour regions of interest (ROIs), in addition to an automated approach to tumour ROI placement.ResultsA total of 14 studies met the inclusion criteria for the meta-analysis, constituting data acquired in 542 paediatric patients. Parameters of interest were based on measurements from ROIs placed within the tumour, including mean and minimum ADC values (ADCROI-mean, ADCROI-min) and the maximum CBF value normalised to grey matter (nCBFROI-max). After combination of the literature data, a number of histological tumour subtype groups showed significant differences in ADC values, which were confirmed, where possible, in our validation cohort of 32 patients. In both the meta-analysis and our cohort, diffuse midline glioma was found to be an outlier among high-grade tumour subtypes, with ADC and CBF values more similar to the low-grade tumours. After grouping patients by WHO grade, significant differences in grade groups were found in ADCROI-mean, ADCROI-min, and nCBFROI-max, in both the meta-analysis and our validation cohort. After excluding diffuse midline glioma, optimum thresholds (derived from ROC analysis) for separating low/high-grade tumours were 0.95 × 10−3 mm2/s (ADCROI-mean), 0.82 × 10−3 mm2/s (ADCROI-min) and 1.45 (nCBFROI-max). These thresholds were able to identify low/high-grade tumours with 96%, 83%, and 83% accuracy respectively in our validation cohort, and agreed well with the results from the meta-analysis. Diagnostic power was improved by combining ADC and CBF measurements from the same tumour, after which 100% of tumours in our cohort were correctly classified as either low- or high-grade (excluding diffuse midline glioma).ConclusionADC and CBF values are useful for differentiating certain histological subtypes, and separating low- and high-grade paediatric brain tumours. The threshold values presented here are in agreement with previously published studies, as well as a new patient cohort. If ADC and CBF values acquired in the same tumour are combined, the diagnostic accuracy is optimised.