Diffusion-weighted magnetic resonance imaging for assessment of lung lesions: repeatability of the apparent diffusion coefficient measurement

A multicenter study of cervical cancer using quantitative diffusion-weighted imaging

BACKGROUND

Parameters from diffusion-weighted imaging (DWI) have been increasingly used as imaging biomarkers for the diagnosis and monitoring of treatment responses in cancer. The consistency of DWI measurements across different centers remains uncertain, which limits the widespread use of quantitative DWI in clinical settings.

PURPOSE

To investigate the consistency of quantitative metrics derived from DWI between different scanners in a multicenter clinical setting.

MATERIAL AND METHODS

A total of 193 patients with cervical cancer from four scanners (MRI1, MRI2, MRI3, and MRI4) at three centers were included in this retrospective study. DWI data were processed using the mono-exponential and intravoxel incoherent motion (IVIM) model, yielding the following parameters: apparent diffusion coefficient (ADC); true diffusion coefficient (D); pseudo-diffusion coefficient (D*); perfusion fraction (f); and the product of f and D* (fD*). Various parameters of cervical cancer obtained from different scanners were compared.

RESULTS

The parameters D and ADC derived from MRI1 and MRI2 were significantly different from those derived from MRI3 or MRI4 (P <0.01 for all comparisons). However, there was no significant difference in cervical cancer perfusion parameters (D* and fD*) between the different scanners (P >0.05). The P values of comparisons of all DWI parameters (D, D*, fD*, and ADC) between MRI3 and MRI4 (same vendor in different centers) for cervical cancer were all >0.05, except for f (P = 0.05).

CONCLUSION

Scanners of the same model by the same vendor can yield close measurements of the ADC and IVIM parameters. The perfusion parameters showed higher consistency among the different scanners.

Preoperative prediction of VETC in hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging at high b values: a pilot study

Background

Vessels encapsulating tumor clusters (VETC) have been considered an important cause of hepatocellular carcinoma (HCC) metastasis.

Purpose

To compare the potential of various diffusion parameters derived from the monoexponential model and four non-Gaussian models (DKI, SEM, FROC, and CTRW) in preoperatively predicting the VETC of HCC.

Methods

86 HCC patients (40 VETC-positive and 46 VETC-negative) were prospectively enrolled. Diffusion-weighted images were acquired using six b-values (range from 0 to 3000 s/mm2). Various diffusion parameters derived from diffusion kurtosis (DK), stretched-exponential (SE), fractional-order calculus (FROC), and continuous-time random walk (CTRW) models, together with the conventional apparent diffusion coefficient (ADC) derived from the monoexponential model were calculated. All parameters were compared between VETC-positive and VETC-negative groups using an independent sample t-test or Mann-Whitney U test, and then the parameters with significant differences between the two groups were combined to establish a predictive model by binary logistic regression. Receiver operating characteristic (ROC) analyses were used to assess diagnostic performance.

Results

Among all studied diffusion parameters, only DKI_K and CTRW_α significantly differed between groups (P=0.002 and 0.004, respectively). For predicting the presence of VETC in HCC patients, the combination of DKI_K and CTRW_α had the larger area under the ROC curve (AUC) than the two parameters individually (AUC=0.747 vs. 0.678 and 0.672, respectively).

Conclusion

DKI_K and CTRW_α outperformed traditional ADC for predicting the VETC of HCC.

Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses

Background

Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions.

Methods

73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer’s agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs.

Results

107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49–0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%.

Conclusions

The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.

Correlation of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) with overall survival in patients with primary non-small cell lung cancer (NSCLC) using 18F-FDG PET/MRI

OBJECTIVES

To investigate if the combined analysis of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) measured in ¹⁸F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) examinations correlates with overall survival in non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

A total of 92 patients with newly diagnosed, histopathologically proven NSCLC (44 women and 48 men, mean age 63.1 ± 9.9y) underwent a dedicated thoracic ¹⁸F-FDG PET/MRI examination. A manually drawn polygonal region of interest (ROI), encompassing the entire primary tumor mass, was placed over the primary tumor on fused PET/MR images to determine the maximum and mean standardized uptake values (SUV_max; SUV_mean) as well as on the ADC maps to quantify the mean and minimum ADC values (ADC_mean, ADC_min). The impact of these parameters to predict patient's overall survival was tested using hazard ratios (HR). Pearson's correlation coefficients were calculated to assess dependencies between the different values. A p-value < 0.05 indicated statistical significance.

RESULTS

In all 92 patients (n = 59 dead at time of retrospective data collection, mean time till death: 19 ± 16 month, n = 33 alive, mean time to last follow-up: 56 ± 22 month) the Hazard ratios (HR) as independent predictors for overall survival (OS) of SUV_max were 2.37 (95 % CI: 1.23-4.59, p = 0.008) and for SUV_mean 1.85 (95 % CI: 1.05-3.26, p = 0.03) while ADC_min showed a HR of 0.95 (95 % CI: 0.57-1.59, p = 0.842) and ADC_mean a HR of 2.01 (95 % CI: 1.2-3.38, p = 0.007). Furthermore, a combined analysis for SUV_max/ADC_mean, SUV_max / ADC_min and SUV_mean/ADC_mean revealed a HR of 2.01 (95 % CI: 1.10-3.67, p = 0.02), 1.75 (95 % CI: 0.97-3.15, p = 0.058) and 1.78 (95 % CI: 1.02-3.10, p = 0.04).

CONCLUSION

SUV_max and SUV_mean of the primary tumor are predictors for OS in therapy-naive NSCLC patients, whereas the combined analysis of SUV and ADC values does not improve these results. Therefore, ADC values do not further enhance the diagnostic value of SUV as a prognostic biomarker in NSCLC.

Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer: Improvements Using Radiomics

Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics.

MRI in Evaluation of Solitary Pulmonary Nodules

OBJECTIVES

The aim of this study is to assess magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), T2-weighted image (T2WI), and apparent diffusion coefficient (ADC) maps' threshold values before computed tomography (CT)-guided transthorasic biopsy in solitary pulmonary nodules (SPN) by describing tumoral cell density.

MATERIALS AND METHODS

Patients who had SPN were prospectively evaluated with MRI (T1WI, T2WI) and DWI (b=0, b=500, b=1000).The ADC maps were created for each patient. Before the biopsy, lesion muscle ratios (LMR) at T2WI, ADC value, and lesion spinal cord ratio at each b values were noted. The measurements were correlated with the histopathological results.

RESULTS

A total of 53 patients were included in the study: 30.2% (n=16) were female, and 69.8% (n=37) were male. Among them, 17 lesions (32.1%) were benign, and 36 lesions (67.9%) were malignant. The age varied between 40 and 82 years, with a mean of 61.7±9.1 years. The SPN diameters were between 10 and 30 mm, and the median was 24 mm. The LSR0 and LMR values were not statistically significant in detecting malignancy. LSR500 >0.53 value can predict malignancy with 100% sensitivity and 70.6% specificity. LSR1000 >0.53 can predict malignancy with 88.9% sensitivity and 88.2% specificity. Setting the cut-off value at 0.9×10^-3, the ADC values had a sensitivity of 72.2% and a specificity of 88.2% for predicting malignancy.

CONCLUSION

For SPN follow-up, a new following-up protocol can be safely established using DWI and ADC mapping. Using these MRI parameters might decrease unnecessary biopsy rates and complications of biopsies.

Optimizing diffusion-weighted magnetic resonance imaging for evaluation of lung tumors: A comparison of respiratory triggered and free breathing techniques

Purpose

The aim of this study was to compare respiratory-triggered (RT) and free breathing (FB) diffusion weighted imaging (DWI) techniques regarding apparent diffusion coefficient (ADC) measurements and repeatability in non-squamous non-small cell lung cancer (NSCLC) measuring the total tumor volume.

Material and Methods

A total of 57 magnetic resonance imaging (MRI) examinations were analyzed. DWI was obtained by a single-shot spin-echo echo-planar imaging sequence, and for each MRI examination 2 consecutive RT and 2 consecutive FB DWI sequences were performed. Two radiologists independently read the images and made measurements. For each tumor the mean ADC value of the whole tumor volume was calculated. The difference in mean ADCs between FB and RT DWI was evaluated using the paired-sample t-test. The repeatability of ADC measurements related to imaging method was evaluated by intra class correlations (ICC) for each of the FB and RT DWI pairs.

Results

There were no significant differences in mean ADCs between FB and RT (Reader 1 p = 0.346, Reader 2 p = 0.583). The overall repeatability of ADC measurement was good for both acquisition methods, with ICCs > 0.9. Subgroup analysis showed somewhat poorer repeatability in small tumors (50 ml or less) and tumors in the lower lung zones for the RT acquisition, with ICC as low as 0.72.

Conclusions

No difference in ADC measurement or repeatability between FB and RT DWI in whole lesion ADC measurements of adenocarcinomas in the lung was demonstrated. The results imply that in this setting the FB acquisition method is accurate and possibly more robust than the RT acquisition technique.

Diffusion MRI of cancer: From low to high b-values

Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.

Development of a robust diffusion-MR elastography (dMRE) technique to mitigate intravoxel phase dispersion

Diffusion-magnetic resonance elastography (dMRE) is an emerging practical technique that can acquire diffusion magnetic resonance imaging and MRE simultaneously. However, a signal loss attributable to intravoxel phase dispersion (IVPD) interferes with the calculation of the apparent diffusion coefficient (ADC). This study presents an approach to dMRE that reduces the influence of IVPD by introducing a new pulse sequence. The existing and proposed techniques were performed using a phantom comprising five rods with different elasticities at 60 Hz vibration to investigate the accuracy of previous and proposed dMRE techniques. The measures of ADC and stiffness, obtained by using both dMRE techniques, were compared with conventional spin-echo (SE) diffusion and SE-MRE. Then, we evaluated those differences by using the mean of absolute differences (MAD) in each rod within the phantom. The results of the MAD of the stiffness from both dMRE techniques showed almost no difference. In contrast, the value of the ADC MAD (MAD ≒ 0.16 × 10^-3 mm²/s), obtained in the soft region within the phantom with the previous dMRE technique, was large. This value was about 2.7 times that of the value produced by the proposed dMRE technique. This difference must reflect the degree of influence of IVPD in both techniques. These results demonstrate that our dMRE technique is a robust method for addressing the signal loss attributable to IVPD.

Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters

Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) has gained wide attention as potential tool for differentiating between malignant and benign solitary pulmonary lesions (SPLs). The overall effects of multiple histopathological parameters on ADC have not been elucidated, which may help to explain the overlapping of ADC between malignant and benign SPLs. The study sought to explore associations between ADC and histopathological parameters in SPLs, and to compare diagnostic capability of ADC among different types of SPLs. Multiple histopathological parameters (cell density, nuclear-to-cytoplasm ratio, necrotic fraction, presence of mucus and grade of differentiation) were quantified in 52 malignant and 13 benign SPLs with surgical pathology available. Cell density (β = −0.40) and presence of mucus (β = 0.77) were independently correlated with ADC in malignant SPLs. The accurate diagnosis rate of squamous carcinomas, adenocarcinomas without mucus and malignant tumors with mucus was 100%, 82% and 0%, respectively. Our study suggested that cell density and presence of mucus are independently correlated with ADC in malignant SPLs. Squamous carcinoma maybe more accurately diagnosed as malignancy by ADC value. Malignant SPLs with mucus and adenocarcinomas with low cell density should be kept in mind in differentiating SPLs using ADC because of insufficient diagnostic capability.

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology.

KEY POINTS

• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

Comparison between multi-slice spiral CT and magnetic resonance imaging in the diagnosis of peritoneal metastasis in primary ovarian carcinoma

The advent of disease evaluation by means of multi-slice spiral computed tomography (MSCT) and magnetic resonance imaging (MRI) represents a continually emerging role in the evaluation of various diseases; however, its role is yet to be adequately defined. Thus, the aim of the study was to compare the diagnostic value of MSCT and MRI in the diagnosis of peritoneal metastasis in primary ovarian carcinoma. Between January 2013 and December 2015, MSCT or MRI data were collected from 42 patients who had been previously diagnosed with peritoneal metastasis of ovarian carcinoma at the First Affiliated Hospital of Kunming Medical University. The tumor location, size, edge, and shape were all evaluated independently by three qualified imaging physicians using a double-blind method to confirm whether the patients were indeed suffering from peritoneal metastasis, as well as to rank the metastatic lesions recorded on a five-point scale. It was hypothesized that MRI and MSCT were comparable in the evaluation of ovarian carcinoma. Therefore, a receiver operating characteristics (ROC) curve was used to analyze the results and also to directly compare the respective diagnostic values of MSCT and MRI. In total, 165 metastatic lesions were confirmed by means of surgical operation. MSCT revealed 131 metastatic lesions, while MRI confirmed 154 metastatic lesions. The metastatic sites were primarily located on the subphrenic, epiploon, and gastrocolic ligaments and were further confirmed by either MRI or CT. In regard to MSCT, the most common site of underdiagnoses was in the vicinity of the uterus-rectum-fossa. MRI displayed a high detection rate in every site. The omission diagnostic rate of MSCT and MRI were 20.61% and 6.67%, respectively, while the accuracy rates were 79.39% and 93.33%, respectively. The obtained results revealed that the MSCT value of area under the ROC curve was smaller than that for MRI. Our findings provided evidence asserting that MRI, in comparison to MSCT, was more accurate in diagnosing peritoneal metastasis in patients with ovarian carcinoma.

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors

The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADCmin- and SUVmax-voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance (D) between ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = -0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation.

Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability

PURPOSE

To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision.

METHODS

Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b = 100, 500 and 800smm-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility.

RESULTS

Whole-tumour ADC values ranged from 0.66-1.94x10-3mm2s-1 (mean = 1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7-9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9-5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson's R2 = 0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%.

CONCLUSION

A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change.

KEY POINTS

• In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement. • ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm. • ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm. • ADC measurement precision is unaffected by the post-processing software used. • In multicentre trials, 22% increase in ADC indicates positive treatment response.

Monitoring Tumor Volume in Patients With Prostate Cancer Undergoing Active Surveillance: Is MRI Apparent Diffusion Coefficient Indicative of Tumor Growth?

OBJECTIVE

The purpose of this study was to measure longitudinal change in tumor volume of the dominant intraprostatic lesion and determine whether baseline apparent diffusion coefficient (ADC) and change in ADC are indicative of tumor growth in patients with prostate cancer undergoing active surveillance.

SUBJECTS AND METHODS

The study group included 151 men (mean age, 68.1 ± 7.4 [SD] years; range, 50-83 years) undergoing active surveillance with 3D whole prostate, zonal, and tumor volumetric findings documented at endorectal MRI examinations performed at two time points (median interval, 1.9 years). Tumor (location confirmed at transrectal ultrasound or template biopsy) ADC was measured on the slice with the largest lesion. Twenty randomly selected patients had the measurements repeated by the same observer after a greater than 4-month interval, and the limits of agreement of measurements were calculated. Tumor volume increases greater than the upper limit of agreement were designated measurable growth, and their baseline ADCs and change in ADC were compared with those of tumors without measurable growth (independent-samples t test).

RESULTS

Fifty-two (34.4%) tumors increased measurably in volume. Baseline ADC and tumor volume were negatively correlated (r = -0.42, p = 0.001). Baseline ADC values did not differ between those with and those without measurable growth (p = 0.06), but change in ADC was significantly different (-6.8% ± 12.3% for those with measurable growth vs 0.23% ± 10.1% for those without, p = 0.0005). Percentage change in tumor volume and percentage change in ADC were negatively correlated (r = -0.31, p = 0.0001). A 5.8% reduction in ADC indicated a measurable increase in tumor volume with 54.9% sensitivity and 77.0% specificity (AUC, 0.67).

CONCLUSION

Tumor volume increased measurably in 34.4% of men after 2 years of active surveillance. Change in ADC may be used to identify tumors with measurable growth.

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.

Diffusion MRI in early cancer therapeutic response assessment

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PURPOSE

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion.

MATERIALS AND METHODS

We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features.

RESULTS

The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648.

CONCLUSIONS

ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Is it better to include necrosis in apparent diffusion coefficient (ADC) measurements? The necrosis/wall ADC ratio to differentiate malignant and benign necrotic lung lesions: Preliminary results

PURPOSE

To determine whether the use of necrosis/wall apparent diffusion coefficient (ADC) ratios in the differentiation of necrotic lung lesions is more reliable than measuring the wall alone.

MATERIALS AND METHODS

In this retrospective study, a total of 76 patients (54 males and 22 females, 71% vs. 29%, with a mean age of 53 ± 18 years, range, 18-84) were enrolled, 33 of whom had lung carcinoma and 43 had a benign necrotic lung lesion. A 3T scanner was used. The calculation of the necrosis/wall ADC ratio was based on ADC values measured from necrosis and the wall of the lesions by diffusion-weighted imaging (DWI). Statistical analyses were performed with the independent samples t-test and receiver operating characteristic analysis. Intraobserver and interobserver reliability were calculated for ADC values of wall and necrosis.

RESULTS

The mean necrosis/wall ADC ratio was 1.67 ± 0.23 for malignant lesions and 0.75 ± 0.19 for benign lung lesions (P < 0.001). To estimate malignancy the area under the curve (AUC) values for necrosis ADC, wall ADC, and the necrosis/wall ADC ratio were 0.720, 0.073, and 0.997, respectively. A wall/necrosis ADC ratio cutoff value of 1.12 demonstrated a 100% sensitivity and 98% specificity in the estimation of malignancy. Positive predictive value was 100%, and negative predictive value 98% and diagnostic accuracy 99%. There was a good intraobserver and interobserver reliability for wall and necrosis.

CONCLUSION

The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating lung carcinoma from benign necrotic lung lesions than measuring the wall alone.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1001-1006.

Non-Gaussian diffusion imaging for malignant and benign pulmonary nodule differentiation: a preliminary study

BACKGROUND

Diffusion-weighted imaging (DWI) derived apparent diffusion coefficient (ADC) has demonstrated inconsistent results in pulmonary nodule differentiation. Diffusion kurtosis imaging (DKI), which quantifies non-Gaussian diffusion, is believed to better characterize tissue micro-structure than conventional DWI.

PURPOSE

To assess the feasibility of DKI in human lungs and to compare its diagnostic value with standard DWI in differentiating malignancies from benign pulmonary nodules.

MATERIAL AND METHODS

Thirty-five pulmonary nodules in 32 consecutive patients were evaluated by DKI by using 3b-values of 0, 500, and 1000 s/mm² and conventional DWI with b values of 0 and 800 s/mm². Two observers independently evaluated and compared diagnostic accuracy of mean kurtosis (MK) and ADC values in differentiating malignancies from benign pulmonary nodules. The intra- and inter-observer repeatability (intra-class correlation coefficient [ICC]) were also assessed for each derived measures.

RESULTS

The diagnostic accuracy, and the area under curve (AUC) in differentiating malignancies from benign pulmonary nodule, were not significantly higher for MK (Obs. 1a: 85.70%, 0.87; Obs. 1b: 80.00%, 0.80; and Obs. 2: 82.80%, 0.91) as compared to ADC (Obs. 1a: 77.14%, 0.81; Obs. 1b: 80.00%, 0.85; and Obs. 2: 77.14%, 0.85 respectively). The intra- and inter-observer agreement (ICC) for malignant and benign lesions was substantial for each reading.

CONCLUSION

The initial results of this study indicate the feasibility of DKI in human lungs. However, there was no significant benefit of DKI derived MK values over ADC for malignant and benign pulmonary nodule differentiation.

Inter- and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI

OBJECTIVE

To prospectively evaluate the inter- and intraobserver agreement of apparent diffusion coefficient (ADC) measurements in free breathing, breath-hold, and respiratory triggered diffusion-weighted imaging (DWI) of lung cancer.

METHODS

Twenty-two patients with lung cancer (tumor size >2cm) underwent DWIs (3.0T) in three imaging methods. Lesion ADCs were measured twice by both of the two independent observers and compared.

RESULTS

No statistical significance was found among methods, though respiratory-triggered DWI tended to have higher ADCs than breath-hold DWI. Great inter- and intraobserver agreement was shown.

CONCLUSION

ADCs had good inter- and intraobserver agreement in all three DWI methods.

Magnetic resonance imaging in lung: a review of its potential for radiotherapy

MRI has superior soft-tissue definition compared with existing imaging modalities in radiation oncology; this has the added benefit of functional as well as anatomical imaging. This review aimed to evaluate the current use of MRI for lung cancer and identify the potential of a MRI protocol for lung radiotherapy (RT). 30 relevant studies were identified. Improvements in MRI technology have overcome some of the initial limitations of utilizing MRI for lung imaging. A number of commercially available and novel sequences have shown image quality to be adequate for the detection of pulmonary nodules with the potential for tumour delineation. Quantifying tumour motion is also feasible and may be more representative than that seen on four-dimensional CT. Functional MRI sequences have shown correlation with flu-deoxy-glucose positron emission tomography (FDG-PET) in identifying malignant involvement and treatment response. MRI can also be used as a measure of pulmonary function. While there are some limitations for the adoption of MRI in RT-planning process for lung cancer, MRI has shown the potential to compete with both CT and PET for tumour delineation and motion definition, with the added benefit of functional information. MRI is well placed to become a significant imaging modality in RT for lung cancer.

Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer

The purpose of this study was to determine optimal sets of b-values in diffusion-weighted MRI (DW-MRI) for obtaining monoexponential apparent diffusion coefficient (ADC) close to perfusion-insensitive intravoxel incoherent motion (IVIM) model ADC (ADCIVIM) in non-small cell lung cancer. Ten subjects had 40 DW-MRI scans before and during radiotherapy in a 1.5 T MRI scanner. Respiratory triggering was applied to the echo-planar DW-MRI with TR ≈ 4500 ms, TE  =  74 ms, eight b-values of 0-1000 μs μm(-2), pixel size  =  1.98 × 1.98 mm(2), slice thickness  =  6 mm, interslice gap  =  1.2 mm, 7 axial slices and total acquisition time ≈6 min. One or more DW-MRI scans together covered the whole tumour volume. Monoexponential model ADC values using various b-value sets were compared to reference-standard ADCIVIM values using all eight b-values. Intra-scan coefficient of variation (CV) of active tumour volumes was computed to compare the relative noise in ADC maps. ADC values for one pre-treatment DW-MRI scan of each of the 10 subjects were computed using b-value pairs from DW-MRI images synthesized for b-values of 0-2000 μs μm(-2) from the estimated IVIM parametric maps and corrupted by various Rician noise levels. The square root of mean of squared error percentage (RMSE) of the ADC value relative to the corresponding ADCIVIM for the tumour volume of the scan was computed. Monoexponential ADC values for the b-value sets of 250 and 1000; 250, 500 and 1000; 250, 650 and 1000; 250, 800 and 1000; and 250-1000 μs μm(-2) were not significantly different from ADCIVIM values (p > 0.05, paired t-test). Mean error in ADC values for these sets relative to ADCIVIM were within 3.5%. Intra-scan CVs for these sets were comparable to that for ADCIVIM. The monoexponential ADC values for other sets-0-1000; 50-1000; 100-1000; 500-1000; and 250 and 800 μs μm(-2) were significantly different from the ADCIVIM values. From Rician noise simulation using b-value pairs, there was a wide range of acceptable b-value pairs giving small RMSE of ADC values relative to ADCIVIM. The pairs for small RMSE had lower b-values as the noise level increased. ADC values of a two b-value set-250 and 1000 μs μm(-2), and all three b-value sets with 250, 1000 μs μm(-2) and an intermediate value approached ADCIVIM, with relative noise comparable to that of ADCIVIM. These sets may be used in lung tumours using comparatively short scan and post-processing times. Rician noise simulation suggested that the b-values in the vicinity of these experimental best b-values can be used with error within an acceptable limit. It also suggested that the optimal sets will have lower b-values as the noise level becomes higher.

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

Diffusion-weighted magnetic resonance imaging (DW-MRI) is used extensively to improve tumour detection and localization because it offers excellent soft tissue contrast between malignant and non-malignant tissues. It also provides a quantitative biomarker; the apparent diffusion coefficient (ADC) can be derived from DW-MRI sequences using multiple diffusion weightings. ADC reflects the tumour microenvironment, e.g. cell membrane integrity and cellularity and has potential for reporting on tumour aggressiveness. This review focuses on the use of the DW-MRI derived imaging biomarker ADC to reflect tumour aggressiveness and its potential impact in managing pelvic cancer patients. The clinical studies which evaluate the role of ADC in pelvic tumours (prostate, bladder, rectal, ovary, cervix and uterus) are summarized and the evidence linking ADC values with tumour aggressiveness is evaluated.

Apparent diffusion coefficient values of diffusion-weighted imaging for distinguishing focal pulmonary lesions and characterizing the subtype of lung cancer: a meta-analysis

OBJECTIVES

The potential performance of apparent diffusion coefficient (ADC) values for distinguishing malignant and benign pulmonary lesions, further characterizing the subtype of lung cancer was assessed.

METHODS

PubMed, EMBASE, Cochrane Library, EBSCO, and three Chinese databases were searched to identify eligible studies on diffusion-weighted imaging (DWI) of focal pulmonary lesions. ADC values of malignant and benign lesions were extracted by lesion type and statistically pooled based on a linear mixed model. Further analysis for subtype of lung cancer was also performed. The methodological quality was assessed using the quality assessment of diagnostic accuracy studies tool.

RESULTS

Thirty-four articles involving 2086 patients were included. Malignant pulmonary lesions have significantly lower ADC values than benign lesions [1.21 (95% CI, 1.19-1.22) mm(2)/s vs. 1.76 (95% CI, 1.72-1.80) mm(2)/s; P < 0.05]. There is a significant difference between ADC values of small cell lung cancer and non-small cell lung cancer (P < 0.05), while the differences were not significant among histological subtypes of lung cancer. The methodological quality was relatively high, and the data points from Begg's test indicated that there was probably no obvious publication bias.

CONCLUSIONS

The ADC value is helpful for distinguishing malignant and benign pulmonary lesions and provides a promising method for differentiation of SCLC from NSCLC.

KEY POINTS

• This meta-analysis assesses the role of DWI in pulmonary lesions. • Differentiation and classification subtype of lung cancer is essential for treatment decision-making. • ADC values can help distinguish between malignant and benign lesions. • ADC values might help characterize the subtype of lung cancer.

Correlation of the apparent diffusion coefficient (ADC) with the standardized uptake value (SUV) in lymph node metastases of non-small cell lung cancer (NSCLC) patients using hybrid 18F-FDG PET/MRI

Objective

To compare the apparent diffusion coefficient (ADC) in lymph node metastases of non-small cell lung cancer (NSCLC) patients with standardized uptake values (SUV) derived from combined 18F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI).

Material and Methods

38 patients with histopathologically proven NSCLC (mean age 60.1 ± 9.5y) received whole-body PET/CT (Siemens mCT™) 60min after injection of a mean dose of 280 ± 50 MBq 18F-FDG and subsequent PET/MRI (mean time after tracer injection: 139 ± 26 min, Siemens Biograph mMR). During PET acquisition, simultaneous diffusion-weighted imaging (DWI, b values: 0, 500, 1000 s/mm²) was performed. A maximum of 10 lymph nodes per patient suspicious for malignancy were analyzed. Regions of interest (ROI) were drawn covering the entire lymph node on the attenuation-corrected PET-image and the monoexponential ADC-map. According to histopathology or radiological follow-up, lymph nodes were classified as benign or malignant. Pearson’s correlation coefficients were calculated for all lymph node metastases correlating SUV_max and SUV_mean with ADC_mean.

Results

A total of 146 suspicious lymph nodes were found in 25 patients. One hundred lymph nodes were eligible for final analysis. Ninety-one lymph nodes were classified as malignant and 9 as benign according to the reference standard. In malignant lesions, mean SUV_max was 9.1 ± 3.8 and mean SUV_mean was 6.0 ± 2.5 while mean ADC_mean was 877.0 ± 128.6 x10^-5 mm²/s in PET/MRI. For all malignant lymph nodes, a weak, inverse correlation between SUV_max and ADC_mean as well as SUV_mean and ADC_mean (r = -0.30, p<0.05 and r = -0.36, p<0.05) existed.

Conclusion

The present data show a weak inverse correlation between increased glucose-metabolism and cellularity in lymph node metastases of NSCLC patients. 18F-FDG-PET and DWI thus may offer complementary information for the evaluation of treatment response in lymph node metastases of NSCLC.

Value of diffusion-weighted MR imaging using various parameters for assessment and characterization of solitary pulmonary nodules

OBJECTIVES

To determine the appropriate parameters and evaluation method for characterizing solitary pulmonary nodules (SPNs) using quantitative parameters of diffusion-weighted imaging (DWI).

METHODS

Thirty-two subjects with 36 SPNs underwent DWI with seven different b values (0, 50, 100, 150, 300, 500, and 1000s/mm(2)). Five quantitative parameters were obtained from the region of interest drawn over each SPN: apparent diffusion coefficients (ADCs), true diffusion coefficients (DCs), and perfusion fractions (PFs), and signal-intensity ratios between lesion and spinal cord from DWI (b values: 1000 [LSR1000] and 500 [LSR500)]). All quantitative parameters and the diagnostic capabilities were statistically compared.

RESULTS

SPNs were diagnosed as follow: malignant (n=27) and benign (n=9). Parameter comparisons for malignant and benign showed both LSRs differed significantly (p<0.05). Applying feasible threshold values showed LSR500 specificity (88.9% [8/9]) and accuracy (77.8% [28/36]) were significantly higher than ADC, DC, and PF specificity and accuracy (p<0.05). LSR1000 accuracy (72.2% [26/36]) was significantly higher than DC accuracy, and its specificity (88.9% [8/9]) was significantly higher than ADC, DC, and PF specificities (p<0.05).

CONCLUSIONS

For quantitative differentiation of SPNs, LSR evaluation was more useful and practical than ADC, DC, and PF, and choice of b values showed little impact for the differentiation.