High-b-value diffusion-weighted MR imaging for pretreatment prediction and early monitoring of tumor response to therapy in mice

Diffusion weighted imaging combining respiratory triggering and navigator echo tracking in the upper abdomen

OBJECTIVES

To evaluate a new motion correction method, named RT + NV Track, for upper abdominal DWI that combines the respiratory triggering (RT) method using a respiration sensor and the Navigator Track (NV Track) method using navigator echoes.

MATERIALS AND METHODS

To evaluate image quality acquired upper abdominal DWI and ADC images with RT, NV, and RT + NV Track in 10 healthy volunteers and 35 patients, signal-to-noise efficiency (SNRefficiency) and the coefficient of variation (CV) of ADC values were measured. Five radiologists independently performed qualitative image-analysis assessments.

RESULTS

RT + NV Track showed significantly higher SNRefficiency than RT and NV (14.01 ± 4.86 vs 12.05 ± 4.65, 10.05 ± 3.18; p < 0.001, p < 0.001). RT + NV Track was superior to RT and equal or better quality than NV in CV and visual evaluation of ADC values (0.033 ± 0.018 vs 0.080 ± 0.042, 0.057 ± 0.034; p < 0.001, p < 0.001). RT + NV Track tends to acquire only expiratory data rather than NV, even in patients with relatively rapid breathing, and can correct for respiratory depth variations, a weakness of RT, thus minimizing image quality degradation.

CONCLUSION

The RT + NV Track method is an efficient imaging method that combines the advantages of both RT and NV methods in upper abdominal DWI, providing stably good images in a short scan time.

Feature selection based on unsupervised clustering evaluation for predicting neoadjuvant chemoradiation response for patients with locally advanced rectal cancer

Accurate response prediction allows for personalized cancer treatment of locally advanced rectal cancer (LARC) with neoadjuvant chemoradiation. In this work, we designed a convolutional neural network (CNN) feature extractor with switchable 3D and 2D convolutional kernels to extract deep learning features for response prediction. Compared with radiomics features, convolutional kernels may adaptively extract local or global image features from multi-modal MR sequences without the need of feature predefinition. We then developed an unsupervised clustering based evaluation method to improve the feature selection operation in the feature space formed by the combination of CNN features and radiomics features. While normal process of feature selection generally includes the operations of classifier training and classification execution, the process needs to be repeated many times after new feature combinations were found to evaluate the model performance, which incurs a significant time cost. To address this issue, we proposed a cost effective process to use a constructed unsupervised clustering analysis indicator to replace the classifier training process by indirectly evaluating the quality of new found feature combinations in feature selection process. We evaluated the proposed method using 43 LARC patients underwent neoadjuvant chemoradiation. Our prediction model achieved accuracy, area-under-curve (AUC), sensitivity and specificity of 0.852, 0.871, 0.868, and 0.735 respectively. Compared with traditional radiomics methods, the prediction models (AUC = 0.846) based on deep learning-based feature sets are significantly better than traditional radiomics methods (AUC = 0.714). The experiments also showed following findings: (1) the features with higher predictive power are mainly from high-order abstract features extracted by CNN on ADC images and T2 images; (2) both ADC_Radiomics and ADC_CNN features are more advantageous for predicting treatment responses than the radiomics and CNN features extracted from T2 images; (3) 3D CNN features are more effective than 2D CNN features in the treatment response prediction. The proposed unsupervised clustering indicator is feasible with low computational cost, which facilitates the discovery of valuable solutions by highlighting the correlation and complementarity between different types of features.

Volumetric apparent diffusion coefficient (ADC) histogram metrics as imaging biomarkers for pretreatment predicting response to fertility-sparing treatment in patients with endometrial cancer

OBJECTIVES

To investigate the feasibility of volumetric apparent diffusion coefficient (ADC) histogram analysis for prediction of fertility-sparing treatment (FST) response in patients with endometrial cancer (EC).

METHODS

Pretreatment data of 54 EC patients with FST were retrospectively analyzed. Treatment response at each follow-up was pathologically evaluated. The associations of ADC histogram metrics (volume, minADC, maxADC, meanADC; 10th, 25th, 50th, 75th and 90th ADC percentiles; skewness; kurtosis) and baseline clinical characteristics with complete response (CR) at the second and third follow-ups, two-consecutive CR, and recurrence at the final follow-up were evaluated by uni- and multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used for diagnostic performance evaluation.

RESULTS

Compared with non-CR patients, CR patients had significantly higher minADC and 10th and 25th ADC percentiles at the second follow-up (P = 0.008, 0.039, and 0.034, respectively) and higher minADC, older age, lower HE4 level, and higher overweight rate at the third follow-up (P = 0.001, 0.040, 0.021, and 0.004, respectively). Patients with two-consecutive CR had a significantly higher minADC than those without (P = 0.018). There was no association between ADC metrics or clinical characteristics and recurrence (all P > 0.05). MinADC yielded the largest AUC in predicting CR (0.688 and 0.735 at the second and third follow-up, respectively) and the presence of two-consecutive CR (0.753). When combined with patient age and HE4 level, the prediction of CR could be further improved at the third follow-up, with an AUC of 0.786.

CONCLUSION

Pretreatment minADC could be a potential imaging biomarker for predicting FST response. Clinical characteristics may have incremental value to minADC in predicting CR.

Feasibility of diffusion-weighted magnetic resonance imaging in evaluation of early therapeutic response after CT-guided microwave ablation of inoperable lung neoplasms

Objective

To determine the early treatment response after microwave ablation (MWA) of inoperable lung neoplasms using the apparent diffusion coefficient (ADC) value calculated 24 h after the ablation.

Materials and methods

This retrospective study included 47 patients with 68 lung lesions, who underwent percutaneous MWA from January 2008 to December 2017. Evaluation of the lesions was done using MRI including DWI sequence with ADC value calculation pre-ablation and 24 h post-ablation. DWI-MR was performed with b values (50, 400, 800 mm²/s). The post-ablation follow-up was performed using chest CT and/or MRI within 24 h following the procedure; after 3, 6, 9, and 12 months; and every 6 months onwards to determine the local tumor response. The post-ablation ADC value changes were compared to the end response of the lesions.

Results

Forty-seven patients (mean age: 63.8 ± 14.2 years, 25 women) with 68 lesions having a mean tumor size of 1.5 ± 0.9 cm (range: 0.7–5 cm) were evaluated. Sixty-one lesions (89.7%) showed a complete treatment response, and the remaining 7 lesions (10.3%) showed a local progression (residual activity). There was a statistically significant difference regarding the ADC value measured 24 h after the ablation between the responding (1.7 ± 0.3 × 10⁻³ mm²/s) and non-responding groups (1.4 ± 0.3 × 10⁻³ mm²/s) with significantly higher values in the responding group (p = 0.001). A suggested ADC cut-off value of 1.42 could be used as a reference point for the post-ablation response prediction (sensitivity: 66.67%, specificity: 84.21%, PPV: 66.7%, and NPV: 84.2%). No significant difference was reported regarding the ADC value performed before the ablation as a factor for the prognosis of treatment response (p = 0.86).

Conclusion

ADC value assessment following ablation may allow the early prediction of treatment efficacy after MWA of inoperable lung neoplasms.

Key Points

• ADC value calculated 24 h post-treatment may allow the early prediction of MWA efficacy as a treatment of pulmonary tumors and can be used in the early immediate post-ablation imaging follow-up.

• The pre-treatment ADC value of lung neoplasms is not different between the responding and non-responding tumors.

Statistical Evaluation of Different Mathematical Models for Diffusion Weighted Imaging of Prostate Cancer Xenografts in Mice

Purpose

To evaluate fitting quality and repeatability of four mathematical models for diffusion weighted imaging (DWI) during tumor progression in mouse xenograft model of prostate cancer.

Methods

Human prostate cancer cells (PC-3) were implanted subcutaneously in right hind limbs of 11 immunodeficient mice. Tumor growth was followed by weekly DWI examinations using a 7T MR scanner. Additional DWI examination was performed after repositioning following the fourth DWI examination to evaluate short term repeatability. DWI was performed using 15 and 12 b-values in the ranges of 0-500 and 0-2000 s/mm², respectively. Corrected Akaike information criteria and F-ratio were used to evaluate fitting quality of each model (mono-exponential, stretched exponential, kurtosis, and bi-exponential).

Results

Significant changes were observed in DWI data during the tumor growth, indicated by ADC_m, ADC_s, and ADC_k. Similar results were obtained using low as well as high b-values. No marked changes in model preference were present between the weeks 1−4. The parameters of the mono-exponential, stretched exponential, and kurtosis models had smaller confidence interval and coefficient of repeatability values than the parameters of the bi-exponential model.

Conclusion

Stretched exponential and kurtosis models showed better fit to DWI data than the mono-exponential model and presented with good repeatability.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm²/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10^-3 mm²/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10^-3 mm²/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Biparametric (bp) and multiparametric (mp) magnetic resonance imaging (MRI) approach to prostate cancer disease: a narrative review of current debate on dynamic contrast enhancement

Prostate cancer is the most common malignancy in male population. Over the last few years, magnetic resonance imaging (MRI) has proved to be a robust clinical tool for identification and staging of clinically significant prostate cancer. Though suggestions by the European Society of Urogenital Radiology to use complete multiparametric (mp) T2-weighted/diffusion weighted imaging (DWI)/dynamic contrast enhancement (DCE) acquisition for all prostate MRI examinations, the real advantage of functional DCE remains a matter of debate. Recent studies demonstrate that biparametric (bp) and mp approaches have similar accuracy, but controversial evidences remain, and the specific potential benefits of contrast medium administration are still poorly discussed in literature. The bp approach is in fact sufficient in most cases to adequately identify a negative test, or to accurately define the degree of aggressiveness of a lesion, especially if larger or with major characteristics of malignancy. This feature would give the DCE a secondary role, probably limited to a second evaluation of the lesion location, for detecting small cancer or in case of controversy. However, DCE has proved to increase the sensitivity of prostate MRI, though a less specificity. Therefore, an appropriate decision algorithm is needed to standardize the MRI approach. Aim of this review study was to provide a schematic description of bpMRI and mpMRI approaches in the study of prostatic anatomy, focusing on comparative validity and current DCE application. Additional theoretical considerations on prostate MRI are provided.

Preclinical Applications of Magnetic Resonance Imaging in Oncology

The evolving possibilities of molecular imaging (MI) are fundamentally changing the way we look at cancer, with imaging paradigms now shifting away from basic morphological measures toward the longitudinal assessment of functional, metabolic, cellular, and molecular information in vivo. Recent developments of imaging methodology and probe molecules utilizing the vast number of novel animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anticancer treatments. While preclinical molecular imaging offers a whole palette of excellent methodology to choose from, we will focus on magnetic resonance imaging (MRI) techniques, since they provide excellent molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values, and limitations of MRI as molecular imaging modality and comment on its high potential to non-invasively assess information on metabolism, hypoxia, angiogenesis, and cell trafficking in preclinical cancer research.

Gastric Cancer Staging: Is It Time for Magnetic Resonance Imaging?

Gastric cancer (GC) is a common cancer worldwide. Its incidence and mortality vary depending on geographic area, with the highest rates in Asian countries, particularly in China, Japan, and South Korea. Accurate imaging staging has become crucial for the application of various treatment strategies, especially for curative treatments in early stages. Unfortunately, most GCs are still diagnosed at an advanced stage, with the peritoneum (61-80%), distant lymph nodes (44-50%), and liver (26-38%) as the most common metastatic locations. Metastatic disease is limited to the peritoneum in 58% of cases; in nonperitoneal distant metastases, the most involved GC metastasization site is the liver (82%). The eighth edition of the tumor-node-metastasis staging system is the most commonly used system for determining GC prognosis. Endoscopic ultrasonography, computed tomography, and 18-fluorideoxyglucose positron emission tomography are historically the most accurate imaging techniques for GC staging. However, studies have recently shown renewed interest in magnetic resonance imaging (MRI) as a useful tool in GC staging, especially for distant metastasis assessment. The technical improvement of diffusion-weighted imaging and the increasing use of hepatobiliary contrast agents have been shown to increase the diagnostic performance of MRI, particularly for detecting peritoneal and liver metastasis. However, no principal oncological guidelines have included the use of MRI as a first-line technique for distant metastasis evaluation during the GC staging process, such as the National Comprehensive Cancer Network Guidelines. This review analyzed the role of the principal imaging techniques in GC diagnosis and staging, focusing on the potential role of MRI, especially for assessing peritoneal and liver metastases.

Diffusion weighted magnetic resonance imaging (DW-MRI) as a non-invasive, tissue cellularity marker to monitor cancer treatment response

Background

Diffusion weighted magnetic resonance imaging (DW-MRI) holds great potential for monitoring treatment response in cancer patients shortly after initiation of radiotherapy. It is hypothesized that a decrease in cellular density of irradiated cancerous tissue will lead to an increase in quantitative apparent diffusion coefficient (ADC) values. DW-MRI can therefore serve as a non-invasive marker of cell death and apoptosis in response to treatment. In the present study, we aimed to investigate the applicability of DW-MRI in preclinical models to monitor radiation-induced treatment response. In addition, we compared DW-MRI with ex vivo measures of cell density, cell death and apoptosis.

Methods

DW-MRI was tested in two different syngeneic mouse models, a colorectal cancer (CT26) and a breast cancer (4 T1). ADC values were compared with quantitative determinations of apoptosis and cell death by flow cytometry. Furthermore, ADC-values were also compared to histological measurement of cell density on tumor sections.

Results

We found a significant correlation between ADC-values and apoptotic state in the CT26 model (P = 0.0031). A strong correlation between the two measurements of ADC-value and apoptotic state was found in both models, which were also present when comparing ADC-values to cell densities.

Conclusions

Our findings demonstrate that DW-MRI can be used for non-invasive monitoring of radiation-induced changes in cell state during cancer therapy. ADC values reflect ex vivo cell density and correlates well with apoptotic state, and can hereby be described as a marker for the cell state after therapy and used as a non-invasive response marker.

Multiple b values of diffusion-weighted magnetic resonance imaging in evaluation of solid head and neck masses

Background

Differentiation between malignant and benign masses is essential for treatment planning and helps in improving the prognosis of malignant tumors; the aim of this work is to determine the role of diffusion-weighted magnetic resonance imaging (DW-MRI) and the apparent diffusion coefficient (ADC) in the differentiation between benign and malignant solid head and neck masses by comparing diagnostic performance of low b values (0.50 and 400 s/mm2) versus high b values (800 and 1000 s/mm2) and comparing the result with histopathological finding.

Results

The study included 60 patients (34 male and 26 female) with solid head and neck masses > 1 cm who referred to radiodiagnosis department for MRI evaluation. Multiple b values were used 50, 400, 800, and 1000 s/mm2 (at least 2 b values). DWI and ADC value of all 60 patients were acquired. Mean ADC values of both malignant and benign masses were statistically measured and compared, and cut off value was determined. Solid head and neck masses in our study DWI with the use of high b value 800 and 1000 s/mm2 were of higher significance (P value 0.001*). There was a significant difference in the mean ADC value between benign and malignant masses (P < 0.01); solid masses were divided into 2 categories: (a) malignant lesions 46.7% (n = 28) with mean ADC value (0.82 ± 0.19) × 10−3 s/mm2 and (b) benign lesions 53.3% (n = 32) with mean ADC value (2.05 ± 0.46) × 10−3 s/mm2) with ADC cutoff value of 1.0 × 10−3 s/mm2 and 94% sensitivity, 93% specificity, negative predictive value (NPV) = 94%, positive predictive value (PPV) 93%, and an accuracy of 93.5%.

Conclusion

The DWI with ADC mapping were valuable as non-invasive tools in differentiating between benign and malignant solid head and neck masses. The use of high b value 800 and 1000 s/mm2 was of higher significance (P value 0.001*) in differentiation between benign and malignant lesion than that with low b values 0, 50, and 400 s/mm2 (0.01). The mean ADC values were significantly lower in malignant solid masses. Attention had to be paid to the choice of b values in MRI-DWI in the head and neck region.

Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

OBJECTIVE

To determine whether intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) derived parameters can be associated with tumour stage of oesophageal squamous cell carcinoma (SCC).

METHODS

60 patients with resectable oesophageal SCC and 20 healthy individuals underwent oesophageal DWI-using multi b-values with a 3.0 T MR system. Pure diffusion coefficient (D), perfusion-related incoherent microcirculation (D*), microvascular volume fraction (f) and apparent diffusion coefficient (ADC) were measured on DWI. Statistical analyses were performed to determine associations of DWI-derived parameters with T-stage.

RESULTS

ADC (r = -0.842), D (r = -0.729), D* (r = -0.301) and f (r = -0.817) were negatively correlated with T-stage of oesophageal SCC (all p < 0.01), and the multinominal regression analyses revealed that IVIM-derived parameters including D (p = 0.038; odds ratio <1) and f (p < 0.001; odds ratio <1) were associated with T-stage. The Mann-Whitney U tests with Bonferroni correction showed that D, f and ADC could discriminate oesophageal SCC, especially T₁-staged tumour, from normal oesophagus (all p < 0.05) while D* could not (p > 0.05). By receiver operating characteristic analyses, f could be the best indicator for detecting oesophageal SCC with an area under receiver operating characteristic (AUC) of 0.964, especially T₁-staged cancer with an AUC of 0.984, and for discriminating T₁-stages between T_0-1 and T_2-3 with an AUC of 0.957, and between T_0-2 and T₃ with an AUC of 0.945 in comparison with any other DWI-derived parameter.

CONCLUSIONS

IVIM derived parameters can be associated with T-stage of oesophageal SCC. Advances in knowledge (1) IVIM-derived parameters are negatively correlated with stage of oesophageal SCC. (2) Among IVIM-derived parameters, microvascular volume fraction helps detect and stage oesophageal SCC.

Measuring the apparent diffusion coefficient in primary rectal tumors: is there a benefit in performing histogram analyses?

Purpose

The apparent diffusion coefficient (ADC) is a potential prognostic imaging marker in rectal cancer. Typically, mean ADC values are used, derived from precise manual whole-volume tumor delineations by experts. The aim was first to explore whether non-precise circular delineation combined with histogram analysis can be a less cumbersome alternative to acquire similar ADC measurements and second to explore whether histogram analyses provide additional prognostic information.

Methods

Thirty-seven patients who underwent a primary staging MRI including diffusion-weighted imaging (DWI; b0, 25, 50, 100, 500, 1000; 1.5 T) were included. Volumes-of-interest (VOIs) were drawn on b1000-DWI: (a) precise delineation, manually tracing tumor boundaries (2 expert readers), and (b) non-precise delineation, drawing circular VOIs with a wide margin around the tumor (2 non-experts). Mean ADC and histogram metrics (mean, min, max, median, SD, skewness, kurtosis, 5th–95th percentiles) were derived from the VOIs and delineation time was recorded. Measurements were compared between the two methods and correlated with prognostic outcome parameters.

Results

Median delineation time reduced from 47–165 s (precise) to 21–43 s (non-precise). The 45th percentile of the non-precise delineation showed the best correlation with the mean ADC from the precise delineation as the reference standard (ICC 0.71–0.75). None of the mean ADC or histogram parameters showed significant prognostic value; only the total tumor volume (VOI) was significantly larger in patients with positive clinical N stage and mesorectal fascia involvement.

Conclusion

When performing non-precise tumor delineation, histogram analysis (in specific 45th ADC percentile) may be used as an alternative to obtain similar ADC values as with precise whole tumor delineation. Histogram analyses are not beneficial to obtain additional prognostic information.

Approaches and genetic determinants in predicting response to neoadjuvant chemotherapy in locally advanced gastric cancer

Gastric cancer remains a major health burden worldwide. There is near-universal agreement that neoadjuvant chemotherapy (NAC) is a preferred management for locally advanced gastric cancer (LAGC). However, the optimal approach for an individual patient is still not clear and remains controversial, which could be at least partly explained by the lack of predictive tools. The ability to predict chemosensitivity from NAC in routine clinical practice is difficult and is an area of intense investigation, especially in the Precision-Medicine Era. Available consistent evidence suggests that a favorable tumor histopathological response to NAC may be a useful positive prognostic marker in gastric cancer. Hence, it is reasonable to speculate that making the histopathological response from NAC predictable will dramatically facility the NAC and improve patients' outcome. This review provides an overview on the current status of predictive biomarkers for histopathological response from NAC in LAGC, including clinicopathological variables, imaging and molecular testing. Furthermore, limitations and future perspectives are also discussed.

A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI

BACKGROUND

Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear.

METHODS

Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models.

RESULTS

All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred.

CONCLUSION

Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work.

Quantitative Assessment of Rectal Cancer Response to Neoadjuvant Combined Chemotherapy and Radiation Therapy: Comparison of Three Methods of Positioning Region of Interest for ADC Measurements at Diffusion-weighted MR Imaging

Purpose To determine the impact of three different methods of region of interest (ROI) positioning for apparent diffusion coefficient (ADC) measurements on the assessment of complete response (CR) to neoadjuvant combined chemotherapy and radiation therapy (CRT) in patients with rectal cancer. Materials and Methods Institutional review board approval was obtained for this study; all patients gave written informed consent. ADCs were measured by two radiologists using three circular ROIs (three-ROIs), single-section (SS), and whole-tumor volume (WTV) methods in 62 patients with locally advanced rectal cancer on pre- and post-CRT images. Interobserver variability was analyzed by calculating intraclass correlation coefficient (ICC). Descriptive statistics and areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate performance in determining CR from pre- and post-CRT ADCs and ADC change. Histopathologic tumor regression grade was the reference standard. Results SS and WTV methods yielded higher AUCs than did the three-ROIs method when determining CR from post-CRT ADC (0.874 [95% confidence interval {CI}: 0.778, 0.970] and 0.886 [95% CI: 0.781, 0.990] vs 0.731 [95% CI: 0.583, 0.878], respectively; P = .033 and P = .003) and numeric change (0.892 [95% CI: 0.812, 0.972] and 0.897 [95% CI: 0.801, 0.994] vs 0.740 [95% CI: 0.591, 0.890], respectively; P = .048 and P = .0021). Respective accuracies of SS, WTV, and three-ROIs methods were 79% (49 of 62), 77% (48 of 62), and 61% (38 of 62) for post-CRT, 79% (49 of 62), 86% (53 of 62), and 60% (37 of 62) for numeric ADC change, and 77% (48 of 62), 84% (52 of 62), and 57% (35 of 62) for percentage ADC change (ADC cut-offs: 1.21, 1.30, and 1.05 × 10^-3 mm²/sec, 0.33, 0.45, and 0.27 × 10^-3 mm²/sec increases, and 40%, 54%, and 27% increases, respectively). Post-CRT and ADC change measurements achieved negative predictive values of 96% (44 of 46) to 100% (39 of 39). Intraobserver agreement was highest for WTV-derived ADCs (ICC, 0.742 [95% CI: 0.316, 0.892] to 0.891 [95% CI: 0.615, 0.956]) and higher for all pretreatment than posttreatment measurements (ICC, 0.761 [95% CI: 0.209, 0.930] and 0.648 [95% CI: 0.164, 0.895] for three-ROIs method, 0.608 [95% CI: 0.287, 0.844] and 0.582 [95% CI: 0.176, 0.870] for SS method, 0.891 [95% CI: 0.615, 0.956] and 0.742 for WTV method [95% CI: 0.316, 0.892]). Conclusion Tumor ADCs are highly dependent on the ROI positioning method used. Larger area measurements yield greater accuracy in response assessment. Post-CRT ADCs and values of ADC changes accurately identify noncomplete responders. WTV measurement of percentage ADC change provides the best results. ^© RSNA, 2016 An earlier incorrect version of this article appeared online. This article was corrected on September 19, 2016.

Monitoring of the tumor response to nano-graphene oxide-mediated photothermal/photodynamic therapy by diffusion-weighted and BOLD MRI

Photothermal therapy (PTT) and photodynamic therapy (PDT) are promising cancer treatment modalities. Because each modality has its own set of advantages and limitations, there has been interest in developing methods that can co-deliver the two regimens for enhanced tumor treatment. Among the efforts, nano-graphene oxide-mediated phototherapies have recently attracted much attention. Nano-graphene oxide has a broad absorbance spectrum and can be loaded with photosensitizers, such as chlorin e6, with high efficiency. Chlorin e6-loaded and PEGylated nano-graphene (GO-PEG-Ce6) can be excited at 660 nm, 808 nm, or both, to induce PDT, PTT, or PDT/PTT combination. Despite the potential of the treatments, there is a lack of a diagnostic tool which can monitor their therapeutic response in a non-invasive and prognostic manner; such an ability is urgently needed for the transformation and translation of the technologies. In this study, we performed diffusion-weighted and blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) after GO-PEG-Ce6-mediated PTT, PDT, or PTT/PDT. We found that after efficient PTT, there is a significant increase of the tumor apparent diffusion coefficient (ADC) value in diffusion-weighted imaging (DWI) maps; meanwhile, an efficient PDT led to an increase of in BOLD images. In both the cases, the amplitude of the increase was correlated with the treatment outcomes. More interestingly, a synergistic treatment efficacy was observed when the PTT/PDT combination was applied, and the combination was associated with a greater ADC and increase than when either modality was used alone. In particular, the PTT/PDT condition that induced the most dramatic short-term increase of the ADC value (>70%) caused the most effective tumor control in the long-run, with 60% of the treated animals being tumor-free after 60 days. These results suggest the great promise of the combination of DWI and BOLD MRI as a tool for accurate monitoring and prognosis of phototherapies, which is of great value to the future developments of the methodologies.

Automated prostate cancer detection using T2-weighted and high-b-value diffusion-weighted magnetic resonance imaging

PURPOSE

The authors propose a computer-aided diagnosis (CAD) system for prostate cancer to aid in improving the accuracy, reproducibility, and standardization of multiparametric magnetic resonance imaging (MRI).

METHODS

The proposed system utilizes two MRI sequences [T2-weighted MRI and high-b-value (b = 2000 s/mm(2)) diffusion-weighted imaging (DWI)] and texture features based on local binary patterns. A three-stage feature selection method is employed to provide the most discriminative features. The authors included a total of 244 patients. Training the CAD system on 108 patients (78 MR-positive prostate cancers and 105 benign MR-positive lesions), two validation studies were retrospectively performed on 136 patients (68 MR-positive prostate cancers, 111 benign MR-positive lesions, and 117 MR-negative benign lesions).

RESULTS

In distinguishing cancer from MR-positive benign lesions, an area under receiver operating characteristic curve (AUC) of 0.83 [95% confidence interval (CI): 0.76-0.89] was achieved. For cancer vs MR-positive or MR-negative benign lesions, the authors obtained an AUC of 0.89 AUC (95% CI: 0.84-0.93). The performance of the CAD system was not dependent on the specific regions of the prostate, e.g., a peripheral zone or transition zone. Moreover, the CAD system outperformed other combinations of MRI sequences: T2W MRI, high-b-value DWI, and the standard apparent diffusion coefficient (ADC) map of DWI.

CONCLUSIONS

The novel CAD system is able to detect the discriminative texture features for cancer detection and localization and is a promising tool for improving the quality and efficiency of prostate cancer diagnosis.

Apparent diffusion coefficient measurement covering complete tumor area better predicts rectal cancer response to neoadjuvant chemoradiotherapy

Aim

To determine the impact of two apparent diffusion coefficient (ADC) measurement techniques on diffusion-weighted magnetic resonance images (DW MRI) on the assessment of rectal cancer response to neoadjuvant chemoradiotherapy (CRT).

Methods

ADC values were measured prospectively with two different techniques – the first, which measures ADCs in the most cellular tumor parts, and the second, which measures the entire tumor area, in 58 patients with locally advanced rectal cancer on pre-CRT and post-CRT image sets. Areas under the receiver operating characteristic curves (AUCs) and parameters of diagnostic accuracy were calculated for pre- and post-CRT ADC values and numeric and percent ADC change for each technique to determine their performance in tumor response evaluation using histopathological tumor-regression grade as the reference standard.

Results

The second technique yielded higher AUCs (0.935 vs 0.704, P < 0.001), percent-change (0.828 vs 0.636, P < 0.001), and numeric-change (0.866 vs 0.653, P < 0.001) than the first technique for post-CRT ADC. Accuracies for post-CRT ADC assessment were 62% for the first and 88% for the second technique (cut-off values: 0.98 and 1.29 × 10⁻³ mm²/s, respectively) and for ADC change assessment, both numeric and percent, 59% and 74%, respectively (cut-off values: increase of 0.18 and 0.28 × 10⁻³ mm²/s; increase of 24% and 37%, respectively).

Conclusions

The type of measurement technique significantly affected ADC results. ADC measurements covering a larger area better predicted tumor response to therapy. Post-CRT ADCs, regardless of the measurement technique, and numeric ADC change measured in the whole tumor volume accurately identified non-complete responders. Post-CRT ADCs measured in the entire tumor area yielded the highest accuracy level in tumor response evaluation.

Multiparametric MR imaging of tumor response to intraarterial chemotherapy in orthotopic xenograft models of human metastatic brain tumor

The purpose of our study was to investigate the therapeutic efficacy of intraarterial (IA) chemotherapy via multiparametric magnetic resonance imaging (MRI) analysis in orthotopic mouse brain tumor models. Stereotactic-guided intracranial inoculation of MDA-MB-231 cells was performed in nude mice. Thirty tumor bearing mice were randomized into three groups, and each group received either IA docetaxel administration (n = 10), intravenous (IV) docetaxel administration (n = 10), or IA solvent injection (n = 10) as control. Treatment response was monitored by diffusion-weighted imaging and dynamic contrast enhanced-MRI obtained 1 day before and 8 days after therapy initiation. Imaging results were correlated with histopathology. In the results, IA chemotherapy showed a significant decrease in tumor volume (86.5 ± 15.6 %) compared to the IV chemotherapy (121.1 ± 39.6%) and control (126.2 ± 22.0%) 8 days after therapy (p < 0.05). Furthermore, IA chemotherapy resulted in a significant increase in mean tumor apparent diffusion coefficient (ADC) values (116.8 ± 44.9%); in contrary IV chemotherapy (66.6 ± 26.9%) and control (69.1 ± 29.5%) showed a significant decrease in ADC values corresponding to further tumor growth (p < 0.05). However, there was no significant difference in perfusion parameters including initial area under the curve, K(trans), K(ep), and V(e) between the groups (p > 0.05). Histopathology confirmed necrosis and necroptosis in the tumors after IA chemotherapy. In conclusion, IA chemotherapy may lead to effective inhibition of tumor cell proliferation and offer potential benefit of inducing higher degree of treatment response than IV chemotherapy.

Increased tumour ADC value during chemotherapy predicts improved survival in unresectable pancreatic cancer

OBJECTIVES

To investigate whether changes to the apparent diffusion coefficient (ADC) of primary tumour in the early period after starting chemotherapy can predict progression-free survival (PFS) or overall survival (OS) in patients with unresectable pancreatic adenocarcinoma.

METHODS

Subjects comprised 43 patients with histologically confirmed unresectable pancreatic cancer treated with first-line chemotherapy. Minimum ADC values in primary tumour were measured using the selected area ADC (sADC), which excluded cystic and necrotic areas and vessels, and the whole tumour ADC (wADC), which included whole tumour components. Relative changes in ADC were calculated from baseline to 4 weeks after initiation of chemotherapy. Relationships between ADC and both PFS and OS were modelled by Cox proportional hazards regression.

RESULTS

Median PFS and OS were 6.1 and 11.0 months, respectively. In multivariate analysis, sADC change was the strongest predictor of PFS (hazard ratio (HR), 4.5; 95 % confidence interval (CI), 1.7-11.9; p = 0.002). Multivariate Cox regression analysis for OS revealed sADC change and CRP as independent predictive markers, with sADC change as the strongest predictive biomarker (HR, 6.7; 95 % CI, 2.7-16.6; p = 0.001).

CONCLUSION

Relative changes in sADC could provide a useful imaging biomarker to predict PFS and OS with chemotherapy for unresectable pancreatic adenocarcinoma.

KEY POINTS

• Relative change in ADC value can predict survival in unresectable pancreatic cancer. • ADC change could determine a chemosensitivity of pancreatic cancer. • ADC values should be measured by excluding cystic, necrotic areas and vessels.

Role of the Apparent Diffusion Coefficient in the Prediction of Response to Neoadjuvant Chemotherapy in Patients With Locally Advanced Breast Cancer

BACKGROUND

We evaluated the diagnostic performance of the baseline diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in the prediction of a complete pathologic response (pCR) to neoadjuvant chemotherapy (NAC) in patients with breast cancer stratified according to the tumor phenotype.

PATIENTS AND METHODS

We retrospectively studied 225 patients with stage II, III, and IV breast cancer who had undergone contrast-enhanced magnetic resonance imaging (MRI) and DWI before and after NAC, followed by breast surgery.

RESULTS

The tumor phenotypes were luminal (n = 143; 63.6%), triple-negative (TN) (n = 37; 16.4%), human epidermal growth factor receptor 2 (HER2)-enriched (n = 17; 7.6%), and hybrid (hormone receptor-positive/HER2(+); n = 28; 12.4%). After NAC, a pCR was observed in 39 patients (17.3%). No statistically significant difference was observed in the mean ADC value between a pCR and no pCR in the general population (1.132 ± 0.191 × 10(-3) mm(2)/s vs. 1.092 ± 0.189 × 10(-3) mm(2)/s, respectively; P = .23). The optimal ADC cutoff value in the general population was 0.975 × 10(-3) mm(2)/s (receiver operating characteristic [ROC] area under the curve [AUC], 0.587 for the prediction of a pCR). After splitting the population into subgroups according to tumor phenotype, we observed a significant or nearly significant difference in the mean ADC value among the responders versus the nonresponders in the TN (P = .06) and HER2(+) subgroups (P = .05). No meaningful difference was seen in the luminal and hybrid subgroups (P = .59 and P = .53, respectively). In contrast, in the TN and HER2(+) subgroups (cutoff value, 0.995 × 10(-3) mm(2)/s and 0.971 × 10(-3) mm(2)/s, respectively), we observed adequate ROC AUCs (0.766 and 0.813, respectively).

CONCLUSION

The pretreatment ADC value is not capable of predicting the pCR in the overall population of patients with locally advanced breast cancer. Nonetheless, an ameliorated diagnostic performance was observed in specific phenotype subgroups (ie, TN and HER2(+) tumors).

Intra- and interobserver variability of whole-tumour apparent diffusion coefficient measurements in nephroblastoma: a pilot study

BACKGROUND

The apparent diffusion coefficient (ADC) is potentially useful for assessing treatment response in nephroblastoma (Wilms tumour). However the precision of ADC measurements in these heterogeneous lesions is unknown.

OBJECTIVE

To assess intra- and interobserver variability of whole-tumour ADC measurements in viable parts of nephroblastomas at diagnosis and after preoperative chemotherapy.

MATERIALS AND METHODS

We included children with histopathologically proven nephroblastoma who had undergone MRI with diffusion-weighted imaging before and after preoperative chemotherapy. Three independent observers performed whole-tumour ADC measurements of all lesions, excluding non-enhancing areas. One observer evaluated all lesions on two occasions. We performed analyses using Bland-Altman plots and concordance correlation coefficient (CCC) calculations with 95% limits of agreement for median ADC, difference between pre- and post-chemotherapy median ADC (ADC shift) and percentage of pixels with ADC values <1.0 × 10(-3) mm(2)/s.

RESULTS

In 22 lesions (13 pretreatment and 9 post-treatment) in 10 children the interobserver variability in median ADC and ADC shift were within the interval of approximately ±0.1 × 10(-3) mm(2)/s (limits of agreement for median ADC ranged -0.08-0.11 × 10(-3) mm(2)/s and for ADC-shift -0.11-0.09 × 10(-3) mm(2)/s). The interobserver variability for percentage of low-ADC pixels was larger and also biased. The calculated CCC confirmed good intra- and interobserver agreement (ρ-c ranging from 0.968 to 0.996).

CONCLUSION

Measurements of whole-tumour ADC values excluding necrotic areas seem to be sufficiently precise for detection of chemotherapy-related change.

Meta-analysis of quantitative diffusion-weighted MR imaging in differentiating benign and malignant pancreatic masses

There have been numerous studies done to explore the diagnostic performance of quantitative diffusion-weighted (DW) MR imaging to differentiate between benign and malignant pancreatic masses. However, the results have been inconsistent. We performed a meta-analysis to investigate whether DW-MR imaging can differentiate between these two diseases. Databases including MEDLINE, EMBASE and Cochrane Library were utilized to find relevant articles published between January 2001 and January 2014. A Stata version 12.0 and a Meta-Disc version 1.4 were used to describe primary results. Twelve studies with 594 patients, which fulfilled the inclusion criteria, were enrolled for the analysis. The pooled sensitivity and specificity of DW imaging was 0.91 (95% CI: 0.84, 0.95) and 0.86 (95% CI: 0.76, 0.93) respectively. The area under the curve of the summary receiver operating characteristic was 0.95 (95% CI: 0.93, 0.96). The results indicated that DW imaging might be a valuable tool for differentiating benign and malignant pancreatic masses.

Effectiveness of MRI for the assessment of mesorectal fascia involvement in patients with rectal cancer: a systematic review and meta-analysis

AIMS

Defining the most appropriate definition of mesorectal fascia involvement (MRF+) by reviewing literature and using new inclusion criteria to re-evaluate the effectiveness of MRI in the assessment of MRF+ for rectal cancer.

METHODS

PubMed, Medline, Embase, and the Cochrane Library databases were electronically searched from 1999 to 2012. The bivariate random effects model was used to estimate the pooled outcomes of each subgroup. The definition of MRF+ in MRI and the influence of neoadjuvant chemoradiotherapy (neo-ChRT) were especially discussed.

RESULTS

Fourteen studies involving 1,600 patients were included. Different definitions of MRF+ (≤ 1, ≤ 2 and ≤ 5 mm) in MRI exhibited different pooled sensitivity (76, 79 and 92%), specificity (88, 66 and 48%) and diagnostic odds ratio (DOR) (22.4, 6.6 and 16.0). The definition of MRF+ at ≤ 1 mm showed the highest DOR. The specificity (88 vs. 93%, p = 0.026) and DOR (15.5 vs. 39.0, p = 0.001) were lower in patients who underwent neo-ChRT than those who did not while using ≤ 1 mm as the definition of MRF+. However, the sensitivity showed no significant difference (67 vs. 74%, p = 0.129).

CONCLUSIONS

MRI is valuable for the assessment of MRF. The most appropriate definition of MRF+ in MRI is ≤ 1 mm. The effectiveness is higher in patients who did not undergo neo-ChRT.

Assessment of aggressiveness of rectal cancer using 3-T MRI: correlation between the apparent diffusion coefficient as a potential imaging biomarker and histologic prognostic factors

BACKGROUND

Diffusion-weighted magnetic resonance imaging (DW-MRI) permits non-invasive assessment of tumor characteristics.

PURPOSE

To assess the value of DW-MRI as a potential non-invasive marker of tumor aggressiveness in rectal cancer by analyzing the relationship between tumoral apparent diffusion coefficient (ADC) values of MRI and histopathologic prognostic parameters that are not affected by preoperative chemoradiation therapy.

MATERIAL AND METHODS

Forty patients with rectal cancer were assessed with primary staging 3-T MRI, including DWI, before undergoing surgical therapy. In all patients, surgery was performed without neoadjuvant therapy. Mean tumor ADC was measured and compared between subgroups based on pretreatment carcinoembryonic antigen (CEA) levels, MRI parameters (e.g. postoperative local recurrence), and histopathologic parameters, including A (invasive distance: A1, T-stage; A2, mesorectal fascia [MRF] status), B (differentiation grade: B1, poorly differentiated; B2, moderately differentiated; B3, well differentiated), C (others: C1, N-stage; C2, lymphangiovascular invasion).

RESULTS

Mean tumor ADCs were different when comparing groups stratified by histologic differentiation grades (P=0.0192). There was no significant difference in mean ADCs when stratifying patients according to CEA levels, T-stage, N-stage, MRF status, presence of lymphangiovascular invasion, or the presence of local recurrence.

CONCLUSION

Significant correlations were found between mean ADC values and differentiation grade. ADC may be useful as an imaging biomarker of tumor aggressiveness, but it cannot serve as an independent biomarker of advanced rectal cancer.

DW-MRI in assessment of the hypoxic fraction, interstitial fluid pressure, and metastatic propensity of melanoma xenografts

Background

Cancer patients with primary tumors showing extensive hypoxia and highly elevated interstitial fluid pressure (IFP) have poor prognosis. The potential of diffusion-weighted magnetic resonance imaging (DW-MRI) in assessing the hypoxic fraction, IFP, and metastatic propensity of tumors was investigated in this study.

Methods

A-07 and R-18 melanoma xenografts were used as general models of human cancer. DW-MRI was performed at 1.5 T, and maps of the apparent diffusion coefficient (ADC) were produced with in-house-made software developed in Matlab. Pimonidazole was used as a hypoxia marker. Tumor cell density and hypoxic fraction were assessed by quantitative analysis of histological sections. IFP was measured with a Millar catheter. Metastatic propensity was determined by examining tumor-bearing mice for pulmonary micrometastases post mortem.

Results

ADC decreased with increasing tumor cell density, independent of whether the A-07 and R-18 data were analyzed separately or together. In the A-07 line, ADC decreased with increasing hypoxic fraction and increasing IFP and was lower in metastatic than in nonmetastatic tumors, and in the R-18 line, ADC decreased with increasing hypoxic fraction. There was a strong inverse correlation between ADC and hypoxic fraction as well as between ADC and IFP across the two tumor lines, primarily because low ADC as well as high hypoxic fraction and high IFP were associated with high cell density.

Conclusion

Low ADC is a potentially useful biomarker of poor prognosis in cancer, since low ADC is mainly a consequence of high cell density, and high cell density may lead to increased hypoxia and interstitial hypertension and, therefore, increased microenvironment-associated metastasis.

High-field small animal magnetic resonance oncology studies

This review focuses on the applications of high magnetic field magnetic resonance imaging (MRI) and spectroscopy (MRS) to cancer studies in small animals. High-field MRI can provide information about tumor physiology, the microenvironment, metabolism, vascularity and cellularity. Such studies are invaluable for understanding tumor growth and proliferation, response to treatment and drug development. The MR techniques reviewed here include (1)H, (31)P, chemical exchange saturation transfer imaging and hyperpolarized (13)C MRS as well as diffusion-weighted, blood oxygen level dependent contrast imaging and dynamic contrast-enhanced MRI. These methods have been proven effective in animal studies and are highly relevant to human clinical studies.

Extramural depth of tumor invasion at thin-section MR in rectal cancer: associating with prognostic factors and ADC value

PURPOSE

To assess the value of maximal extramural depth (EMD) of T3 tumor spread on MRI as a potential noninvasive imaging biomarker of tumor aggressiveness in rectal cancer, by analyzing the relationship between tumoral EMD values and clinical or histological prognostic parameters. In addition, we try to investigate the relationship between EMD and apparent diffusion coefficient (ADC) values.

MATERIALS AND METHODS

Ninety rectal cancer patients who underwent primary MRI staging and diffusion weighted imaging (DWI) as T3 tumor were included. Tumor EMD was measured, and the EMD values of the subgroups based on pretreatment CEA, CA19-9 levels, N stage, and histological parameters were compared. The correlation between EMD and ADC values was compared.

RESULTS

Interobserver agreement of confidence levels for observers 1 and 2 was good for cN stage (k = 0.678) and EMD measurement(k = 0.612) and was excellent for ADC measurement (k = 0.880). Tumor EMDs differ between CEA <5 ng/mL versus ≥ 5 ng/mL (P = 0.013), CA19-9 < 27 U/mL versus ≥ 27 U/mL (P = 0.012), the groups of cN0 versus cN+ cancers (P = 0.049), and between the several groups of histological differentiation grades (P = 0.033). There was no significant difference in EMDs between the various groups of vessel carcinoma embolus and neural invasion. A significant negative correlation (r = -0.581; P = 0.001) between ADC and EMD values was found.

CONCLUSION

Significant correlations were found between EMD values and CEA, CA19-9 level, differentiation grade and ADC value. As been found, higher EMD values were associated with a more aggressive tumor profile and, therefore, EMD has the potential to become an imaging biomarker of tumor aggressiveness indicator.

Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging

PURPOSE

To explore the role of histogram analysis of apparent diffusion coefficient (ADC) maps obtained at standard- and high-b-value (1000 and 3000 sec/mm(2), respectively) diffusion-weighted (DW) imaging in the differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board of Seoul National University Hospital, and informed consent requirement was waived. Thirty patients with histopathologically proved glioblastoma who had undergone concurrent chemotherapy and radiation therapy (CCRT) with temozolomide underwent diffusion-weighted MR imaging with b values of 1000 and 3000 sec/mm(2), and corresponding ADC maps were calculated from entire newly developed or enlarged enhancing lesions after completion of CCRT. Histogram parameters of each ADC map between true progression (n = 15) and pseudoprogression (n = 15) groups were compared by using the unpaired Student t test. Receiver operating characteristic analysis was used to determine the best cutoff values for predictors in the differentiation of true progression from pseudoprogression. Results were validated in an independent test set of nine patients by using the best cutoff value to predict differentiation of true progression from pseudoprogression. The accuracy of the selected best cutoff value in the independent test set was then calculated.

RESULTS

In terms of cumulative histograms, the fifth percentile of both ADC at b value of 1000 sec/mm(2) (ADC1000) and the ADC at b value of 3000 sec/mm(2) (ADC3000) were significantly lower in the true progression group than in the pseudoprogression group (P = .049 and P < .001, respectively). In contrast, neither the mean ADC1000 nor the mean ADC3000 was significantly different between the two groups. The diagnostic values of the parameters derived from ADC1000 and ADC3000 were compared, and a significant difference (0.224, P = .016) was found between the area under the receiver operating characteristic curve of the fifth percentile for ADC1000 and that for ADC3000. The accuracies were 66.7% (six of nine patients) and 88.9% (eight of nine patients) based on the fifth percentile of both ADC1000 and ADC3000 in the independent test set, respectively.

CONCLUSION

The fifth percentile of the cumulative ADC histogram obtained at a high b value was the most promising parameter in the differentiation of true progression from pseudoprogression of the newly developed or enlarged enhancing lesions after CCRT with temozolomide for glioblastoma treatment. Online supplemental material is available for this article.

Fractional change in apparent diffusion coefficient as an imaging biomarker for predicting treatment response in head and neck cancer treated with chemoradiotherapy

BACKGROUND AND PURPOSE

ADC provides a measure of water molecule diffusion in tissue. The aim of this study was to evaluate whether the fractional change in ADC during therapy can be used as a valid predictive indicator of treatment response in head and neck squamous cell carcinoma treated with chemoradiotherapy.

MATERIALS AND METHODS

Forty patients underwent DWI at pretreatment and 3 weeks after the start of treatment. The pretreatment ADC, fractional change in ADC, tumor regression rate, and other clinical variables were compared with locoregional control and locoregional failure and were analyzed by using logistic regression analysis and receiver operating characteristic analysis. Furthermore, progression-free survival curves divided by the corresponding threshold value were compared by means of the log-rank test.

RESULTS

The fractional change in ADCprimary, the fractional change in ADCnode, primary tumor volume, nodal volume, tumor regression ratenode, N stage, and tumor location revealed significant differences between locoregional failure and locoregional control (P < .05). In univariate analysis, the fractional change in ADCprimary, fractional change in ADCnode, tumor regression ratenode, N stage, and tumor location showed significant association with locoregional control (P < .05). In multivariate analysis, however, only the fractional change in ADCprimary was identified as a significant and independent predictor of locoregional control (P = .04). A threshold fractional change in ADCprimary of 0.24 revealed a sensitivity of 100%, specificity of 78.7%, and overall accuracy of 84.8% for the prediction of locoregional control. Progression-free survival of the 2 groups divided by the fractional change in ADCprimary at 0.24 showed a significant difference (P < .05).

CONCLUSIONS

The results suggest that the fractional change in ADCprimary is a valid imaging biomarker for predicting treatment response in head and neck squamous cell carcinoma treated with chemoradiotherapy.

Nasopharyngeal carcinoma: comparison of diffusion and perfusion characteristics between different tumour stages using intravoxel incoherent motion MR imaging

OBJECTIVE

To explore intravoxel incoherent motion (IVIM) characteristics of nasopharyngeal carcinoma (NPC) and relationships with different tumour stages.

METHODS

We prospectively recruited 80 patients with newly diagnosed undifferentiated NPC. Diffusion-weighted MR imaging was performed and IVIM parameters (D, pure diffusion; f, perfusion fraction; D*, pseudodiffusion coefficient) were calculated. Patients were stratified into low and high tumour stage groups based on American Joint Committee on Cancer (AJCC) and TNM staging for determination of the predictive powers of IVIM parameters using t test, multiple logistic regression and ROC curve analyses.

RESULTS

D, f and D* were all statistically significantly lower in high-stage groups in AJCC, T and N staging. D, f and D* were all independent predictors of AJCC staging, f and D* were independent predictors of T staging, and D was an independent predictor of N staging. D was most powerful for AJCC and N staging, whereas f was most powerful for T staging. Optimal cut-off values (area under the curve, sensitivity, specificity, positive likelihood ratio, negative likelihood ratio) were as follows: AJCC stage, D = 0.782 × 10(-3) mm(2)/s (0.915, 93.3 %, 76.2 %, 3.92, 0.09); T staging, f = 0.133 (0.905, 80.5 %, 92.5 %, 10.73, 0.21); N staging, D = 0.761 × 10(-3) mm(2)/s (0.848, 87.5 %, 66.7 %, 2.62, 0.19). Multivariate analysis showed no diagnostic improvement.

CONCLUSION

Nasopharyngeal carcinoma has distinctive intravoxel incoherent motion characteristics parameters in different tumour staging, potentially helping pretreatment staging.

KEY POINTS

• Magnetic resonance imaging is increasingly used to assess nasopharyngeal carcinoma (NPC). • NPC has distinctive diffusion/perfusion characteristics at different stages. • Non-invasive MR imaging may help pretreatment staging prediction. • Diffusion properties of NPC best correlate with AJCC and N staging. • Perfusion properties of NPC best correlate with T staging.

Diffusion-weighted magnetic resonance for prediction of response after neoadjuvant chemoradiation therapy for locally advanced rectal cancer: preliminary results of a monoinstitutional prospective study

PURPOSE

To evaluate diffusion-weighted imaging (DWI) for assessment of treatment response in locally advanced rectal cancer (LARC) 8 weeks after neoadjuvant chemoradiotherapy (CRT).

METHODS AND MATERIALS

A total of 28 patients with LARC underwent magnetic resonance imaging (MRI) prior to and 8 weeks after CRT. Tumor volume (TV) was calculated on T2-weighted MRI scans as well as the apparent diffusion coefficient (ADC) was calculated using Echo-planar DWI-sequences. All data were correlated to surgical results and histopathologic tumor regression grade (TRG), according to Mandard's classification. Post-treatment difference ADC (%ΔADC) and TV (%ΔTV) changes at 8 weeks were compared complete response (CR; TRG1) and non-complete response tumors (non-CR; TRG2-5).

RESULTS

The mean % ADC increase of CR group was significantly higher compared to non-CR group (77.2 ± 54.63% vs. 36.0 ± 29.44%; p = 0.05). Conversely, the mean % TV reduction did not significantly differ in CR group from non-CR group (73.7% vs. 63.77%; p = 0.21). Accordingly, the diagnostic accuracy of the mean % ADC increase to discriminate CR from non-CR group was significantly higher than that of the mean % TV reduction (0.913 vs. 0.658; p = 0.022). No correlation was found between mean % TV reduction and TRG (rho = 0.22; p = 0.3037), whereas a negative correlation between mean % ADC increase and TRG was recorded (r = -0.69; p = 0.006).

CONCLUSION

The mean % ADC increase appears to be a reliable tool to differentiate CR from non-CR after CRT in patients with LARC.

Correlation of apparent diffusion coefficient measured by diffusion-weighted MRI and clinicopathologic features in pancreatic cancer patients

BACKGROUND/PURPOSE

The aim of this study was to evaluate the clinical usefulness of diffusion-weighted magnetic resonance imaging (DWI) in patients with pancreatic cancer by comparing the apparent diffusion coefficient (ADC) value with clinicopathologic features.

METHODS

Twenty-two consecutive patients (12 men, 10 women; mean age 64.4 years) with pancreatic cancer underwent DWI before surgery. We retrospectively investigated the correlations between tumor ADC value and clinicopathologic features.

RESULTS

Apparent diffusion coefficient value was significantly lower for pancreatic cancer than for noncancerous tissue (P < 0.001). Receiver operating characteristic analysis yielded an optimal ADC cutoff value of 1.21 × 10(-3) mm(2)/s to distinguish pancreatic cancer from noncancerous tissue. There was a significant negative correlation between ADC value and tumor size (r = -0.59, P = 0.004) and between ADC value and number of metastatic lymph nodes (r = -0.56, P = 0.007). Tumors with low ADC value had a significant tendency to show high portal venous system invasion (P = 0.02) and extrapancreatic nerve plexus invasion (P = 0.01).

CONCLUSIONS

Apparent diffusion coefficient value appears to be a promising parameter for detecting pancreatic cancer and evaluating the degree of malignancy of pancreatic cancer.

Ewing sarcoma dissemination and response to T-cell therapy in mice assessed by whole-body magnetic resonance imaging

BACKGROUND

Novel treatment strategies in Ewing sarcoma include targeted cellular therapies. Preclinical in vivo models are needed that reflect their activity against systemic (micro)metastatic disease.

METHODS

Whole-body magnetic resonance imaging (WB-MRI) was used to monitor the engraftment and dissemination of human Ewing sarcoma xenografts in mice. In this model, we evaluated the therapeutic efficacy of T cells redirected against the Ewing sarcoma-associated antigen GD2 by chimeric receptor engineering.

RESULTS

Of 18 mice receiving intravenous injections of VH-64 Ewing sarcoma cells, all developed disseminated tumour growth detectable by WB-MRI. All mice had lung tumours, and the majority had additional manifestations in the bone, soft tissues, and/or kidney. Sequential scans revealed in vivo growth of tumours. Diffusion-weighted whole-body imaging with background signal suppression effectively visualised Ewing sarcoma growth in extrapulmonary sites. Animals receiving GD2-targeted T-cell therapy had lower numbers of pulmonary tumours than controls, and the median volume of soft tissue tumours at first detection was lower, with a tumour growth delay over time.

CONCLUSION

Magnetic resonance imaging reliably visualises disseminated Ewing sarcoma growth in mice. GD2-retargeted T cells can noticeably delay tumour growth and reduce pulmonary Ewing sarcoma manifestations in this aggressive disease model.

Differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma: application of high b-value diffusion-weighted imaging

BACKGROUND AND PURPOSE

High b-value DWI has been expected to have an additional diagnostic role and demonstrated some promising results in head and neck cancer. The aim of this study was to evaluate the diagnostic performance of DWI at a high b-value (b=2000 s/mm(2)) compared with a standard b-value (b=1000 s/mm(2)) and the ratio of ADC values of high and standard b-values for their ability to differentiate between recurrent tumor and posttreatment changes after the treatment of head and neck squamous cell carcinoma.

MATERIALS AND METHODS

A total of 33 patients diagnosed with head and neck squamous cell carcinoma were enrolled in the present study; all had contrast-enhancing lesions on follow-up MR imaging. All patients underwent single-shot echo-planar DWI at b=1000 s/mm(2) and b=2000 s/mm(2), and corresponding ADC maps were generated (ADC1000 and ADC2000, respectively). The mean ADC1000, ADC2000, and ADCratio (ADCratio = ADC2000/ADC1000 × 100) values were evaluated within a manually placed ROI with contrast-enhanced T1-weighted images as references. For the statistical analysis, we performed a Student t test and multivariate logistic regression.

RESULTS

The mean ADC1000 in recurrent tumor was significantly lower than that in posttreatment changes (P < .001), whereas the mean ADC2000 resulted in no significant difference (P = .365). The mean ADCratio was significantly higher in recurrent tumor than that in posttreatment changes (73.5 ± 7.2% vs 56.9 ± 8.8%, respectively; P < .001). Multivariate logistic regression analysis revealed that the ADCratio was the only independently differentiating variable (P = .024). The sensitivity, specificity, and accuracy of ADCratio were 95.0%, 69.2%, and 84.8%, respectively, by use of the optimal cutoff value of 62.6%.

CONCLUSIONS

We suggest that the ADCratio calculated from the ADC1000 and ADC2000 is a promising value for the differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma.

Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density

PURPOSE

We obtained intravoxel incoherent motion (IVIM) parameters through biexponential analysis on diffusion-weighted MR imaging (DWI) using multiple b values. Correlation was evaluated between these parameters and histological microvessel density (MVD) for the possibility of noninvasive evaluation of MVD with DWI.

METHODS

Twenty-five nude mice with the HT29 colorectal cancer cells implanted were analyzed after undergoing DWI with multiple b values (0, 50, 100, 300, 500, 700, and 1000 s/mm(2)). Tissue diffusivity (D(t)), pseudo-diffusion coefficient (D(p)), and perfusion fraction (f(p)) were calculated using a biexponential analysis, and these parameters were correlated with MVD. The MVD was determined with the CD31 stain. For statistical analysis, Spearman's rank correlation was applied.

RESULTS

The mean value and correlation coefficient with MVD for each IVIM parameter were as follows: D(t)  = 0.98 ± 0.06 × 10(-3) mm(2)/s with r = 0.139 (P = 0.508); D(p) = 23.70 ± 7.94 × 10(-3) mm(2)/s with r = 0.782 (P < 0.001); and f(p) = 15.58 ± 5.7% with r = 0.749 (P < 0.001). D(p) and f(p) showed significant correlation with MVD, but D(t) did not.

CONCLUSION

The IVIM parameters, D(p) and f(p), on DWI might be used in the noninvasive evaluation of MVD.

Preclinical molecular imaging using PET and MRI

Molecular imaging fundamentally changes the way we look at cancer. Imaging paradigms are now shifting away from classical morphological measures towards the assessment of functional, metabolic, cellular, and molecular information in vivo. Interdisciplinary driven developments of imaging methodology and probe molecules utilizing animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anti-cancer treatments. Preclinical molecular imaging offers a whole palette of excellent methodology to choose from. We will focus on positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques, since they provide excellent and complementary molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values and limitations of PET and MRI as molecular imaging modalities and comment on their high potential to non-invasively assess information on hypoxia, angiogenesis, apoptosis, gene expression, metabolism, and cell trafficking in preclinical cancer research.

Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and MRS

The aim of this study was to determine whether tumor size, MRS parameters and apparent diffusion coefficient (ADC) measurements could be applied to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Ninety patients with breast cancer (median size, 4.5 cm; range, 1.6-9.5 cm) were evaluated with single-voxel ¹H MRS and dynamic contrast-enhanced MRI. Diffusion-weighted imaging was performed in 41 of these patients using a 1.5-T scanner before and after completion of NAC. Pre- and post-treatment measurements and changes in tumor size, MRS parameters [absolute and normalized total choline-containing compound (tCho) integral and tCho signal-to-noise ratio (SNR)] and ADCs in pCR versus non-pCR were compared using the nonparametric Mann-Whitney test. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of each parameter. After NAC, 30 patients (33%) showed pCR and 60 (67%) showed non-pCR. At pretreatment, ADC was the only significant parameter in differentiating between pCR and non-pCR [(0.83 ± 0.05) × 10⁻³ versus (0.97 ± 0.14) × 10⁻³ mm²/s] (p = 0.014). Post-treatment measurements after completion of NAC and changes in tumor size (both p < 0.001), MRS parameters (p = 0.027 and p = 0.020 for absolute tCho integral, p = 0.036 and p = 0.023 for normalized tCho integral, and p = 0.032 and p = 0.061 for tCho SNR) and ADC (p = 0.003 and p < 0.001) were significantly different between the pCR and non-pCR groups, except for changes in tCho SNR. In ROC analysis, the areas under the ROC curve (AUCs) of 0.63-0.73 were obtained for tumor size and MRS parameters. AUCs for pre- and post-treatment ADC and changes in ADC were 0.75, 0.80 and 0.96, respectively. The optimal cut-off of the percentage change in ADC for predicting pCR was 40.7%, yielding 100% sensitivity and 91% specificity. Patients with pCR showed significantly lower pretreatment ADCs than those with non-pCR. The change in ADC after NAC was the most accurate predictor of pCR.

Diffusion-weighted MRI in the detection of prostate cancer: meta-analysis

OBJECTIVE

The objective of our study was to estimate and compare the performance of diffusion-weighted imaging (DWI) with other MRI techniques including T2-weighted MRI for the detection of prostate cancer.

MATERIALS AND METHODS

Searches of the PubMed and Scopus electronic databases for the terms "prostate," "cancer," "diffusion-weighted imaging," and "magnetic resonance imaging" using an end date of December 2010 were completed. All included studies had histopathologic correlation; 2×2 contingency data were constructed for each study. A Bayesian receiver operating characteristic (ROC) model was used across studies to determine sensitivity, specificity, and area under the full or partial ROC curve.

RESULTS

Nineteen articles consisting of a total of 5892 lesions were analyzed. Based on a 95% credible interval, DWI alone yielded a significantly better area under the ROC curve, sensitivity, and specificity (0.85, 0.69, 0.89, respectively) than T2-weighted imaging alone (0.75, 0.60, 0.76). Combined DWI and T2-weighted imaging (0.73, 0.70, 0.83) showed a similar area under the ROC curve but significantly better sensitivity and specificity than T2-weighted imaging alone. DWI and combined DWI and T2-weighted imaging yielded similar overall sensitivity, but DWI alone showed better overall specificity than combined DWI and T2-weighted imaging. At specificities of greater than 80%, combined DWI and T2-weighted imaging yielded a partial area under the ROC curve (0.138) similar to that of DWI alone (0.129) and was significantly better than the partial area under the ROC curve of T2-weighted imaging alone (0.070). DWI alone and combined DWI and T2-weighted imaging appear to be superior to dynamic contrast-enhanced imaging alone (area under the ROC curve, 0.79; sensitivity, 0.58; specificity, 0.82).

CONCLUSION

DWI appears to improve diagnostic performance and can be a useful adjunct to conventional anatomic imaging for identifying tumor foci in prostate cancer.

The clinical value of diffusion-weighted imaging in combination with T2-weighted imaging in diagnosing prostate carcinoma: a systematic review and meta-analysis

OBJECTIVE

We aimed to explore the role of diffusion-weighted imaging (DWI) in combination with T2-weighted imaging (T2WI) in detecting prostate carcinoma through a systematic review and meta-analysis.

MATERIALS AND METHODS

The MEDLINE, EMBASE, Cancerlit, and Cochrane Library databases were searched for studies published from January 2001 to July 2011 evaluating the diagnostic performance of T2WI combined with DWI in detecting prostate carcinoma. We determined sensitivities and specificities across studies, calculated positive and negative likelihood ratios, and constructed summary receiver operating characteristic curves. We also compared the performance of T2WI combined with DWI with T2WI alone by analyzing studies that had also used these diagnostic methods on the same patients.

RESULTS

Across 10 studies (627 patients), the pooled sensitivity of T2WI combined with DWI was 0.76 (95% CI, 0.65-0.84), and the pooled specificity was 0.82 (95% CI, 0.77-0.87). Overall, the positive likelihood ratio was 4.31 (95% CI, 3.12-5.92), and the negative likelihood ratio was 0.29 (95% CI, 0.20-0.43). In seven studies in which T2WI combined with DWI and T2WI alone were performed, the sensitivity and specificity of T2WI combined with DWI were 0.72 (95% CI, 0.67-0.82) and 0.81 (95% CI, 0.76-0.86), respectively, and the sensitivity and specificity of T2WI alone were 0.62 (95% CI, 0.55-0.68) and 0.77 (95% CI, 0.71-0.82), respectively.

CONCLUSION

T2WI combined with DWI may be a valuable tool for detecting prostate cancer in the overall evaluation of prostate cancer, compared with T2WI alone. High-quality prospective studies of T2WI combined with DWI to detect prostate carcinoma still need to be conducted.

Differential diagnosis of axillary inflammatory and metastatic lymph nodes in rabbit models by using diffusion-weighted imaging: compared with conventional magnetic resonance imaging

Objective

This experiment aims to determine the diagnostic value of diffusion-weighted imaging (DWI) in the differentiation of axillary inflammatory lymph nodes from metastatic lymph nodes in rabbit models in comparison with conventional magnetic resonance imaging (MRI).

Materials and Methods

Conventional MRI and DWI were performed at 4 weeks after successful inoculation into the forty female New Zealand white rabbits' mammary glands. The size-based and signal-intensity-based criteria and the relative apparent diffusion coefficient (rADC) value were compared between the axillary inflammatory lymph nodes and metastatic lymph nodes, with histopathological findings as the reference standard. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the aforementioned criteria and rADC value in differentiating the axillary inflammatory lymph nodes from metastatic lymph nodes.

Results

Thirty-two axillary inflammatory lymph nodes and 46 metastatic ones were successfully isolated and taken into pathological analysis. The differences of the aforementioned criteria between the two groups were not statistically significant (p > 0.05). However, the rADC value of the inflammatory lymph nodes (0.9 ± 0.14) was higher than that of metastatic ones (0.7 ± 0.18), with significant difference (p = 0.016). When the rADC value was chosen as 0.80, the area under the ROC curve is greater than all other criteria, and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for differentiating two groups were 86.2%, 79.3%, 81.2%, 84.2%, and 85.6%, respectively.

Conclusion

Diffusion-weighted imaging is a promising new technique for differentiating axillary inflammatory lymph nodes from metastatic lymph nodes. Compared with routine magnetic resonance sequences, DWI could provide more useful physiological and functional information for diagnosis.