Modelling DW-MRI data from primary and metastatic ovarian tumours

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

MRI Apparent Diffusion Coefficient (ADC) as a Biomarker of Tumour Response: Imaging-Pathology Correlation in Patients with Hepatic Metastases from Colorectal Cancer (EORTC 1423)

Background: Tumour apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (MRI) is a putative pharmacodynamic/response biomarker but the relationship between drug-induced effects on the ADC and on the underlying pathology has not been adequately defined. Hypothesis: Changes in ADC during early chemotherapy reflect underlying histological markers of tumour response as measured by tumour regression grade (TRG). Methods: Twenty-six patients were enrolled in the study. Baseline, 14 days, and pre-surgery MRI were performed per study protocol. Surgical resection was performed in 23 of the enrolled patients; imaging-pathological correlation was obtained from 39 lesions from 21 patients. Results: There was no evidence of correlation between TRG and ADC changes at day 14 (study primary endpoint), and no significant correlation with other ADC metrics. In scans acquired one week prior to surgery, there was no significant correlation between ADC metrics and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki67 index. Conclusions: Our hypothesis was not supported by the data. The lack of meaningful correlation between change in ADC and TRG is a robust finding which is not explained by variability or small sample size. Change in ADC is not a proxy for TRG in metastatic colorectal cancer.

T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study

OBJECTIVE

To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer.

METHODS

Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm²). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADC_mean, ADC_min, D_mean, D_min, D*, f, MD_mean, MD_min, MK_mean, and MK_max) were compared based on histological type, grade, and LVSI status.

RESULTS

Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MK_mean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADC_min, D_min, and MD_min were significantly lower while MK_max was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MK_mean than LVSI-negative SCC (p < 0.05).

CONCLUSION

Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients.

ADVANCES IN KNOWLEDGE

Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.

Diffusion-weighted MRI to determine response and long-term clinical outcomes in muscle-invasive bladder cancer following neoadjuvant chemotherapy

Objective

This study aims to determine local treatment response and long-term survival outcomes in patients with localised muscle-invasive bladder cancer (MIBC) patients receiving neoadjuvant chemotherapy (NAC) using diffusion-weighted MRI (DWI) and apparent diffusion coefficient (ADC) analysis.

Methods

Patients with T2-T4aN0-3M0 bladder cancer suitable for NAC were recruited prospectively. DWI was performed prior to NAC and was repeated following NAC completion. Conventional response assessment was performed with cystoscopy and tumour site biopsy. Response was dichotomised into response (

Results

Forty-eight patients (96 DWI) were evaluated. NAC response was associated with significant increase in mean ΔADC and %ΔADC compared to poor response (ΔADCall 0.32×10-3 versus 0.11×10-3 mm2/s; p=0.009, and %ΔADCall 21.70% versus 8.23%; p=0.013). Highest specificity predicting response was seen at 75th percentile ADC (AUC, 0.8; p=0.01). Sensitivity, specificity, positive predictive power, and negative predictive power of %ΔADCb100 75th percentile was 73.7%, 90.0%, 96.6%, and 52.9%, respectively. %ΔADCb100 75th percentile >15.5% was associated with significant improvement in OS (HR, 0.40; 95% CI, 0.19-0.86; p=0.0179), bCSS (HR, 0.26; 95% CI, 0.08-0.82; p=0.0214), PFS (HR, 0.16; 95% CI, 0.05-0.48; p=0.0012), and time to cystectomy (HR, 0.19; 95% CI, 0.07-0.47; p=0.0004).

Conclusions

Quantitative ADC analysis can successfully identify NAC response and improved long-term clinical outcomes. Multi-centre validation to assess reproducibility and repeatability is required before testing within clinical trials to inform MIBC treatment decision making.

Advances in knowledge

We successfully demonstrated that measured change in DWI can successfully identify NAC response and improved long-term survival outcomes.

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Key Words

• MRI
• diffusion weighted magnetic resonance imaging (DWI)
• imaging biomakers
• muscle invasive bladder cancer (MIBC)
• neoadjuavant chemotherapy

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MESH Headings Collapse

Grants

• 28724 Cancer Research UK

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Affiliation(s)

Shaista Hafeez Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Mu Koh Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Kelly Jones Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Amir El Ghzal Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
James D’Arcy Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
Pardeep Kumar Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Vincent Khoo Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Susan Lalondrelle Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Fiona McDonald Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Alan Thompson Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Erica Scurr Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Aslam Sohaib Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Robert Anthony Huddart Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom

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Preliminary study of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted MRI and diffusion kurtosis imaging on differential diagnosis of spinal metastases and chordoma

PURPOSE

Quantitative comparison of diffusion parameters from various models of diffusion-weighted (DWI) and diffusion kurtosis (DKI) imaging for distinguishing spinal metastases and chordomas.

METHODS

DWI and DKI examinations were performed in 31 and 13 cases of spinal metastases and chordomas, respectively. DWI derived apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), water molecular distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α). DKI derived mean diffusivity (MD) and mean kurtosis (MK). Independent sample t-testing compared statistical differences among parameters. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were determined. Pearson correlation analysis evaluated the parameters' correlations.

RESULTS

ADC, D, f, DDC, α, and MD were significantly lower in spinal metastases than chordomas (all P < 0.05). MK was significantly higher in spinal metastases than chordomas (P < 0.05). D had the highest area under the ROC curve (AUC) of 0.886, greater than MD (AUC = 0.706) or DDC (AUC = 0.742) in differentiating the two tumors (both P < 0.05). Combining D with f and α statistically significantly increased the AUC for diagnosis (to 0.995) relative to D alone (P < 0.05). There was a certain correlation among DDC, ADC, and D (all P < 0.05).

CONCLUSIONS

Monoexponential, biexponential, and stretched-exponential models of DWI and DKI can potentially differentiate spinal metastases and chordomas. D combined with f and α performed best.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer

BACKGROUND

Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue.

PURPOSE

To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue.

MATERIAL AND METHODS

Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis.

RESULTS

All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05).

CONCLUSION

All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

Diffusion-Weighted Magnetic Resonance Imaging in Ovarian Cancer: Exploiting Strengths and Understanding Limitations

Detection, characterization, staging, and response assessment are key steps in the imaging pathway of ovarian cancer. The most common type, high grade serous ovarian cancer, often presents late, so that accurate disease staging and response assessment are required through imaging in order to improve patient management. Currently, computerized tomography (CT) is the most common method for these tasks, but due to its poor soft-tissue contrast, it is unable to quantify early response within lesions before shrinkage is observed by size criteria. Therefore, quantifiable techniques, such as diffusion-weighted magnetic resonance imaging (DW-MRI), which generates high contrast between tumor and healthy tissue, are increasingly being explored. This article discusses the basis of diffusion-weighted contrast and the technical issues that must be addressed in order to achieve optimal implementation and robust quantifiable diffusion-weighted metrics in the abdomen and pelvis. The role of DW-MRI in characterizing adnexal masses in order to distinguish benign from malignant disease, and to differentiate borderline from frankly invasive malignancy is discussed, emphasizing the importance of morphological imaging over diffusion-weighted metrics in this regard. Its key role in disease staging and predicting resectability in comparison to CT is addressed, including its valuable use as a biomarker for following response within individual lesions, where early changes in the apparent diffusion coefficient in peritoneal metastases may be detected. Finally, the task of implementing DW-MRI into clinical trials in order to validate this biomarker for clinical use are discussed, along with the trials that include it within their protocols.

Changes in apparent diffusion coefficient and pathological response in colorectal liver metastases after preoperative chemotherapy

BACKGROUND

The pathological response to preoperative chemotherapy of colorectal liver metastases (CRLMs) is predictive of long-term prognosis after liver resection. Accurate preoperative assessment of chemotherapy response could enable treatment optimization.

PURPOSE

To investigate whether changes in lesion-apparent diffusion coefficient (ADC) measured with diffusion-weighted magnetic resonance imaging (MRI) can be used to assess pathological treatment response in patients with CRLMs undergoing preoperative chemotherapy.

MATERIAL AND METHODS

Patients who underwent liver resection for CRLMs after preoperative chemotherapy between January 2011 and December 2019 were retrospectively included if they had undergone MRI before and after preoperative chemotherapy on the same 1.5-T MRI scanner with diffusion-weighted imaging with b-values 50, 400, and 800 s/mm². The pathological chemotherapy response was assessed using the tumor regression grade (TRG) by AJCC/CAP. Lesions were divided into two groups: pathological responding (TRG 0-2) and non-responding (TRG 3). The change in lesion ADC after preoperative chemotherapy was compared between responding and non-responding lesions.

RESULTS

A total of 27 patients with 49 CRLMs were included, and 24/49 lesions showed a pathological chemotherapy response. After chemotherapy, ADC increased in both pathological responding (pretreatment ADC: 1.26 [95% confidence interval (CI)=1.06-1.37] vs. post-treatment ADC: 1.33 [95% CI=1.13-1.56] × 10^-3 mm²/s; P = 0.026) and non-responding lesions (1.12 [95% CI=0.980-1.21] vs. 1.20 [95% CI=1.09-1.43] × 10^-3 mm²/s; P = 0.018). There was no difference in median relative difference in ADC after chemotherapy between pathological responding and non-responding lesions (15.8 [95% CI=1.42-26.3] vs. 7.17 [95% CI=-4.31 to 31.2]%; P = 0.795).

CONCLUSION

Changes in CRLM ADCs did not differ between pathological responding and non-responding lesions.

Correlation between molecular prognostic factors and magnetic resonance imaging intravoxel incoherent motion histogram parameters in breast cancer

OBJECTIVE

To explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer.

MATERIALS AND METHODS

A total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images. Whole-tumor histogram parameters were obtained with Firevoxel's software by accumulating all ROIs. Next, Kolmogorov-Smirnov test, Student's t-test, Mann-Whitney U test, receiver operating characteristic curve analysis and spearman rank correlation analysis were used to assess the relationship between histogram parameters and molecular prognostic factors of breast cancer.

RESULTS

Among estrogen receptor (ER)-negative ROCs, the apparent diffusion coefficient (ADC) 10th percentile had the highest ROC of 0.792, with a cut-off value of 0.788 × 10^-3 mm²/s, and sensitivity and specificity of 0.714 and 0.867, respectively. The negative correlation between lymph node metastasis status and ADC standard deviation was significant (ρ = -0.44, the correlation coefficients was represented by ρ). Positive correlations were observed between hormonal expression of ER and progesterone receptor (PR) with heterogeneity metrics of ADC or perfusion fraction (f), such as ADC inhomogeneity (ρ = 0.37, ρ = 0.29) and f skewness (ρ = 0.32, ρ = 0.28). Negative correlations were observed with numerical metrics, such as the ADC median (ρ = -0.31, ρ = -0.34) and f 45th percentile (ρ = -0.35, ρ = -0.28). The positive correlations between human epidermal receptor factor-2 (HER2) and pseudo-diffusivity (Dp) numerical metrics, Ki-67 expression, and heterogeneity metrics of Dp were high.

CONCLUSIONS

The ADC 10th percentile had the largest area under the curve in the ER-negative ROC analysis, and the ADC standard deviation was the most valuable in the correlation analysis of lymph node metastasis. Whole-lesion quantitative histogram parameters of IVIM could, therefore, provide a scientific basis for radiomics to further guide clinical practice in the prognosis of breast cancer.

Radiomics of diffusion-weighted MRI compared to conventional measurement of apparent diffusion-coefficient for differentiation between benign and malignant soft tissue tumors

Diffusion-weighted imaging (DWI) is proven useful to differentiate benign and malignant soft tissue tumors (STTs). Radiomics utilizing a vast array of extracted imaging features has a potential to uncover disease characteristics. We aim to assess radiomics using DWI can outperform the conventional DWI for STT differentiation. In 151 patients with 80 benign and 71 malignant tumors, ADC_mean and ADC_min were measured on solid portion within the mass by two different readers. For radiomics approach, tumors were segmented and 100 original radiomic features were extracted on ADC map. Eight radiomics models were built with training set (n = 105), using combinations of 2 different algorithms—multivariate logistic regression (MLR) and random forest (RF)—and 4 different inputs: radiomics features (R), R + ADC_min (I), R + ADC_mean (E), R + ADC_min and ADC_mean (A). All models were validated with test set (n = 46), and AUCs of ADC_mean, ADC_min, MLR-R, RF-R, MLR-I, RF-I, MLR-E, RF-E, MLR-A and RF-A models were 0.729, 0.753 0.698, 0.700, 0.773, 0.807, 0.762, 0.744, 0.773 and 0.807, respectively, without statistically significant difference. In conclusion, radiomics approach did not add diagnostic value to conventional ADC measurement for differentiating benign and malignant STTs.

Development of MRI-Based Radiomics Model to Predict the Risk of Recurrence in Patients With Advanced High-Grade Serous Ovarian Carcinoma

OBJECTIVE. The purpose of our study was to develop a radiomics model based on preoperative MRI and clinical information for predicting recurrence-free survival (RFS) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). MATERIALS AND METHODS. This retrospective study enrolled 117 patients with HGSOC, including 90 patients with recurrence and 27 without recurrence; 1046 radiomics features were extracted from T2-weighted images and contrast-enhanced T1-weighted images using a manual segmentation method. L1 regularization-based least absolute shrinkage and selection operator (LASSO) regression was performed to select features, and the synthetic minority oversampling technique (SMOTE) was used to balance our dataset. A support vector machine (SVM) classifier was used to build the classification model. To validate the performance of the proposed models, we applied a leave-one-out cross-validation method to train and test the classifier. Cox proportional hazards regression, Harrell concordance index (C-index), and Kaplan-Meier plots analysis were used to evaluate the associations between radiomics signatures and RFS. RESULTS. The fusion radiomics-based model yielded a significantly higher AUC value of 0.85 in evaluating RFS than the model using contrast-enhanced T1-weighted imaging features alone or T2-weighted imaging features alone (AUC = 0.79 and 0.74 and p = .02 and .01, respectively). Kaplan-Meier survival curves showed significant differences between high and low recurrence risk in patients with HGSOC by different models. The fusion model combining radiomics features and clinical information showed higher performance than the clinical model (C-index = 0.62 and 0.60, respectively). CONCLUSION. The proposed MRI-based radiomics signatures may provide a potential way to develop a prediction model and can help identify patients with advanced HGSOC who have a high risk of recurrence.

Diffusion-weighted MRI and PET/CT reproducibility in epithelial ovarian cancers during neoadjuvant chemotherapy

PURPOSE

To investigate the reproducibility of diffusion-weighted (DW) MRI and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG)-Positron emission tomography/CT (PET/CT) in monitoring response to neoadjuvant chemotherapy in epithelial ovarian cancer.

MATERIALS AND METHODS

Ten women (median age, 67 years; range: 41.8-77.3 years) with stage IIIC-IV epithelial ovarian cancers were included in this prospective trial (NCT02792959) between 2014 and 2016. All underwent initial laparoscopic staging, four cycles of carboplatine-paclitaxel-based chemotherapy and interval debulking surgery. PET/CT and DW-MRI were performed at baseline (C0), after one cycle (C1) and before surgery (C4). Two nuclear physicians and two radiologists assessed five anatomic sites for the presence of ≥1 lesion. Target lesions in each site were defined and their apparent diffusion coefficient (ADC), maximal standardized uptake value (SUV-max), SUV-mean, SUL-peak, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were monitored (i.e., 10 patients ×5 sites ×3 time-points). Their relative early and late changes were calculated. Intra/inter-observer reproducibilities of qualitative and quantitative analysis were estimated with Kappa and intra-class correlation coefficients (ICCs).

RESULTS

For both modalities, inter- and intra-observer agreement percentages were excellent for initial staging but declined later for DW-MRI, leading to lower Kappa values for inter- and intra-observer variability (0.949 and 1 at C0, vs. 0.633 and 0.643 at C4, respectively) while Kappa values remained>0.8 for PET/CT. Inter- and intra-observer ICCs were>0.75 for SUV-max, SUL-peak, SUV-mean and their change regardless the time-point. ADC showed lower ICCs (range: 0.013-0.811). ANOVA found significant influences of the evaluation time, the measurement used (ADC, SUV-max, SUV-mean, SUV-max, SUL-peak, MTV or TLG) and their interaction on ICC values (P=0.0023, P<0.0001 and P =0.0028, respectively).

CONCLUSION

While both modalities demonstrated high reproducibility at baseline, only SUV-max, SUL-peak, SUV-mean and their changes maintained high reproducibility during chemotherapy.

Noninvasive DW-MRI metrics for staging hepatic fibrosis and grading inflammatory activity in patients with chronic hepatitis B

PURPOSE

To assess the value of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging (DWI) models for staging hepatic fibrosis (HF) and grading inflammatory activity in patients with chronic hepatitis B (CHB).

METHODS

82 patients with CHB and 30 healthy volunteers underwent DWI with 13 b-values on a 3T MRI unit. The standard apparent diffusion coefficient (ADC_st) was calculated using a monoexponential model. The true diffusion coefficient (D_t), pseudo-diffusion coefficient (D_p), and perfusion fraction (f) were calculated using a biexponential model. The distributed diffusion coefficient (DDC) and water-molecule diffusion heterogeneity index (α) were calculated using a stretched-exponential model. Receiver operating characteristic (ROC) curves were performed for diffusion parameters to compare the diagnosis performance.

RESULTS

The distributions of hepatic fibrosis stages and the inflammatory activity grades (METAVIR scoring system) were as follows: F0, n = 1; F1, n = 16; F2, n = 31; F3, n = 19; and F4, n = 15. A0, n = 1; A1, n = 14; A2, n = 46; and A3, n = 21. ADC_st, D_t and DDC values showed negative correlation with the fibrosis stage (r = - 0.418, - 0.717 and - 0.630, all P < 0.001) and the inflammatory activity grade (r = - 0.514, - 0.626 and - 0.550, all P < 0.001). The area under the ROC curve (AUC) of D_t (AUC = 0.854, 0.881) and DDC (AUC = 0.794, 0.834) were significantly higher than that of ADC_st (AUC = 0.637, 0.717) in discriminating significant fibrosis (≥ F2) and advanced fibrosis (≥ F3) (all P < 0.05). Although D_t (AUC = 0.867, 0.836) and DDC (AUC = 0.810, 0.808) showed higher AUCs than ADC_st (AUC = 0.767, 0.803), there was no significant difference in their ability in detecting inflammatory activity grade ≥ A2/A3 (P > 0.05).

CONCLUSIONS

D_t and DDC are promising indicators and outperform ADC_st for staging HF. While both D_t and DDC have similar diagnostic performance compared with ADC_st for grading inflammatory activity.

Association between IVIM parameters and treatment response in locally advanced squamous cell cervical cancer treated by chemoradiotherapy

OBJECTIVE

To examine the associations of intravoxel incoherent motion (IVIM) parameters with treatment response in cervical cancer following concurrent chemoradiotherapy (CCRT).

MATERIALS AND METHODS

Forty-five patients, median age of 58 years (range: 28-82), with pre-CCRT and post-CCRT MRI, were retrospectively analysed. The IVIM parameters pure diffusion coefficient (D) and perfusion fraction (f) were estimated using the full b-value distribution (BVD) as well as an optimised subsample BVD. Dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC) were used to measure observer repeatability in tumour delineation at both time points. Treatment response was determined by the response evaluation criteria in solid tumour (RECIST) 1.1 between MRI examinations. Mann-Whitney U tests were used to test for significant differences in IVIM parameters between treatment response groups.

RESULTS

Pre-CCRT tumour delineation repeatability was good (DSC = 0.81) while post-CCRT delineation repeatability was moderate (DSC = 0.67). Values of D and f had good repeatability at both time points (ICC > 0.80). Pre-CCRT f estimated using the full BVD and optimised subsample BVD were found to be significantly higher in patients with partial response compared to those with stable disease or disease progression (p = 0.01 and 95% CI = -0.02-0.00 for both cases).

CONCLUSION

Pre-CCRT f was associated with treatment response in cervical cancer with good observer repeatability. Similar discriminative ability was also observed in estimated pre-CCRT f from an optimised subsample BVD.

KEY POINTS

• Pre-treatment tumour delineation and IVIM parameters had good observer repeatability. • Post-treatment tumour delineation was worse than at pre-treatment, but IVIM parameters retained good ICC. • Pre-treatment perfusion fraction estimated from all b-values and an optimised subsample of b-values were associated with treatment response.

Comparison of models of diffusion in Wilms' tumours and normal contralateral renal tissue

Objective

ADC (Apparent Diffusion Coefficient) derived from Diffusion-Weighted Imaging (DWI) has shown promise as a non-invasive quantitative imaging biomarker in Wilms’ tumours. However, many non-Gaussian models could be applied to DWI. This study aimed to compare the suitability of four diffusion models (mono exponential, IVIM [Intravoxel Incoherent Motion], stretched exponential, and kurtosis) in Wilms’ tumours and the unaffected contralateral kidneys.

Materials and methods

DWI data were retrospectively reviewed (110 Wilms’ tumours and 75 normal kidney datasets). The goodness of fit for each model was measured voxel-wise using Akaike Information Criteria (AIC). Mean AIC was calculated for each tumour volume (or contralateral normal kidney tissue). One-way ANOVAs with Greenhouse–Geisser correction and post hoc tests using the Bonferroni correction evaluated significant differences between AIC values; the lowest AIC indicating the optimum model.

Results

IVIM and stretched exponential provided the best fits to the Wilms’ tumour DWI data. IVIM provided the best fit for the normal kidney data. Mono exponential was the least appropriate fitting method for both Wilms’ tumour and normal kidney data.

Discussion

The diffusion weighted signal in Wilms’ tumours and normal kidney tissue does not exhibit a mono-exponential decay and is better described by non-Gaussian models of diffusion.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

Application of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted magnetic resonance imaging in the differential diagnosis of metastases and myeloma in the spine-Univariate and multivariate analysis of related parameters

OBJECTIVE

To explore the value of related parameters in monoexponential, biexponential, and stretched-exponential models of diffusion-weighted imaging (DWI) in differentiating metastases and myeloma in the spine.

METHODS

53 metastases and 16 myeloma patients underwent MRI with 10 b-values (0-1500 s/mm²). Parameters of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), the distribution diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) from DWI were calculated. The independent sample t test and the Mann-Whiney U test were used to compare the statistical difference of the parameter values between the two. Receiver operating characteristics (ROC) curve analysis was used to identify the diagnostic efficacy. Then substituted each parameter into the decision tree model and logistic regression model, identified meaningful parameters, and evaluated their joint diagnostic performance.

RESULTS

The ADC, D, and α values of metastases were higher than those of myeloma, whereas the D* value was lower than that of myeloma, and the difference was significant (p < 0.05); the area under the ROC curve for the above parameters was 0.661, 0.710, 0.781, and 0.743, respectively. There was no significant difference in the f and DDC values (p > 0.05). D and α were found to conform to the decision tree model, and the accuracy of model diagnosis was 84.1%. ADC and α were found to conform to the logistic regression model, and the accuracy was 87.0%.

CONCLUSION

The 3 models of DWI have certain values indifferentiating metastases and myeloma in spine, and the diagnostic performance of ADC, D, α and D*was better. Combining ADC with α may markedly aid in the differential diagnosis of the two.

ADVANCES IN KNOWLEDGE

Monoexponential, biexponential, and stretched-exponential models can offer additional information in the differential diagnosis of metastases and myeloma in the spine. Decision tree model and logistic regression model are effective methods to help further distinguish the two.

Removing rician bias in diffusional kurtosis of the prostate using real-data reconstruction

PURPOSE

To compare prostate diffusional kurtosis imaging (DKI) metrics generated using phase-corrected real data with those generated using magnitude data with and without noise compensation (NC).

METHODS

Diffusion-weighted images were acquired at 3T in 16 prostate cancer patients, measuring 6 b-values (0-1500 s/mm2 ), each acquired with 6 signal averages along 3 diffusion directions, with noise-only images acquired to allow NC. In addition to conventional magnitude averaging, phase-corrected real data were averaged in an attempt to reduce rician noise-bias, with a range of phase-correction low-pass filter (LPF) sizes (8-128 pixels) tested. Each method was also tested using simulations. Pixelwise maps of apparent diffusion (D) and apparent kurtosis (K) were calculated for magnitude data with and without NC and phase-corrected real data. Average values were compared in tumor, normal transition zone (NTZ), and normal peripheral zone (NPZ).

RESULTS

Simulations indicated LPF size can strongly affect K metrics, where 64-pixel LPFs produced accurate metrics. Relative to metrics estimated from magnitude data without NC, median NC K were lower (P < 0.0001) by 6/11/8% in tumor/NPZ/NTZ, 64-LPF real-data K were lower (P < 0.0001) by 4/10/7%, respectively.

CONCLUSION

Compared with magnitude data with NC, phase-corrected real data can produce similar K, although the choice of phase-correction LPF should be chosen carefully.

Comparison of Monoexponential, Biexponential, Stretched-Exponential, and Kurtosis Models of Diffusion-Weighted Imaging in Differentiation of Renal Solid Masses

Objective

To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [D_f], slow diffusion coefficient [D_s], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses.

Materials and Methods

A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30–69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations.

Results

Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, D_s, and MK showed significant differences between benign and malignant lesions (p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) (p < 0.05). α was significantly lower in the benign group than in the malignant group (p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC (p < 0.05) except D_f and α (p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) (p > 0.05).

Conclusion

Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer

OBJECTIVE

To evaluate the usefulness of histogram analysis of stretched exponential model (SEM) on diffusion-weighted imaging in evaluating clinically significant prostate cancer (CSC).

METHODS

A total of 85 patients with prostate cancer underwent 3 T multiparametric MRI, followed by radical prostatectomy. Histogram parameters of the tumor from the SEM [distributed diffusion coefficient (DDC) and α] and the monoexponential model [MEM; apparent diffusion coefficient (ADC)] were evaluated. The associations between parameters and Gleason score or Prostate Imaging Reporting and Data System v. 2 were evaluated. The area under the receiver operating characteristics curve was calculated to evaluate diagnostic performance of parameters in predicting CSC.

RESULTS

The values of histogram parameters of DDC and ADC were significantly lower in patients with CSC than in patients without CSC (p < 0.05), except for skewness and kurtosis. The value of the 25th percentile of α was significantly lower in patients with CSC than in patients without CSC (p = 0.014). Histogram parameters of ADC and DDC had significant weak to moderate negative associations with Gleason score or Prostate Imaging Reporting and Data System v. 2 (p < 0.001), except for skewness and kurtosis. For predicting CSC, the area under the curves of mean ADC (0.856), 50th percentile DDC (0.852), and 25th percentile α (0.707) yielded the highest values compared to other histogram parameters from each group.

CONCLUSION

Histogram analysis of the SEM on diffusion-weighted imaging may be a useful quantitative tool for evaluating CSC. However, the SEM did not outperform the MEM.

ADVANCES IN KNOWLEDGE

Histogram parameters of SEM may be useful for evaluating CSC.

Diffusion-weighted magnetic resonance imaging in peritoneal carcinomatosis from suspected ovarian cancer: Diagnostic performance in correlation with surgical findings

PURPOSE

Ovarian cancer (OC) is the commonest cause of death by gynaecological cancer in developed countries. Peritoneal carcinomatosis (PC) complete debulking without residual disease of >1 cm is the best prognostic predictor in advanced OC. PC is assessed with Computed tomography (CT). CT accuracy and cytoreduction success predictive ability are limited. PET/CT is not an imaging standard for PC. PC shows high signal foci in Diffusion-weighted magnetic resonance imaging (DWI MRI). We assessed the diagnostic performance (DP) and tumour burden correlation of Whole body DWI with background suppression MRI (WB-DWIBS/MRI) in PC of suspected OC using the Peritoneal Cancer Index (PCI), referring to cytoreduction surgery as the standard reference.

METHOD

Fifty patients with suspicion of disseminated OC underwent cytoreduction and WB-DWIBS/MRI. The PCI scores tumour burden (0-3) in 13 anatomical regions (global range of 0-39). Two radiologists (Rad1/Rad2) assessed the PCI preoperatively and with surgical findings. We evaluated regional and global DP, the interobserver agreement (Cohen´s kappa coefficient), statistical differences (McNemar test) and tumour burden (Pearson's test).

RESULTS

72% (36/50) were epithelial OC and 78% (39/50) achieved complete cytoreduction. Global-PCI correlation was 0.762 (Rad1) with DP: Sensitivity 0.84, specificity 0.89, accuracy 0.89, and kappa 0.41. Average global-PCI was 7. The pelvis and right hypochondrium showed the highest positive rate and DP, while the intestinal regions presented the lowest. Previous studies reported higher sensitivity than CT or PET/CT, although only a few used the PCI.

CONCLUSIONS

WB-DWIBS/MRI is reliable to depict, quantify and to predict complete cytoreductive surgery in OC PC.

Intravoxel Incoherent Motion Imaging in Differentiation Borderline From Malignant Ovarian Epithelial Tumors: Correlation With Histological Cell Proliferation and Vessel Characteristics

BACKGROUND

The differentiation of borderline from malignant ovarian epithelial tumors (OETs) is difficult based on morphologic characteristics. Diffusion and perfusion information from intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) might be useful for this distinction.

PURPOSE

To investigate the potential of IVIM-DWI in discriminating borderline from malignant OETs by correlating with cell proliferation and microvessel density (MVD).

STUDY TYPE

Prospective.

SUBJECTS

Sixty-six patients with OETs (22 borderline, BOETs; 44 malignant, MOETs) underwent IVIM-DWI before surgery.

FIELD STRENGTH

3.0T IVIM-DWI sequence with 12 b-values (0-1000 sec/mm² ).

ASSESSMENT

Apparent diffusion coefficient (ADC) and IVIM-DWI parameters (diffusion coefficient [D], microvascular volume fraction [f], and pseudodiffusion coefficient [D*]) were measured. Cell proliferation and MVD was determined by immunohistochemical staining of Ki-67 and CD-31, respectively.

STATISTICAL TESTS

Mann-Whitney U-test; two-sample t-test; intraclass correlation coefficient; Bland-Altman analysis; receiver operating characteristics (ROC) curves; and Spearman correlation.

RESULTS

ADC and D in BOETs was significantly higher than those in MOETs (P < 0.001), while f in BOETs was significantly lower than those in MOETs (P < 0.001). No significant difference was found in D* between borderline and malignancies (P = 0.324). In the differential diagnosis of borderline from malignant OETs; D demonstrated the highest area under the curve (AUC) of 0.951, while ADC and f had a lower AUC of 0.921 and 0.847, respectively. The ADC and D was negatively correlated with cell proliferation (r = -0.682, r = -0.694, respectively, P < 0.001), while f was positively correlated with MVD of the OETs (r = 0.558, P < 0.001).

DATA CONCLUSION

IVIM-DWI may be a useful tool for differentiating BOETs from MOETs. D and f could be image biomarkers to reflect histopathological characteristics of cell proliferation and MVD in OETs.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:928-935.

Extended abdominopelvic MRI versus CT at the time of adnexal mass characterization for assessing radiologic peritoneal cancer index (PCI) prior to cytoreductive surgery

PURPOSE

To evaluate whether extending the MRI scan to include the abdomen at the time of adnexal mass characterization could replace additional CT for peritoneal cancer index (PCI) assessment.

METHODS

After institutional review board approval for this prospective study, 36 consecutive females with ovarian and FT malignancies were included. All patients signed an informed consent. Patients underwent preoperative CT (32 patients) and MRI (36 patients). Images were interpreted by 2 independent observers. Surgical data were available in 27 patients. Region-by-region analysis was performed for detection rates of peritoneal carcinomatosis (PC). Inter-observer agreement for each region was evaluated by kappa statistics. Radiologic PCI was calculated by CT and MRI independently and inter-observer agreement for CT and MRI as well as agreement between radiologic and surgical PCI were evaluated by weighted-kappa statistics.

RESULTS

On region-by-region analysis, the highest detection rates of PC were noted at the central abdomen and pelvis. Detection rates were higher by MRI than CT, mainly in bowel serosal surface, pelvis, and right upper abdomen regions. Inter-observer agreement of MRI was higher than CT in most regions. The median PCI by CT was 5 and 4 for the first and second observers (range 0-21 for both observers), respectively. The median PCI by MRI was 6 (range 0-23 for both observers). The inter-observer agreement of PCI was excellent by both CT and MRI (k = 0.876 and k = 0.912, respectively). The agreement between CT and surgical PCI was 0.660 and 0.590 for the first and second observers, respectively. The agreement between MRI and surgical PCI was 0.797 and 0.798 for the first and second observers, respectively.

CONCLUSIONS

Extending MRI scan to include the abdomen at the time of adnexal mass characterization allows accurate estimation of PC, with better results than CT, obviating the need for dedicated CT scan of abdomen and pelvis for imaging of PC.

Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.

Monoexponential, Biexponential, and stretched-exponential models using diffusion-weighted imaging: A quantitative differentiation of breast lesions at 3.0T

BACKGROUND

Diffusion-weighted imaging (DWI) plays an important role in the differentiation of malignant and benign breast lesions.

PURPOSE

To investigate the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential DWI models in the differential diagnosis of breast lesions.

STUDY TYPE

Prospective.

POPULATION

Sixty-one patients (age range: 25-68 years old; mean age: 46 years old) with 31 malignant lesions, 42 benign lesions, and 28 normal breast tissues diagnosed initially by clinical palpation, ultrasonography, or conventional mammography were enrolled in the study from January to September 2016.

FIELD STRENGTH

3.0T MR scanner, T₁ WI, T₂ WI, DWI (conventional and multi-b values), dynamic contrast-enhanced.

ASSESSMENT

The apparent diffusion coefficient (ADC) was calculated by monoexponential analysis. The diffusion coefficient (ADC_slow ), pseudodiffusion coefficient (ADC_fast ), and perfusion fraction (f) were calculated using the biexponential model. The distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) were obtained using a stretched-exponential model. All parameters were compared for malignant tumors, benign tumors, and normal breast tissues. A receiver operating characteristic curve was used to compare the ability of these parameters, in order to differentiate benign and malignant breast lesions.

STATISTICAL TESTS

All statistical analyses were performed using statistical software (SPSS).

RESULTS

ADC, ADC_slow , f, DDC, and α values were significantly lower in malignant tumors when compared with normal breast tissues and benign tumors (P < 0.05). However, ADC and f had higher area under the receiver operating characteristic curve (AUC) values (0.889 and 0.919, respectively).

DATA CONCLUSION

The parameters derived from the biexponential and stretched-exponential DWI could provide additional information for differentiating between benign and malignant breast tumors when compared with conventional diffusion parameters.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;50:1461-1467.

Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial

Quantitative radiomics features, extracted from medical images, characterize tumour-phenotypes and have been shown to provide prognostic value in predicting clinical outcomes. Stability of radiomics features extracted from apparent diffusion coefficient (ADC)-maps is essential for reliable correlation with the underlying pathology and its clinical applications. Within a multicentre, multi-vendor trial we established a method to analyse radiomics features from ADC-maps of ovarian (n = 12), lung (n = 19), and colorectal liver metastasis (n = 30) cancer patients who underwent repeated (<7 days) diffusion-weighted imaging at 1.5 T and 3 T. From these ADC-maps, 1322 features describing tumour shape, texture and intensity were retrospectively extracted and stable features were selected using the concordance correlation coefficient (CCC > 0.85). Although some features were tissue- and/or respiratory motion-specific, 122 features were stable for all tumour-entities. A large proportion of features were stable across different vendors and field strengths. By extracting stable phenotypic features, fitting-dimensionality is reduced and reliable prognostic models can be created, paving the way for clinical implementation of ADC-based radiomics.

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer

RATIONALE AND OBJECTIVES

We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer.

MATERIALS AND METHODS

Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations.

RESULTS

ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively.

CONCLUSION

Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.

Variability in quantitative diffusion-weighted MR imaging (DWI) across different scanners and imaging sites: is there a potential consensus that can help reducing the limits of expected bias?

KEY POINTS

• Variability of ADC measurements may be substantial across different MRI scanners and imaging sites. • DWI protocol standardization and increased awareness of frequent sources of error can help reducing the limits of expected bias. • Focusing on ADC change and normalized ADC values rather than on absolute measurements can facilitate consistent use of ADC in multi-center studies.

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.

Characterization of tubo-ovarian abscess mimicking adnexal masses: Comparison between contrast-enhanced CT, 18F-FDG PET/CT and MRI

0BJECTIVE: We compared the diagnostic accuracy of contrast-enhanced computed tomography (CT), fluorine 18-labeled-fludeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/CT and conventional magnetic resonance imaging (MRI) without and with diffusion-weighted imaging (DWI) for characterization of tubo-ovarian abscesses (TOAs) that mimic adnexal tumors.

MATERIALS AND METHODS

We evaluated (retrospectively) 43 patients who underwent contrast-enhanced CT, PET/CT, conventional MRI without and with DWI, and who were found to have TOAs and complex adnexal tumors. All images were evaluated independently by four radiologists using a two-point grading system. Results of contrast-enhanced CT, PET/CT, MRI without DWI, and MRI with DWI were compared for each patient using receiver operating characteristic curves. Sensitivity, specificity, and positive predictive value (PPV) were calculated and compared using the chi-square test.

RESULTS

Sensitivity of MRI with DWI (95%) was significantly higher than that of contrast-enhanced CT (78.6%), PET/CT (86.7%) and MRI without DWI (87.5%). Specificities of these modalities were not significantly different. The PPV of MRI with DWI (100%) was significantly higher than that of the other three modalities (CT, 72.4%; PET/CT 78.5%; MRI without DWI, 81.5%). Overall accuracy of MRI with DWI was significantly higher than that of the other three modalities (CT, 74.4%; PET/CT, 81.4%; MRI without DWI, 83.7%).

CONCLUSION

MRI with DWI shows high accuracy for characterization of complex ovarian lesions, and is the most useful method for differentiation of TOAs from ovarian tumors.

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.

BOLD MRI to evaluate early development of renal injury in a rat model of diabetes

Objective

To investigate changes in renal oxygenation levels by blood-oxygenation-level dependent (BOLD)-magnetic resonance imaging (MRI), and to evaluate BOLD-MRI for detecting early diabetic renal injury.

Methods

Seventy-five rats, with unilateral nephrectomy, were randomly divided into streptozotocin-induced diabetes mellitus (DM, n = 65) and normal control (NC, n = 10) groups. BOLD-MRI scans were performed at baseline (both groups) and at 3, 7, 14, 21, 28, 35, 42, 49, 56, 63 and 70 days (DM only). Renal cortical (C) and medullary (M) R2* signals were measured and R2* medulla/cortex ratio (MCR) was calculated.

Results

DM-group CR2* and MR2* values were significantly higher than NC values following diabetes induction. R2* values increased gradually and peaked at day 35 (CR2*, 33.95 ± 0.34 s^–1; MR2*, 43.79 ± 1.46 s^–1), then dropped gradually (CR2*, 33.17 ± 0.69 s^–1; MR2*, 41.61 ± 0.95 s^–1 at day 70). DM-group MCR rose gradually from 1.12 to 1.32 at day 42, then decreased to 1.25 by day 70.

Conclusions

BOLD-MRI can be used to non-invasively evaluate renal hypoxia and early diabetic renal injury in diabetic rats. MCR may be adopted to reflect dynamic changes in renal hypoxia.

UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer

OBJECTIVE

Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology.

METHODS

A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control.

RESULTS

The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T.

CONCLUSION

This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.

A data-driven statistical model that estimates measurement uncertainty improves interpretation of ADC reproducibility: a multi-site study of liver metastases

Apparent Diffusion Coefficient (ADC) is a potential quantitative imaging biomarker for tumour cell density and is widely used to detect early treatment changes in cancer therapy. We propose a strategy to improve confidence in the interpretation of measured changes in ADC using a data-driven model that describes sources of measurement error. Observed ADC is then standardised against this estimation of uncertainty for any given measurement. 20 patients were recruited prospectively and equitably across 4 sites, and scanned twice (test-retest) within 7 days. Repeatability measurements of defined regions (ROIs) of tumour and normal tissue were quantified as percentage change in mean ADC (test vs. re-test) and then standardised against an estimation of uncertainty. Multi-site reproducibility, (quantified as width of the 95% confidence bound between the lower confidence interval and higher confidence interval for all repeatability measurements), was compared before and after standardisation to the model. The 95% confidence interval width used to determine a statistically significant change reduced from 21.1 to 2.7% after standardisation. Small tumour volumes and respiratory motion were found to be important contributors to poor reproducibility. A look up chart has been provided for investigators who would like to estimate uncertainty from statistical error on individual ADC measurements.

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.

Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging of Cervical Cancer With Different b-Values

OBJECTIVE

The aims of this study were to evaluate the dependence of diffusion parameters on the b values adopted for intravoxel incoherent motion diffusion-weighted magnetic resonance imaging and to investigate the application value of multiple diffusion parameters obtained from monoexponential and biexponential models in subjects with a normal cervix and in cervical cancer patients.

METHODS

A total of 120 female patients with cervical cancer and 21 female control subjects with a normal cervix underwent diffusion-weighted magnetic resonance imaging with 13 b values (0-2000 s/mm) at 3 T. The standard apparent diffusion coefficient (Dst), diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated by fitting with monoexponential and biexponential models at 2 different ranges of b values: 0 to 1000 and 0 to 2000 s/mm. A univariate analysis was performed to identify factors that could distinguish cervical carcinoma from normal cervical tissue. Parameters that correlated with the pathological grade and stage of cervical cancer were also evaluated. Receiver operating characteristic curves were used to evaluate the diagnostic efficiency of every parameter.

RESULTS

All the tested parameters, except the D* of the 2 different ranges of b value groups, significantly differed between the patients with cervical carcinoma and control subjects (P < 0.01). D2000, Dst2000, and D1000 showed comparable diagnostic value, with an area under the curve of 0.923, 0.909, and 0.907, respectively. Dst2000, D2000, Dst1000, and D1000 differed significantly among the 3 degrees of cervical stromal infiltration depth (P < 0.05).

CONCLUSIONS

D2000 and Dst2000 tended to outperform D1000 in terms of diagnostic efficiency, but there was no significant difference in their ability to differentiate cervical carcinoma from normal cervix. Cervical cancers with lower Dst and D values tended to have greater infiltration depth.

Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases

Diffusion-weighted imaging quantified using the mono-exponential model has shown great promise for monitoring treatment response in prostate cancer bone metastases. The aim of this prospective study is to evaluate whether non-mono-exponential diffusion models better describe the water diffusion properties and may improve treatment response assessment. Diffusion-weighted imaging data of 12 treatment-naïve patients with 34 metastases acquired before and at one, two, and three months after initiation of antiandrogen treatment are analysed using the mono-exponential, the intravoxel incoherent motion, the stretched exponential, and the statistical model. Repeatability of the fitted parameters and changes under therapy are quantified. Model preference is assessed and correlation coefficients across times are calculated to delineate the relationship between the prostate-specific antigen levels and the diffusion parameters as well as between the diffusion parameters within each model. There is a clear preference for non-mono-exponential diffusion models at all time points. Particularly the stretched exponential is favoured in approximately 60% of the lesions. Its parameters increase significantly in response to treatment and are highly repeatable. Thus, the stretched exponential may be utilized as a potential optimal model for monitoring treatment response. Compared with the mono-exponential model, it may provide complementary information on tissue properties and improve response assessment.

Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations

OBJECTIVES

To assess the feasibility of the mono-exponential, bi-exponential and stretched-exponential models in evaluating response of breast tumours to neoadjuvant chemotherapy (NACT) at 3 T.

METHODS

Thirty-six female patients (median age 53, range 32-75 years) with invasive breast cancer undergoing NACT were enrolled for diffusion-weighted MRI (DW-MRI) prior to the start of treatment. For assessment of early response, changes in parameters were evaluated on mid-treatment MRI in 22 patients. DW-MRI was performed using eight b values (0, 30, 60, 90, 120, 300, 600, 900 s/mm2). Apparent diffusion coefficient (ADC), tissue diffusion coefficient (D t), vascular fraction (ƒ), distributed diffusion coefficient (DDC) and alpha (α) parameters were derived. Then t tests compared the baseline and changes in parameters between response groups. Repeatability was assessed at inter- and intraobserver levels.

RESULTS

All patients underwent baseline MRI whereas 22 lesions were available at mid-treatment. At pretreatment, mean diffusion coefficients demonstrated significant differences between groups (p < 0.05). At mid-treatment, percentage increase in ADC and DDC showed significant differences between responders (49 % and 43 %) and non-responders (21 % and 32 %) (p = 0.03, p = 0.04). Overall, stretched-exponential parameters showed excellent repeatability.

CONCLUSION

DW-MRI is sensitive to baseline and early treatment changes in breast cancer using non-mono-exponential models, and the stretched-exponential model can potentially monitor such changes.

KEY POINTS

• Baseline diffusion coefficients demonstrated significant differences between complete pathological responders and non-responders. • Increase in ADC and DDC at mid-treatment can discriminate responders and non-responders. • The ƒ fraction at mid-treatment decreased in responders whereas increased in non-responders. • The mono- and stretched-exponential models showed excellent inter- and intrarater repeatability. • Treatment effects can potentially be assessed by non-mono-exponential diffusion models.

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models

PURPOSE

To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC).

MATERIALS AND METHODS

Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded.

RESULTS

Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809.

Intravoxel incoherent motion MRI assessment of chemoradiation-induced pelvic bone marrow changes in cervical cancer and correlation with hematological toxicity

PURPOSE

To investigate bone marrow changes after chemoradiation (CRT) using intravoxel incoherent motion magnetic resonance imaging (IVIM-MRI) and correlate imaging changes with hematological toxicity (HT) in patients with locally advanced cervical cancer.

MATERIALS AND METHODS

Thirty-nine patients with newly diagnosed cervical cancer were prospectively recruited for two sequential 3.0T IVIM-MRI studies: before treatment (MRI-1) and 3-4 weeks after standardized CRT (MRI-2). The irradiated pelvic bone marrow was outlined as the regions of interest to derive the true diffusion coefficient (D) and perfusion fraction (f) based on a biexponential model. The apparent coefficient diffusion (ADC) was derived using the monoexponential model. Changes in these parameters between MRI-1 and MRI-2 were calculated as ΔD, Δf, and ΔADC. HT was defined accordingly to NCI-CTCAE (v. 4.03) of grade 3 and above. Statistical analysis was performed using Mann-Whitney U-test.

RESULTS

The median age of patients was 54 years old (range 27-83 years old); 14 patients suffered from HT. Early bone marrow changes (3-4 weeks) of ΔD showed a significant difference between HT and non-HT groups (6.4 ± 19.7% vs. -6.4 ± 19.4%, respectively, P = 0.041). However, no significant changes were noted in Δf (3.7 ± 13.3% vs. 1.5 ± 12.5% respectively, P = 0. 592) and ΔADC (5.5 ± 26.3% vs. -3.3 ± 27.0% respectively, P = 0.303) between the HT and non-HT groups. Δf increased insignificantly for both groups.

CONCLUSION

ΔD was the only significant parameter to differentiate early cellular environment changes in bone marrow after CRT, suggestive that ΔD was more sensitive than Δf and ΔADC to reflect the underlying microenvironment injury.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1491-1498.

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

OBJECTIVES

Assessment of empirical diffusion-weighted MRI (DW-MRI) models in cervical tumours to investigate whether fitted parameters distinguish between types and grades of tumours.

METHODS

Forty-two patients (24 squamous cell carcinomas, 14 well/moderately differentiated, 10 poorly differentiated; 15 adenocarcinomas, 13 well/moderately differentiated, two poorly differentiated; three rare types) were imaged at 3 T using nine b-values (0 to 800 s mm-2). Mono-exponential, stretched exponential, kurtosis, statistical, and bi-exponential models were fitted. Model preference was assessed using Bayesian Information Criterion analysis. Differences in fitted parameters between tumour types/grades and correlation between fitted parameters were assessed using two-way analysis of variance and Pearson's linear correlation coefficient, respectively.

RESULTS

Non-mono-exponential models were preferred by 83 % of tumours with bi-exponential and stretched exponential models preferred by the largest numbers of tumours. Apparent diffusion coefficient (ADC) and diffusion coefficients from non-mono-exponential models were significantly lower in poorly differentiated tumours than well/moderately differentiated tumours. α (stretched exponential), K (kurtosis), f and D* (bi-exponential) were significantly different between tumour types. Strong correlation was observed between ADC and diffusion coefficients from other models.

CONCLUSIONS

Non-mono-exponential models were preferred to the mono-exponential model in DW-MRI data from cervical tumours. Parameters of non-mono-exponential models showed significant differences between types and grades of tumours.

KEY POINTS

• Non-mono-exponential DW-MRI models are preferred in the majority of cervical tumours. • Poorly differentiated cervical tumours exhibit lower diffusion coefficients than well/moderately differentiated tumours. • Non-mono-exponential model parameters α, K, f, and D* differ between tumour types. • Micro-structural features are likely to affect parameters in non-mono-exponential models differently.

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

OBJECTIVES

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours.

METHODS

Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm-2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians.

RESULTS

The values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083).

CONCLUSION

Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data.

KEY POINTS

• ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.

Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T 2 s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T 2 estimates. Two consented healthy volunteer cohorts (n  =  5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE  =  62-102 ms, b  =  0-250 mm-2s, 30 combinations. Protocol 2: 8 b-values 0-800 mm-2s at TE  =  62 ms, with 3 additional b-values 0-50 mm-2s at TE  =  80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4  ±  7% (TE  =  62 ms) to 30.7  ±  11% (TE  =  102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9  ±  6%, T2-IVIM: 18.3  ±  7%), as well as T 2  =  42.1  ±  7 ms, 77.6  ±  30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model.

Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: A prospective single-center study

PURPOSE

To assess stretched-exponential, mono-exponential and intravoxel incoherent motion (IVIM) models of diffusion-weighted MRI(DWI) in predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) in rectal cancer patients.

MATERIALS AND METHODS

This prospective study recruited 98 consecutive patients with locally advanced rectal cancer who underwent 3 Tesla MR examination before, during and after CRT. The apparent diffusion coefficient (ADC), IVIM-derived parameters (D, f, and D*), and stretched-exponential model-derived parameters (DDC and α) were measured. The parameters and their corresponding changes during and after CRT were compared between pCR and non-pCR. Receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Coefficient of variations and intraclass correlation coefficient were calculated to assess reliability and agreement.

RESULTS

Nineteen patients achieved pCR while 79 did not. The pCR group had higher ADC and α (ADC₂ and α₂ ), and their changes (ΔADC₂ , and Δα₂ ) at the endpoint than non-pCR group. α₂ and ADC₂ yielded similar AUCs (P = 0.339), Δα₂ and ΔADC₂ yielded similar AUCs (P = 0.263) ADC and α presented substantial agreement, and α presented the minimum CV (5.0-7.0%).

CONCLUSION

ADC and α were useful for assessing pCR after CRT. α might be more useful because it demonstrated better diagnostic performance than IVIM-derived parameters and better reliability than ADC.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:175-183.

Diffusion-weighted imaging outside the brain: Consensus statement from an ISMRM-sponsored workshop

The significant advances in magnetic resonance imaging (MRI) hardware and software, sequence design, and postprocessing methods have made diffusion-weighted imaging (DWI) an important part of body MRI protocols and have fueled extensive research on quantitative diffusion outside the brain, particularly in the oncologic setting. In this review, we summarize the most up-to-date information on DWI acquisition and clinical applications outside the brain, as discussed in an ISMRM-sponsored symposium held in April 2015. We first introduce recent advances in acquisition, processing, and quality control; then review scientific evidence in major organ systems; and finally describe future directions. J. Magn. Reson. Imaging 2016;44:521-540.