Prediction of high Ki-67 proliferation index of gastrointestinal stromal tumors based on CT at non-contrast-enhanced and different contrast-enhanced phases.

OBJECTIVES: To evaluate and analyze radiomics models based on non-contrast-enhanced computed tomography (CT) and different phases of contrast-enhanced CT in predicting Ki-67 proliferation index (PI) among patients with pathologically confirmed gastrointestinal stromal tumors (GISTs). METHODS: A total of 383 patients with pathologically proven GIST were divided into a training set (n = 218, vendor 1) and 2 validation sets (n = 96, vendor 2; n = 69, vendors 3-5). Radiomics features extracted from the most recent non-contrast-enhanced and three contrast-enhanced CT scan prior to pathological examination. Random forest models were trained for each phase to predict tumors with high Ki-67 proliferation index (Ki-67>10%) and were evaluated using the area under the receiver operating characteristic curve (AUC) and other metrics on the validation sets. RESULTS: Out of 107 radiomics features extracted from each phase of CT images, four were selected for analysis. The model trained using the non-contrast-enhanced phase achieved an AUC of 0.792 in the training set and 0.822 and 0.711 in the two validation sets, similar to models trained on different contrast-enhanced phases (p > 0.05). Several relevant features, including NGTDM Busyness and tumor size, remained predictive in non-contrast-enhanced and different contrast-enhanced images. CONCLUSION: The results of this study indicate that a radiomics model based on non-contrast-enhanced CT matches that of models based on different phases of contrast-enhanced CT in predicting the Ki-67 PI of GIST. GIST may exhibit similar radiological patterns irrespective of the use of contrast agent, and such radiomics features may help quantify these patterns to predict Ki-67 PI of GISTs. CLINICAL RELEVANCE STATEMENT: GIST may exhibit similar radiomics patterns irrespective of contrast agent; thus, radiomics models based on non-contrast-enhanced CT could be an alternative for risk stratification in GIST patients with contraindication to contrast agent. KEY POINTS: • Performance of radiomics models in predicting Ki-67 proliferation based on different CT phases is evaluated. • Non-contrast-enhanced CT-based radiomics models performed similarly to contrast-enhanced CT in risk stratification in GIST patients. • NGTDM Busyness remains stable to contrast agents in GISTs in radiomics models.

Cerebral hemodynamics in symptomatic anterior circulation intracranial stenosis measured by angiography-based quantitative flow ratio: association with CT perfusion.

OBJECTIVES: Cerebral hemodynamics is important for the management of intracranial atherosclerotic stenosis (ICAS). This study aimed to determine the utility of angiography-based quantitative flow ratio (QFR) to reflect cerebral hemodynamics in symptomatic anterior circulation ICAS by evaluating its association with CT perfusion (CTP). METHODS: Sixty-two patients with unilateral symptomatic stenosis in the intracranial internal carotid artery or middle cerebral artery who received percutaneous transluminal angioplasty (PTA) or PTA with stenting were included. Murray law-based QFR (µQFR) was computed from a single angiographic view. CTP parameters including cerebral blood flow, cerebral blood volume, mean transit time (MTT), and time to peak (TTP) were calculated, and relative values were obtained as the ratio between symptomatic and contralateral hemispheres. Relationships between µQFR and perfusion parameters, and between µQFR and perfusion response after intervention, were analyzed. RESULTS: Thirty-eight patients had improved perfusion after treatment. µQFR was significantly correlated with relative values of TTP and MTT, with correlation coefficients of -0.45 and -0.26, respectively, on a per-patient basis, and -0.72 and -0.43, respectively, on a per-vessel basis (all p < 0.05). Sensitivity and specificity for µQFR to diagnose hypoperfusion at a cut-off value of 0.82 were 94.1% and 92.1%, respectively. Multivariate analysis revealed that µQFRpost (adjusted odds ratio [OR], 1.48; p = 0.002), collateral score (adjusted OR, 6.97; p = 0.01), and current smoking status (adjusted OR, 0.03; p = 0.01) were independently associated with perfusion improvement after treatment. CONCLUSIONS: µQFR was associated with CTP in patients with symptomatic anterior circulation ICAS and may be a potential marker for real-time hemodynamic evaluation during interventional procedures. KEY POINTS: • Murray law-based QFR (µQFR) is associated with CT perfusion parameters in intracranial atherosclerotic stenosis and can differentiate hypoperfusion from normal perfusion. • Post-intervention µQFR, collateral score, and current smoking status are independent factors associated with improved perfusion after treatment.

Diagnostic performance of double inversion recovery MRI sequence for synovitis of the wrist joints in rheumatoid arthritis.

PURPOSE: To assess the diagnostic accuracy of double inversion recovery (DIR) magnetic resonance imaging (MRI) sequences for synovitis of the wrist joints in patients with rheumatoid arthritis (RA). MATERIAL AND METHODS: Participants with newly diagnosed RA were enrolled between November 2019 and November 2020. MRI examinations of the wrist joints were performed using a contrast-enhanced T1-weighted imaging sequence (CE-T1WI) and DIR sequence. We measured synovitis score, number of synovial areas, synovial volume, mean synovium-to-bone signal ratio (SBR), and synovial contrast-to-noise ratio (SNR). The inter-reviewer agreement rated on a four-point scale was evaluated by calculating the weighted k statistics. Two MRI sequences were assessed using Bland-Altman analyses, and the diagnostic performance of DIR images was calculated using the chi-square test. RESULTS: A total of 47 participants were evaluated, and 282 joint regions in 5076 images were reviewed by two readers. There was no significant difference in synovitis scores (P = 0.67), number of synovial areas (P = 0.89), and synovial volume (P = 0.086) between the two MRI sequences. DIR images showed better SBR and SNR (all P < 0.01). There was good agreement between the two reviewers in terms of synovitis distribution (κ = 0.79). The synovitis was well agreed upon by the two readers according to Bland-Altman analyses. Using CE-T1WI as the reference standard, DIR imaging demonstrated a sensitivity of 94.1% and a specificity of 84.6% at the patient level. CONCLUSION: The non-contrast DIR sequence showed good consistency with CE-T1WI and potential for evaluating synovitis in patients with RA.

Diffusion-weighted MRI for predicting pathologic response to neoadjuvant chemotherapy in breast cancer: evaluation with mono-, bi-, and stretched-exponential models.

BACKGROUND: To investigate the performance of diffusion-weighted (DW) MRI with mono-, bi- and stretched-exponential models in predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) for breast cancer, and further outline a predictive model of pCR combining DW MRI parameters, contrast-enhanced (CE) MRI findings, and/or clinical-pathologic variables. METHODS: In this retrospective study, 144 women who underwent NACT and subsequently received surgery for invasive breast cancer were included. Breast MRI including multi-b-value DW imaging was performed before (pre-treatment), after two cycles (mid-treatment), and after all four cycles (post-treatment) of NACT. Quantitative DW imaging parameters were computed according to the mono-exponential (apparent diffusion coefficient [ADC]), bi-exponential (pseudodiffusion coefficient and perfusion fraction), and stretched-exponential (distributed diffusion coefficient and intravoxel heterogeneity index) models. Tumor size and relative enhancement ratio of the tumor were measured on contrast-enhanced MRI at each time point. Pre-treatment parameters and changes in parameters at mid- and post-treatment relative to baseline were compared between pCR and non-pCR groups. Receiver operating characteristic analysis and multivariate regression analysis were performed. RESULTS: Of the 144 patients, 54 (37.5%) achieved pCR after NACT. Overall, among all DW and CE MRI measures, flow-insensitive ADC change (ΔADC200,1000) at mid-treatment showed the highest diagnostic performance for predicting pCR, with an area under the receiver operating characteristic curve (AUC) of 0.831 (95% confidence interval [CI]: 0.747, 0.915; P < 0.001). The model combining pre-treatment estrogen receptor and human epidermal growth factor receptor 2 statuses and mid-treatment ΔADC200,1000 improved the AUC to 0.905 (95% CI: 0.843, 0.966; P < 0.001). CONCLUSION: Mono-exponential flow-insensitive ADC change at mid-treatment was a predictor of pCR after NACT in breast cancer.

Blood oxygenation level-dependent cardiovascular magnetic resonance of the skeletal muscle in healthy adults: Different paradigms for provoking signal alterations.

PURPOSE: Stress blood oxygenation level-dependent (BOLD) cardiovascular magnetic resonance allows for quantitative evaluation of blood flow reserve in skeletal muscles. This study aimed to prospectively compare three commonly used skeletal BOLD cardiovascular magnetic resonance paradigms in healthy adults: gas inhalation, cuff compression-induced ischemia and postocclusive reactive hyperemia, and exercise. METHODS: Twelve young (22 ± 0.9 years) and 10 elderly (58 ± 5.0 years) healthy subjects underwent BOLD cardiovascular magnetic resonance under the three paradigms. T2∗ signal intensity time curves were generated and quantitative parameters were calculated. Meanwhile, stress transcutaneous oxygen pressure measurements were obtained as comparison. Measurement reproducibility was assessed with intraclass correlation coefficients. Differences in the T2∗ BOLD variation, the correlation with transcutaneous oxygen pressure, and the age-related change between paradigms were statistically analyzed. RESULTS: Minimum ischemic value and maximum hyperemic peak value showed the highest interobserver and interscan reproducibilities (intraclass correlation coefficient >0.90). The plantar dorsiflexion exercise paradigm elicited the largest T2∗ BOLD variation (15.48% ± 10.56%), followed by ischemia (8.30% ± 6.33%). Negligible to weak changes were observed during gas inhalation. Correlations with transcutaneous oxygen pressure measurements were found in the ischemic phase (r = 0.966; P < .001) and in the postexercise phase (r = -0.936; P < .001). Minimum ischemic value, maximum hyperemic peak value, maximum postexercise value, and slope of postexercise signal decay showed significant differences between young and elderly subjects (P < .01). CONCLUSION: Ischemia and reactive hyperemia have superior reproducibility, and exercise could induce the largest T2∗ variation. Key parameters from the two paradigms show age-related differences.

Diagnostic Utility of the Simplified Perfusion Fraction for Identifying Myocardial Injury in Patients With Reperfused ST-segment Elevation Myocardial Infarction.

BACKGROUND: Acute myocardial infarction (AMI) is a disease with high morbidity and mortality worldwide and the evaluation of myocardial injury and perfusion status following myocardial ischemia and reperfusion is of clinical value. PURPOSE: To assess the diagnostic utility of simplified perfusion fraction (SPF) in differentiating salvage and infarcted myocardium and its predictive value for left ventricular remodeling in patients with reperfusion ST-segment elevation myocardial infarction (STEMI). STUDY TYPE: Prospective. POPULATION: Forty-one reperfused STEMI patients and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: 3.0T MRI. The MR examination included cine, T2 -short tau inversion recovery (T2 -STIR), first pass perfusiong (FPP)，phase sensitive inversion recovery (PSIR), and diffusion-weighted imaging (DWI). ASSESSMENT: SPF values among different myocardium regions (infarcted, salvaged, remote, and MVO) and stages of reperfused STEMI patients as well as normal controls were measured. The diagnostic utility of SPF values in differentiating salvaged and infarcted myocardium was assessed. STATISTICAL ANALYSIS: Independent t-test and the Mann-Whitney U-test. Logistic regression. RESULTS: SPF values in healthy controls were not significantly different than SPF values in the remote myocardium of patients (40.09 ± 1.47% vs. 40.28 ± 1.93%, P = 0.698). In reperfusion STEMI patients, SPF values were lower in infarcted myocardium compared to remote and salvaged myocardium (32.15 ± 2.36% vs. 40.28 ± 1.93%, P < 0.001; 32.15 ± 2.36% vs. 36.68 ± 2.71%, P < 0.001). SPF values of infarcted myocardium showed a rebound increase from acute to convalescent stages (32.15 ± 2.36% vs. 34.69 ± 3.69%, P < 0.001). When differentiating infarcted and salvaged myocardium, SPF values demonstrated an area under the curve (AUC) of 0.89 (sensitivity 85.4%, specificity 80.5%, cutoff 34.42%). Lower SPF values were associated with lower odds ratio (OR = 0.304) of left ventricular remodeling after adjusting for potential confounders with a confidence interval (CI) of 0.129-0.717, P = 0.007. DATA CONCLUSION: SPF might be able to differentiate salvaged and infarcted myocardium and is a strong predictor of left ventricular remodeling in reperfused STEMI patients. Level of Evidence 2 Technical Efficacy Stage 2.

[Texture filtering based unsupervised registration methods and its application in liver computed tomography images].

Image registration is of great clinical importance in computer aided diagnosis and surgical planning of liver diseases. Deep learning-based registration methods endow liver computed tomography (CT) image registration with characteristics of real-time and high accuracy. However, existing methods in registering images with large displacement and deformation are faced with the challenge of the texture information variation of the registered image, resulting in subsequent erroneous image processing and clinical diagnosis. To this end, a novel unsupervised registration method based on the texture filtering is proposed in this paper to realize liver CT image registration. Firstly, the texture filtering algorithm based on L0 gradient minimization eliminates the texture information of liver surface in CT images, so that the registration process can only refer to the spatial structure information of two images for registration, thus solving the problem of texture variation. Then, we adopt the cascaded network to register images with large displacement and large deformation, and progressively align the fixed image with the moving one in the spatial structure. In addition, a new registration metric, the histogram correlation coefficient, is proposed to measure the degree of texture variation after registration. Experimental results show that our proposed method achieves high registration accuracy, effectively solves the problem of texture variation in the cascaded network, and improves the registration performance in terms of spatial structure correspondence and anti-folding capability. Therefore, our method helps to improve the performance of medical image registration, and make the registration safely and reliably applied in the computer-aided diagnosis and surgical planning of liver diseases.

Multiparameter diffusion-weighted imaging for characterizing pathological patterns in lupus nephritis patients: A preliminary study.

BACKGROUND: Microstructural changes of lupus nephritis (LN) kidney such as inflammatory cell infiltration or fibrosis could influence water molecular movement or diffusion, which indicates that diffusion-weighted imaging (DWI) may become a valuable tool in evaluation of this disease. PURPOSE: To explore whether multiparameter diffusion-weighted imaging (mDWI) could contribute to characterize pathological patterns in LN patients. STUDY TYPE: Retrospective. POPULATION: Twenty-two patients with LN. FIELD STRENGTH/SEQUENCE: Multi-b value DWI was performed with a 3.0 T scanner. ASSESSMENT: Apparent diffusion coefficient (ADC)m , perfusion-related diffusion coefficient (Df ), molecular diffusion coefficient (Ds ), perfusion fraction (f), ADCs , α, ADCk , and mean kurtosis (MK) were calculated by monoexponential, biexponential, stretched-exponential, and kurtosis models fits, respectively. STATISTICAL TESTS: Independent sample t-test, Pearson analysis and receiver operating characteristic (ROC). RESULTS: In the whole group, the activity index (AI) correlated significantly with alpha values in the medulla (rho = -0.54, P = 0.03). The chronicity index (CI) correlated significantly with Ds values in the medulla (rho = -0.61, P = 0.02). No significant association was found between any other diffusion parameter and histologic grade with all P > 0.05. For differentiating proliferative LN (Class III or IV) from Class V, the area under the ROC curve (AUC) of alpha in the medulla was 0.833 (P = 0.023). DATA CONCLUSION: mDWI might be used for the characterization of pathological patterns in LN patients. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1075-1084.

Brain T1ρ mapping for grading and IDH1 gene mutation detection of gliomas: a preliminary study.

INTRODUCTION: The longitudinal relaxation time in the rotating frame (T1ρ) has proved to be sensitive to metabolism and useful in application to neurodegenerative diseases. However, few literature exists on its utility in gliomas. Thus, this study was conducted to explore the performance of T1ρ mapping in tumor grading and characterization of isocitrate dehydrogenase 1 (IDH1) gene mutation status of gliomas. METHODS: Fifty-seven patients with gliomas underwent brain MRI and quantitative measurements of T1ρ and apparent diffusion coefficient (ADC) were recorded. Parameters were compared between high-grade gliomas (HGG) and low-grade gliomas (LGG) and between IDH1 mutant and wildtype groups. RESULTS: HGG showed significantly higher T1ρ values in both the solid and peritumoral edema areas compared with LGG (P < 0.001 and P = 0.005, respectively), whereas no significant differences in the two areas were found for ADC (both P > 0.05). Receiver operating characteristic (ROC) curve analysis showed that T1ρ value in the solid area achieved the highest area under the ROC curve (AUC, 0.841) in grading with a sensitivity of 80.6% and a specificity of 81.0%. In the grade II/III glioma group, multivariate logistic regression showed that both tumor frontal lobe location (odds ratio [OR] 526.608; P = 0.045) and T1ρ value of the peritumoral edema area (OR 0.863; P = 0.037) were significant predictors of IDH1 mutation. Using the combination, the diagnostic sensitivity and specificity for IDH1 mutated gliomas were 93.3% and 88.9%, respectively. CONCLUSIONS: Our study shows the feasibility of applying T1ρ mapping in assessing the histologic grade and IDH1 mutation status of gliomas.

Added value of mean and entropy of apparent diffusion coefficient values for evaluating histologic phenotypes of invasive ductal breast cancer with MR imaging.

OBJECTIVES: To study the added value of mean and entropy of apparent diffusion coefficient (ADC) values at standard (800 s/mm2) and high (1500 s/mm2) b-values obtained with diffusion-weighted imaging in identifying histologic phenotypes of invasive ductal breast cancer (IDC) with MR imaging. METHODS: One hundred thirty-four IDC patients underwent diffusion-weighted imaging with b-values of 800 and 1500 s/mm2, and corresponding ADC800 and ADC1500 maps were generated. Mean and entropy of volumetric ADC values were compared with molecular markers (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67). Associations among morphologic features, ADC metrics, and phenotypes (luminal A, luminal B [HER2 negative], luminal B [HER2 positive], HER2 positive, and triple negative) were evaluated. RESULTS: Mean ADC values were significantly decreased in ER-positive, PR-positive, and HER2-negative tumors (p < 0.01). Ki-67 ≥ 20% tumors demonstrated significantly higher ADC entropy values compared with Ki-67 < 20% tumors (p < 0.001). Luminal A subtype tended to display lower ADC entropy values compared with other subtypes, while HER2-positive subtype tended to display higher mean ADC values. ADC1500 entropy provided superior diagnostic performance over ADC800 entropy (p = 0.04). Independent risk factors were ADC1500 entropy (p = 0.002) associated with luminal A, irregular mass shape (p = 0.018) and ADC1500 entropy (p = 0.022) with luminal B (HER2 positive), mean ADC1500 (p = 0.018) with HER2 positive, and smooth mass margin (p = 0.012) and rim enhancement (p = 0.003) with triple negative. CONCLUSIONS: Mean and entropy of ADC values provided complementary information and added value for evaluating IDC histologic phenotypes. High-b-value ADC1500 may facilitate better phenotype discrimination. KEY POINTS: • ADC metrics are associated with molecular marker status in IDC. • ADC 1500 improves differentiation of histologic phenotypes compared with ADC 800 . • ADC metrics add value to morphologic features in IDC phenotyping.

[New Model for Intelligent Imaging Screening of Pulmonary Nodules].

The artificial intelligence based on medical aid diagnosis has been in full swing in these years. How to better and more safely utilize this new technology to improve the diagnostic efficiency and quality of doctors poses new challenges for our hospital management. This paper aims to explore relevant management problems and corresponding solutions from seven aspects:data security, system integration, technical parameters, risks, workflows and diagnosis results by introducing a new intelligent image screening system. After these management problems have been better solved, we found that the intelligent image screening system can improve the diagnostic efficiency and quality of doctors.

Evaluation of skeletal muscle microvascular perfusion of lower extremities by cardiovascular magnetic resonance arterial spin labeling, blood oxygenation level-dependent, and intravoxel incoherent motion techniques.

BACKGROUND: Noninvasive cardiovascular magnetic resonance (CMR) techniques including arterial spin labeling (ASL), blood oxygenation level-dependent (BOLD), and intravoxel incoherent motion (IVIM), are capable of measuring tissue perfusion-related parameters. We sought to evaluate and compare these three CMR techniques in characterizing skeletal muscle perfusion in lower extremities and to investigate their abilities to diagnose and assess the severity of peripheral arterial disease (PAD). METHODS: Fifteen healthy young subjects, 14 patients with PAD, and 10 age-matched healthy old subjects underwent ASL, BOLD, and IVIM CMR perfusion imaging. Healthy young and healthy old participants were subjected to a cuff-induced ischemia experiment with pressures of 20 mmHg and 40 mmHg above systolic pressure during imaging. Perfusion-related metrics, including blood flow, T2* relaxation time, perfusion fraction f, diffusion coefficient D, and pseudodiffusion coefficient D*, were measured in the anterior, lateral, soleus, and gastrocnemius muscle groups. Friedman, Mann-Whitney, Wilcoxon signed rank, and Spearman rank correlation tests were used for statistical analysis. RESULTS: In cases of significant differences determined by the Friedman test (P < 0.05), blood flow, T2*, and D values gradually decreased, while f values showed a tendency to increase in healthy subjects under cuff compression. No significant correlations were found among the ASL, BOLD, and IVIM parameters (all P > 0.05). Blood flow and T2* values showed significant positive correlations with transcutaneous oxygen pressure measurements (ρ = 0.465 and 0.522, respectively; both P ≤ 0.001), while f values showed a significant negative correlation in healthy young subjects (ρ = - 0.351; P = 0.018). T2* was independent of age in every muscle group. T2* values were significantly decreased in PAD patients compared with healthy old subjects and severe PAD patients compared with mild-to-moderate PAD patients (all P < 0.0125). Significant correlations were found between T2* and ankle-brachial index values in all muscle groups in PAD patients (ρ = 0.644-0.837; all P < 0.0125). Other imaging parameters failed to show benefits towards the diagnosis and disease severity evaluation of PAD. CONCLUSIONS: ASL, BOLD, and IVIM provide complementary information regarding tissue perfusion. Compared with ASL and IVIM, BOLD may be a more reliable technique for assessing PAD in the resting state and could thus be applied together with angiography in clinical studies as a tool to comprehensively assess microvascular and macrovascular properties in PAD patients.

Apparent diffusion coefficient measurement in glioma: Influence of region-of-interest determination methods on apparent diffusion coefficient values, interobserver variability, time efficiency, and diagnostic ability.

PURPOSE: To compare four methods of region-of-interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in distinguishing low-grade gliomas (LGGs) from high-grade gliomas (HGGs). MATERIALS AND METHODS: Two independent readers measured ADC parameters using four ROI methods (single-slice [single-round, five-round and freehand] and whole-volume) on 43 patients (20 LGGs, 23 HGGs) who had undergone 3.0 Tesla diffusion-weighted imaging and time required for each method of ADC measurements was recorded. Intraclass correlation coefficients (ICCs) were used to assess interobserver variability of ADC measurements. Mean and minimum ADC values and time required were compared using paired Student's t-tests. All ADC parameters (mean/minimum ADC values of three single-slice methods, mean/minimum/standard deviation/skewness/kurtosis/the10th and 25th percentiles/median/maximum of whole-volume method) were correlated with tumor grade (low versus high) by unpaired Student's t-tests. Discriminative ability was determined by receiver operating characteristic curves. RESULTS: All ADC measurements except minimum, skewness, and kurtosis of whole-volume ROI differed significantly between LGGs and HGGs (all P < 0.05). Mean ADC value of single-round ROI had the highest effect size (0.72) and the greatest areas under the curve (0.872). Three single-slice methods had good to excellent ICCs (0.67-0.89) and the whole-volume method fair to excellent ICCs (0.32-0.96). Minimum ADC values differed significantly between whole-volume and single-round ROI (P = 0.003) and, between whole-volume and five-round ROI (P = 0.001). The whole-volume method took significantly longer than all single-slice methods (all P < 0.001). CONCLUSION: ADC measurements are influenced by ROI determination methods. Whole-volume histogram analysis did not yield better results than single-slice methods and took longer. Mean ADC value derived from single-round ROI is the most optimal parameter for differentiating LGGs from HGGs. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:722-730.

Multiparametric diffusion-weighted imaging in breast lesions: Association with pathologic diagnosis and prognostic factors.

PURPOSE: To determine the utility of multiparametric diffusion-weighted imaging (DWI) including monoexponential (apparent diffusion coefficient [ADC]), biexponential (Df , Ds , and f), stretched-exponential (distributed diffusion coefficient [DDC] and α), and kurtosis (mean diffusivity [MD] and mean kurtosis [MK]) models in the differentiation and characterization of breast lesions, and assess their associations with prognostic factors in invasive breast cancer. MATERIALS AND METHODS: This study included 101 patients (44 benign and 57 malignant lesions) who underwent 3T breast multi-b-value DWI. Diffusion model selection was investigated in benign and malignant lesions using the Akaike information criteria (AIC). Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for statistical analysis. RESULTS: Goodness-of-fit analysis showed that most benign lesion voxels (50.5%) were preferred by the kurtosis model, and most malignant lesion voxels (51.2%) by the stretched-exponential model. All diffusion measures showed significant differences between benign and malignant lesions (P < 0.05), and between in situ and invasive cancers (P < 0.05) except MD (P = 0.103). There were no significant differences in areas under the ROC curves (AUCs) between ADC and non-monoexponential diffusion parameters (P > 0.05), except Df and α, whose AUCs were significantly lower than AUC of ADC for differentiating benign from malignant lesions (P = 0.03 and P < 0.01, respectively). In patients with invasive breast cancer, α was significantly correlated with tumor size (P = 0.007) and Ki-67 expression (P = 0.012), Df was significantly correlated with lymph node metastasis (P = 0.021) and Ki-67 expression (P = 0.042), and ADC, Ds , f, DDC, and MD were significantly correlated with estrogen receptor status (all P < 0.05). CONCLUSION: Multiparametric DWI shows relationships with pathologic outcomes and prognostic factors of breast lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:740-750.

Evaluation of carotid plaque vulnerability in vivo: Correlation between dynamic contrast-enhanced MRI and MRI-modified AHA classification.

PURPOSE: To noninvasively monitor carotid plaque vulnerability by exploring the relationship between pharmacokinetic parameters (PPs) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and plaque types based on MRI-modified American Heart Association (AHA) classification, as well as to assess the ability of PPs in discrimination between stable and vulnerable plaques suspected on MRI. MATERIALS AND METHODS: Of 70 consecutive patients with carotid plaques who volunteered for 3.0T MRI (3D time-of-flight [TOF], T1 -weighted, T2 -weighted, 3D magnetization-prepared rapid acquisition gradient-echo [MP-RAGE] and DCE-MRI), 66 participants were available for analysis. After plaque classification according to MRI-modified AHA Lesion-Type (LT), PPs (Ktrans , kep , ve , and vp ) of DCE-MRI were measured. The Extended Tofts model was used for calculation of PPs. For participants with multiple carotid plaques, the plaque with the worst MRI-modified AHA LT was chosen for analysis. Correlations between PPs and plaque types and the ability of these parameters to distinguish stable and vulnerable plaques suspected on MRI were assessed. RESULTS: Significant positive correlation between Ktrans and LT III to VI was found (ρ = 0.532, P < 0.001), as was the correlation between kep and LT III to VI (ρ = 0.409, P < 0.001). Stable and vulnerable plaques suspected on MRI could potentially be distinguished by Ktrans (sensitivity 83%, specificity 100%) and kep (sensitivity 77%, specificity 91%). CONCLUSION: Ktrans and kep from DCE-MRI can provide quantitative information to monitor plaque vulnerability in vivo and differentiate vulnerable plaques suspected on MRI from stable ones. These two parameters could be adopted as imaging biomarkers for plaque characterization and risk stratification. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:870-876.

Assessment of response to anti-angiogenic targeted therapy in pulmonary metastatic renal cell carcinoma: R2* value as a predictive biomarker.

PURPOSE: To evaluate the utility of MR R2*-mapping and the optimal time-point for assessing the response of pulmonary metastatic renal cell carcinoma (mRCC) to anti-angiogenic targeted therapy (aATT). MATERIALS AND METHODS: The exploration-sample group and the validation-sample group consisted of 22 and 16 patients. The parameters of MR R2*-mapping, including the R2* value at each time-point (R2*base, R2*1cyc and R2*2cyc) and change between different time-points (R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc), were evaluated with a receiver-operating-characteristic analysis, and a cut-off value derived from the clinical outcome was applied to the Kaplan-Meier method to assess the value of R2* mapping and Response-Evaluation-Criteria in Solid Tumours (RECIST) during treatment evaluation. RESULTS: The inter-, intra-observer agreements and inter-scan consistency were excellent (p > 0.80). For the exploration-sample group, the areas under the curve for the parameters of MR R2* mapping were 0.55, 0.60, 0.83, 0.64, 0.88 and 0.83 for R2*base, R2*1cyc, R2*2cyc, R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc. For the validation-sample, R2*(2cyc-base)/base better predicted progression-free survival (p = 0.03) than RECIST and other R2* mapping parameters with a lower p value. CONCLUSION: Assessing aATT outcome based on changes in the R2* value between baseline and second treatment is more accurate than assessment at other time-points and assessment based on the RECIST. KEY POINTS: • The inter-scan consistency of R2*-mapping in pulmonary mRCC are excellent. • The intra-/inter-observer agreement of R2* mapping in pulmonary mRCC are excellent. • Using changes in R2* value between baseline/after second-treatment is better than RECIST. • The choice of baseline/after second treatment is better than other time-points.

Preliminary study of diffusion kurtosis imaging in thyroid nodules and its histopathologic correlation.

OBJECTIVES: To evaluate the utility of diffusion kurtosis imaging (DKI) of patients with thyroid nodules and to assess the probable correlation with histopathological factors. METHODS: The study included 58 consecutive patients with thyroid nodules who underwent magnetic resonance imaging (MRI) examination, including DKI and diffusion-weighted imaging (DWI). Histopathological analysis of paraffin sections included cell density and immunohistochemical analysis of Ki-67 and vascular endothelial growth factor (VEGF). Statistical analyses were performed using Student's t-test, receiver operating characteristic (ROC) curves and Spearman's correlation. RESULTS: The diffusion parameters, cell density and immunohistochemistry analysis between malignant and benign lesions showed significant differences. The largest area under the ROC curve was acquired for the D value (AUC = 0.797). The highest sensitivity was shown with the use of K (threshold = 0.832, sensitivity = 0.917). The Ki-67 expression generally stayed low. A moderate correlation was found between ADC, D and cell density (r = -0.536, P = 0.000; r = -0.570, P = 0.000) and ADC, D and VEGF expression (r = -0.451, P = 0.000; r = -0.522, P = 0.000). CONCLUSION: The DKI-derived parameters D and K demonstrated an advantage compared to conventional DWI for thyroid lesion diagnosis. While the histopathological study indicated that the D value correlated better with extracellular change than the ADC value, the K value probably changed relative to the intracellular structure. KEY POINTS: • DWI and DKI parameters can identify PTC from benign thyroid nodules. • Correlations were found between diffusion parameters and histopathological analysis. • DKI obtains better diagnostic accuracy than conventional DWI.

Stroke assessment with intravoxel incoherent motion diffusion-weighted MRI.

Intravoxel incoherent motion (IVIM) diffusion-weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non-invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi-b-value diffusion-weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b-values to a simple mono-exponential model. The IVIM-derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow-related parameter fD*, were calculated with the bi-exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono-exponential model using all b-values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t-test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi-exponential behavior, and the IVIM model showed better goodness of fit than the mono-exponential model with lower Akaike information criterion values. The paired Student t-test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.

Characterization of breast masses as benign or malignant at 3.0T MRI with whole-lesion histogram analysis of the apparent diffusion coefficient.

PURPOSE: To investigate the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in capturing breast lesion heterogeneity and determine which ADC metric may help best differentiate benign from malignant breast mass lesions at 3.0T magnetic resonance imaging (MRI). MATERIALS AND METHODS: We retrospectively included 101 women with breast mass lesions (benign:malignant = 36:65) who underwent 3.0T diffusion-weighted imaging (DWI) and subsequently had histopathologic confirmation. ADC histogram parameters, including the mean, minimum, maximum, 10th/25th/50th/75th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, univariate and multivariate logistic regression, area under the receiver-operating characteristic curve (Az ), intraclass correlation coefficient (ICC), and Bland-Altman test were used for statistical analysis. RESULTS: Mean, minimum, maximum, and 10th/25th/50th/75th/90th percentile ADCs were significantly lower (all P < 0.0001), while skewness and entropy ADCs were significantly higher (P < 0.001 and P = 0.001, respectively) in malignant lesions compared with benign ones. The Az values of minimum and 25th percentile ADCs were significantly higher than that of mean ADC (P = 0.0194 and P = 0.0154, respectively) or that of median ADC (P = 0.0300 and P = 0.0401, respectively), indicating that minimum and 25th percentile ADCs may be more accurate for lesion discrimination. Multivariate logistic regression showed that the minimum ADC was the unique independent predictor of breast malignancy. Minimum and 25th percentile ADCs had excellent interobserver agreement (ICC = 0.943 and 0.989, respectively; narrow width of 95% limits of agreement). CONCLUSION: These results suggest that whole-lesion ADC histogram analysis may facilitate the differentiation between benign and malignant breast mass lesions.