Monitoring early response to anti-angiogenic therapy: diffusion-weighted magnetic resonance imaging and volume measurements in colon carcinoma xenografts.
ABSTRACT: OBJECTIVES: To evaluate the use of diffusion-weighted MRI (DW-MRI) and volume measurements for early monitoring of antiangiogenic therapy in an experimental tumor model. MATERIALS AND METHODS: 23 athymic nude rats, bearing human colon carcinoma xenografts (HT-29) were examined before and after 6 days of treatment with regorafenib (n?=?12) or placebo (n?=?11) in a clinical 3-Tesla MRI. For DW-MRI, a single-shot EPI sequence with 9 b-values (10-800 s/mm2) was used. The apparent diffusion coefficient (ADC) was calculated voxelwise and its median value over a region of interest, covering the entire tumor, was defined as the tumor ADC. Tumor volume was determined using T2-weighted images. ADC and volume changes between first and second measurement were evaluated as classifiers by a receiver-operator-characteristic (ROC) analysis individually and combined using Fisher's linear discriminant analysis (FLDA). RESULTS: All ADCs and volumes are stated as median±standard deviation. Tumor ADC increased significantly in the therapy group (0.76±0.09×10(-3) mm2/s to 0.90±0.12×10(-3) mm2/s; p<0.001), with significantly higher changes of tumor ADC than in the control group (0.10±0.11×10(-3) mm2/s vs. 0.03±0.09×10(-3) mm2/s; p?=?0.027). Tumor volume increased significantly in both groups (therapy: 347.8±449.1 to 405.3±823.6 mm3; p?=?0.034; control: 219.7±79.5 to 443.7±141.5 mm3; p<0.001), however, the therapy group showed significantly reduced tumor growth (33.30±47.30% vs. 96.43±31.66%; p<0.001). Area under the curve and accuracy of the ADC-based ROC analysis were 0.773 and 78.3%; and for the volume change 0.886 and 82.6%. The FLDA approach yielded an AUC of 0.985 and an accuracy of 95.7%. CONCLUSIONS: Regorafenib therapy significantly increased tumor ADC after 6 days of treatment and also significantly reduced tumor growth. However, ROC analyses using each parameter individually revealed a lack of accuracy in discriminating between therapy and control group. The combination of both parameters using FLDA substantially improved diagnostic accuracy, thus highlighting the potential of multi-parameter MRI as an imaging biomarker for non-invasive early tumor therapy monitoring.
Project description:BACKGROUND:Available data proving the value of DWI for breast cancer diagnosis is mainly for enhancing masses; DWI may be less sensitive and specific in non-mass enhancement (NME) lesions. The objective of this study was to assess the diagnostic accuracy of DWI using different ROI measurement approaches and ADC metrics in breast lesions presenting as NME lesions on dynamic contrast-enhanced (DCE) MRI. METHODS:In this retrospective study, 95 patients who underwent multiparametric MRI with DCE and DWI from September 2007 to July 2013 and who were diagnosed with a suspicious NME (BI-RADS 4/5) were included. Twenty-nine patients were excluded for lesion non-visibility on DWI (n?=?24: 12 benign and 12 malignant) and poor DWI quality (n?=?5: 1 benign and 4 malignant). Two readers independently assessed DWI and DCE-MRI findings in two separate randomized readings using different ADC metrics and ROI approaches. NME lesions were classified as either benign (>?1.3?×?10-3?mm2/s) or malignant (??1.3?×?10-3?mm2/s). Histopathology was the standard of reference. ROC curves were plotted, and AUCs were determined. Concordance correlation coefficient (CCC) was measured. RESULTS:There were 39 malignant (59%) and 27 benign (41%) lesions in 66 (65 women, 1 man) patients (mean age, 51.8?years). The mean ADC value of the darkest part of the tumor (Dptu) achieved the highest diagnostic accuracy, with AUCs of up to 0.71. Inter-reader agreement was highest with Dptu ADC max (CCC 0.42) and lowest with the point tumor (Ptu) ADC min (CCC?=?-?0.01). Intra-reader agreement was highest with Wtu ADC mean (CCC?=?0.44 for reader 1, 0.41 for reader 2), but this was not associated with the highest diagnostic accuracy. CONCLUSIONS:Diagnostic accuracy of DWI with ADC mapping is limited in NME lesions. Thirty-one percent of lesions presenting as NME on DCE-MRI could not be evaluated with DWI, and therefore, DCE-MRI remains indispensable. Best results were achieved using Dptu 2D ROI measurement and ADC mean.
Project description:BACKGROUND:To evaluate the utility of non-invasive parameters derived from T1 mapping and diffusion-weighted imaging (DWI) on gadoxetic acid-enhanced MRI for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS:A total of 94 patients with single HCC undergoing partial hepatectomy was analyzed in this retrospective study. Preoperative T1 mapping and DWI on gadoxetic acid-enhanced MRI was performed. The parameters including precontrast, postcontrast and reduction rate of T1 relaxation time and apparent diffusion coefficient (ADC) values were measured for differentiating MVI-positive HCCs (n?=?38) from MVI-negative HCCs (n?=?56). The receiver operating characteristic curve (ROC) was analyzed to compare the diagnostic performance of the calculated parameters. RESULTS:MVI-positive HCCs demonstrated a significantly lower reduction rate of T1 relaxation time than that of MVI-negative HCCs (39.4% vs 49.9, P?<?0.001). The areas under receiver operating characteristic curve (AUC) were 0.587, 0.728, 0.824, 0,690 and 0.862 for the precontrast, postcontrast, reduction rate of T1 relaxation time, ADC and the combination of reduction rate and ADC, respectively. The cut-off value of the reduction rate and ADC calculated through maximal Youden index in ROC analyses was 44.9% and 1553.5?s/mm2. To achieve a better diagnostic performance, the criteria of combining the reduction rate lower than 44.9% and the ADC value lower than 1553.5?s/mm2 was proposed with a high specificity of 91.8% and accuracy of 80.9%. CONCLUSIONS:The proposed criteria of combining the reduction rate of T1 relaxation time lower than 44.9% and the ADC value lower than 1553.5?s/mm2 on gadoxetic acid-enhanced MRI holds promise for evaluating MVI status of HCC.
Project description:PURPOSE:To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally advanced rectal cancer (LARC) using radiomics and deep learning based on pre-treatment MRI and a mid-radiation follow-up MRI taken 3-4?weeks after the start of CRT. METHODS:A total of 51 patients were included, 45 with pre-treatment, 41 with mid-radiation therapy (RT), and 35 with both MRI sets. The multi-parametric MRI protocol included T2, diffusion weighted imaging (DWI) with b-values of 0 and 800?s/mm2, and dynamic-contrast-enhanced (DCE) MRI. After completing CRT and surgery, the specimen was examined to determine the pathological response based on the tumor regression grade. The tumor ROI was manually drawn on the post-contrast image and mapped to other sequences. The total tumor volume and mean apparent diffusion coefficient (ADC) were measured. Radiomics using GLCM texture and histogram parameters, and deep learning using a convolutional neural network (CNN), were performed to differentiate pathologic complete response (pCR) vs. non-pCR, and good response (GR) vs. non-GR. RESULTS:Tumor volume decreased and ADC increased significantly in the mid-RT MRI compared to the pre-treatment MRI. For predicting pCR vs. non-pCR, combining ROI and radiomics features achieved an AUC of 0.80 for pre-treatment, 0.82 for mid-RT, and 0.86 for both MRI together. For predicting GR vs. non-GR, the AUC was 0.91 for pre-treatment, 0.92 for mid-RT, and 0.93 for both MRI together. In deep learning using CNN, combining pre-treatment and mid-RT MRI achieved a higher accuracy compared to using either dataset alone, with AUC of 0.83 for predicting pCR vs. non-pCR. CONCLUSION:Radiomics based on pre-treatment and early follow-up multi-parametric MRI in LARC patients receiving CRT could extract comprehensive quantitative information to predict final pathologic response.
Project description:BACKGROUND:To determine the usefulness of Diffusion Weighted Imaging (DWI) derived from PET/MRI in discriminating normal from metastatic lymph nodes and the correlation between the metastatic lymph nodes with the grade and the localization of the primary tumor. METHODS:Retrospective study of 90 lymph nodes from 90 subjects; 65 patients who had proven histopathological metastatic lymph nodes from (HNSCC) who had undergone 18F- PET/MRI for clinical staging and assessment and twenty-five lymph nodes were chosen from 25 healthy subjects. Apparent Diffusion Coefficient (ADC) map was generated from DWI with b values (0 and 800?s/mm2). ADC values of the metastatic lymph nodes were calculated and compared to the normal lymph nodes ADC values, ROC was used to determine the best cut-off values to differentiate between the two group. Metastatic lymph nodes ADC mean values were compared to primary tumor grade and localization. RESULTS:ADCmean value of the metastatic lymph nodes in the overall sample (0.899?±?0.98*10-?3?mm2/sec) was significantly lower than the normal lymph nodes' ADCmean value (1.267?±?0.88*10-?3?mm2/sec); (P?=?0.001). The area under the curve (AUC) was 98.3%, sensitivity and specificity were 92.3 and 98.6%, respectively, when using a threshold value of (1.138?±?0.75*10-?3?mm2/sec) to differentiate between both groups. Significant difference was found between metastatic lymph nodes (short-axis diameter?<?10?mm), ADCmean (0.898?±?0.72*10-?3?mm2/sec), and the benign lymph nodes ADCmean, (P?=?0.001). No significant difference was found between ADCmean of the metastatic lymph nodes <?10?mm and the metastatic lymph nodes >?10?mm, ADCmean (0.899?±?0.89*10-?3?mm2/sec), (P?=?0.967). No significant differences were found between metastatic lymph nodes ADCmean values and different primary tumor grades or different primary tumor localization, (P >?0.05). CONCLUSION:DWI-ADC is an effective and efficient imaging technique in differentiating between normal and malignant lymph nodes, and might be helpful to discriminate sub-centimeters lymph nodes. TRIAL REGISTRATION:The trial is registered in clinical trials under ID: NCT04360993 , registration date: 17/04/2020.
Project description:Diffusion weighted imaging (DWI) has proven to be sensitive for detecting early injury to the parotid gland in pSS (primary Sjögren's syndrome). Here, we explored the application of ADC histogram and texture analyses for evaluating the disease activity of pSS. A total of 55 patients with pSS who met the classification criteria of the 2002 AECG criteria prospectively underwent 3.0-T magnetic resonance imaging (MRI) including DWI (b?=?0 and 1000?s/mm2). According to the ESSDAI score, 35 patients were categorized into the low-activity group (ESSDAI?<?5) and 20 into the moderate-high-activity group (ESSDAI???5). Via analysis of the whole-volume ADC histogram, the ADCmean, skewness, kurtosis, and entropy values of the bilateral parotid glands were determined. Multivariate analysis was used to identify independent risk factors for predicting disease activity. The diagnostic performance of the indexes was evaluated via receiver operating characteristic (ROC) analysis. ROC analysis showed that the anti-SSB, lip biopsy, MRI morphology, ADC, ADCmean, and entropy values were able to categorize the disease into two groups, particularly the entropy values. The multivariate model, which included anti-SSB, MRI morphology and entropy, had an area under the ROC curve of 0.923 (P?<?0.001). The parotid entropy value distinguished disease activity in patients with pSS, especially combined with anti-SSB and MRI morphology.
Project description:Pediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion-weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis.To assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions.Retrospective.Forty-two pediatric patients with abdominal lesions (n?=?32 malignant, n?=?10 benign), verified by histopathology.1.5T MRI system and a DW-MRI sequence with six b-values (0, 50, 100, 150, 600, 1000 s/mm2 ).Parameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole-tumor regions of each parameter.Comparison of histogram parameters of and their diagnostic performance was determined using Kruskal-Wallis, Mann-Whitney U, and receiver-operating characteristic (ROC) analysis.IVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90th percentile (area under the curve [AUC]?=?0.935; P?=?0.002; cutoff value?=?32,376 × 10-6 mm2 /s) and f mean values (AUC?=?1.00; P < 0.001; cutoff value?=?14.7) in discriminating between neuroblastoma (n?=?11) and Wilms' tumors (n?=?8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05).IVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis.4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1475-1486.
Project description:<h4>Introduction and aim</h4>It is difficult to distinguish between non-functioning pituitary macroadenomas (NFPMAs) and sellar meningiomas because of their overlapping imaging manifestations on routine MRI, especially in cases of meningiomas growing into the saddle. Here, we aimed to differentiate between these two tumors using apparent diffusion coefficient (ADC) values and MRI characteristics.<h4>Methods</h4>A total of 60 NFPMA and 52 sellar meningioma cases confirmed by the pathological analysis were retrospectively reviewed. All patients were examined via routine MRI and diffusion-weighted imaging (DWI) before undergoing surgery. The clinical characteristics, MRI characteristics, and max ADC (ADCmax), average ADC (ADCmean), and minimum ADC (ADCmin) values were compared between the two tumors via Chi-square test and two sample t-tests. Receiver operating characteristic (ROC) curve and binary logistic regression analyses were conducted to determine the discrimination ability.<h4>Results</h4>The ADCmax, ADCmean, and ADCmin values were significantly higher in NFPMAs compared to sellar meningiomas (P < 0.001 for all). Among ADC values, ADCmax demonstrated good performance with an AUC of 0.896 (95% CI, 0.823-0.969) and accuracy of 88.7%. A cut-off value of 0.97 × 10-3 mm2/s was used for ADCmax for differentiation between tumors. A combination of ADCmax values and clinicoradiological features showed the best discrimination ability for differential diagnosis between the two tumors, with an AUC of 0.981 (95% CI, 0.958-1.000) and accuracy of 96.9%.<h4>Conclusion</h4>A combination of ADCmax and clinicoradiological features demonstrates good discrimination ability and high accuracy for differentiation between NFPMAs and sellar meningiomas, and is a potential quantitative tool to aid in the selection of surgical techniques.
Project description:The clinical value of MR diffusion tensor imaging (DTI) in grade diagnosis of gliomas was investigated. A total of 31 patients with glioma were administered 3.0T MR convention and DTI examination, with quantitative measurement of anisotropy coefficient fractional anisotropy (FA) and apparent dispersion coefficient (ADC) value, and the comparison of quantitative parameters of glioma between low- and high-grade, which was detected by Mann-Whitney U test. The receiver operation characteristic (ROC) curve was drawn to take the value of ADC and FA in tumor ROI as a critical point, to calculate the area under the curve and to confirm the diagnosis threshold value and evaluate its diagnostic efficiency. The FA value of 14 low-grade glioma cases was 139.4±81.3, with an ADC value of (1.36±0.21) ×10-3 mm2/sec. The FA value of 17 high-grade glioma cases was 103.1±41.5, with ADC value of (1.09±0.28)-3 mm2/sec; the difference between the two groups was statistically significant (P<0.05). The ADC value was taken as the critical point to judge tumor grade and draw the ROC curve; the area under the curve was 0.79. As the diagnosis threshold value, the ADC value of 1.11×10-3 mm2/sec was used to distinguish between low- and high-grade tumor with a sensitivity of 58.8% and specificity of 92.9%. The FA value was taken as a critical point to judge tumor grade and draw the ROC curve; the area under the curve was 0.62. As the diagnosis threshold value, the FA value of 178.9 was applied to distinguish between low- and high-grade tumor sensitivity of 94.1% and specificity of 35.7%. Therefore, the FA value and ADC value in DTI has an important estimated value for the pathological grade of glioma.
Project description:PURPOSE:Conventional breast MRI is highly sensitive for cancer detection but prompts some false positives. We performed a prospective, multicenter study to determine whether apparent diffusion coefficients (ADCs) from diffusion-weighted imaging (DWI) can decrease MRI false positives.Experimental Design: A total of 107 women with MRI-detected BI-RADS 3, 4, or 5 lesions were enrolled from March 2014 to April 2015. ADCs were measured both centrally and at participating sites. ROC analysis was employed to assess diagnostic performance of centrally measured ADCs and identify optimal ADC thresholds to reduce unnecessary biopsies. Lesion reference standard was based on either definitive biopsy result or at least 337 days of follow-up after the initial MRI procedure. RESULTS:Of 107 women enrolled, 67 patients (median age 49, range 24-75 years) with 81 lesions with confirmed reference standard (28 malignant, 53 benign) and evaluable DWI were analyzed. Sixty-seven of 81 lesions were BI-RADS 4 (n = 63) or 5 (n = 4) and recommended for biopsy. Malignancies exhibited lower mean in centrally measured ADCs (mm2/s) than benign lesions [1.21 × 10-3 vs.1.47 × 10-3; P < 0.0001; area under ROC curve = 0.75; 95% confidence interval (CI) 0.65-0.84]. In centralized analysis, application of an ADC threshold (1.53 × 10-3 mm2/s) lowered the biopsy rate by 20.9% (14/67; 95% CI, 11.2%-31.2%) without affecting sensitivity. Application of a more conservative threshold (1.68 × 10-3 mm2/s) to site-measured ADCs reduced the biopsy rate by 26.2% (16/61) but missed three cancers. CONCLUSIONS:DWI can reclassify a substantial fraction of suspicious breast MRI findings as benign and thereby decrease unnecessary biopsies. ADC thresholds identified in this trial should be validated in future phase III studies.
Project description:BACKGROUND:Routine screening of prostate specific antigen (PSA) is no longer recommended because of a high rate of over-diagnosis of prostate cancer (PCa). OBJECTIVE:To evaluate the efficacy of diffusion-weighted magnetic resonance imaging (DW-MRI) for PCa detection, and to explore the clinical utility of ultrahigh b-value DW-MRI in predicting prostate biopsy outcomes. METHODOLOGY:73 male patients were selected for the study. They underwent 3T MRI using T2WI conventional DW-MRI with b-value 1000 s/mm2, and ultrahigh b-value DW-MRI with b-values of 2000 s/mm2 and 3000 s/mm2. Two radiologists evaluated individual prostate gland images on a 5-point rating scale using PI-RADS, for the purpose of region-specific comparisons among modalities. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratios (LR) were investigated for each MRI modality. The area under the receiver operating characteristic (ROC) curve (AUC) was also calculated. RESULTS:Results showed the improved diagnostic value of ultrahigh b-value DWI-MRI for detection of PCa when compared to other b values and conventional MRI protocols. Sensitivity values for 3000 s/mm2 in both peripheral zone (PZ) and transition zone (TZ) were significantly higher than those observed with conventional DW-MRI-Specificity values for 3000 s/mm2 in the TZ were significantly higher than other b-value images, whereas specificity values using 3000 s/mm2 in the PZ were not significantly higher than 2000 s/mm2 images. PPV and NPV between 3000 s/mm2 and the other three modalities were significantly higher for both PZ and TZ images. The PLRs and NLRs of b-value 3000 s/mm2 DW-MRI in the PZ and TZ were also recorded. ROC analysis showed greater AUCs for the b value 3000 s/mm2 DWI than for the other three modalities. CONCLUSIONS:DW-MRI with a b-value of 3000 s/mm2 was found to be the most accurate and reliable MRI modality for PCa tumor detection and localization, particularly for TZ lesion discrimination. It may be stated that the b-value of 3000 s/mm2 is a novel, improved diagnostic biomarker with greater predictive accuracy for PCa prior to biopsy.