Quality control of quantitative diffusion-weighted magnetic resonance imaging: metrological problems

Quantitative magnetic resonance imaging is a modern method for detecting pathological changes in the patient’s tissues. However, images with quantitative characteristics are not widely used due to the limitation of the accuracy and reproducibility of the measured values. The purpose of this work is to formulate the metrological problem of quantitative magnetic resonance imaging and to ensure the reliability of research based on the analysis of practical approaches to quality control of diffusion-weighted magnetic resonance imaging. As part of the work performed, an analysis was carried out of the use of phantoms as means to ensure quality control of certain parameters of quantitative magnetic resonance imaging. The importance of validation was noted, the metrics used to control the quality of quantitative magnetic resonance imaging were highlighted, an overview of examples of clinical studies using diffusion-weighted magnetic resonance imaging was presented. It was found that accurate calibration and testing of magnetic resonance imaging scanners, as well as verification of image analysis tools, are necessary for the use of quantitative magnetic resonance imaging data in clinical practice.

To evaluate the potential of apparent diffusion coefficients (ADCs) obtained at quantitative diffusion-weighted magnetic resonance (MR) imaging of the breast as a biomarker of low-grade ductal carcinoma in situ (DCIS). This retrospective study was approved by an institutional review board, and the requirement to obtain informed consent was waived. Twenty-two women (age range, 36-75 years; mean age, 56.4 years) with pure DCIS (seven with low-grade DCIS, five with intermediate-grade DCIS, and seven with high-grade DCIS) and three with microinvasion underwent breast MR imaging at 1.5 T between January 2008 and November 2010. MR examinations included contrast material-enhanced (gadoteridol) T1-weighted imaging and diffusion-weighted MR imaging with b values of 0 and 1000 sec/mm(2). ADC maps were generated. The distributions of the ADCs in regions of interest covering the lesions were compared among the three grades by using linear mixed-model analysis, and the discriminatory power of the lesion minimum ADC was determined with receiver operating characteristic analysis. The mean ADC was 1.42 × 10(-3) mm(2)/sec (95% confidence interval [CI]: 1.31 × 10(-3) mm(2)/sec, 1.54 × 10(-3) mm(2)/sec) for low-grade DCIS, 1.23 × 10(-3) mm(2)/sec (95% CI: 1.10 × 10(-3) mm(2)/sec, 1.36 × 10(-3) mm(2)/sec) for intermediate-grade DCIS, 1.19 × 10(-3) mm(2)/sec (95% CI: 1.08 × 10(-3) mm(2)/sec, 1.30 × 10(-3) mm(2)/sec) for high-grade DCIS, and 2.06 × 10(-3) mm(2)/sec (95% CI: 1.94 × 10(-3) mm(2)/sec, 2.18 × 10(-3) mm(2)/sec) for normal breast tissue. The mean ADCs for high- and intermediate-grade DCIS were significantly lower than that for low-grade DCIS (P < .01 and P = .03, respectively), and the mean ADC for low-grade DCIS was significantly lower than that for normal tissue (P < .001). The lesion minimum ADC for low-grade DCIS was also significantly higher than that for high- and intermediate-grade DCIS (P < .01). A threshold of 1.30 × 10(-3) mm(2)/sec for the minimum ADC in the diagnosis of low-grade DCIS had a specificity of 100% (12 of 12 patients; 95% CI: 73.5%, 100%) and a positive predictive value of 100% (four of four patients; 95% CI: 39.8%, 100%). These preliminary results suggest that quantitative diffusion-weighted MR imaging could be used to identify patients with low-grade DCIS with very high specificity. If the results of this study are confirmed, this approach could potentially spare those patients from invasive approaches such as mastectomy or axillary lymph node excision.

Bladder Cancer: New Insights Into Dose, Volume and Prognostic Biomarkers

Quantitative diffusion-weighted magnetic resonance imaging in the evaluation of parotid gland masses: a study with histopathological correlation

To identify myocardial fibrosis in hypertrophic cardiomyopathy (HCM) subjects using quantitative cardiac diffusion-weighted imaging (DWI) and to compare its performance with native T1 mapping and extracellular volume (ECV). Thirty-eight HCM subjects (mean age, 53 ± 9years) and 14 normal controls (mean age, 51 ± 8years) underwent cardiac magnetic resonance imaging (CMRI) on a 3.0T magnetic resonance (MR) machine with DWI, T1 mapping and late gadolinium enhancement (LGE) imaging as the reference standard. The mean apparent diffusion coefficient (ADC), native T1 value and ECV were determined for each subject. Overall, the HCM subjects exhibited an increased native T1 value (1241.04 ± 78.50ms), ECV (0.31 ± 0.03) and ADC (2.36 ± 0.34s/mm(2)) compared with the normal controls (1114.60 ± 37.99ms, 0.24 ± 0.04, and 1.62 ± 0.38s/mm(2), respectively) (p < 0.05). DWI differentiated healthy and fibrotic myocardia with an area under the curve (AUC) of 0.93, while the AUCs of the native T1 values (0.93), (p > 0.05) and ECV (0.94), (p > 0.05) exhibited an equal differentiation ability. Both HCM LGE+ and HCM LGE- subjects had an increased native T1 value, ECV and ADC compared to the normal controls (p < 0.05). HCM LGE+ subjects exhibited an increased ECV (0.31 ± 0.04) and ADC (2.43 ± 0.36s/mm(2)) compared to HCM LGE- subjects (p < 0.05). HCM LGE+ and HCM LGE- subjects had similar native T1 values (1250 ± 76.36ms vs. 1213.98 ± 92.30ms, respectively) (p > 0.05). ADC values were linearly associated with increased ECV (R(2) = 0.36) and native T1 values (R(2) = 0.40) among all subjects. DWI is a feasible alternative to native T1 mapping and ECV for the identification of myocardial fibrosis in patients with HCM. DWI and ECV can quantitatively characterize the extent of fibrosis in HCM LGE+ and HCM LGE- patients.

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

Magnetic resonance (MR) imaging has been established as the best imaging modality for the detection, localization, and staging of uterine cancers. Recently, the usefulness of diffusion-weighted imaging (DWI) in the diagnosis of cancers has been reported in several studies. To calculate the apparent diffusion coefficient (ADC) values of normal uterine zones as well as benign and malignant uterine diseases, and to determine a cut-off ADC value for the quantitative detection of uterine malignancies with DWI. Eighty-seven patients (mean age 53 years) with 107 benign and malignant uterine pathologies and 50 healthy controls (mean age 38 years) were enrolled in the study. DWI was performed with b factors of 0, 500, and 1000 s/mm(2). The ADC values of benign and malignant lesions were compared using Student's t test. The mean and the standard deviation of the ADC values of the control group were as follows: myometrium 1.76+/-0.19 x 10(-3) mm(2)/s, junctional zone 0.99+/-0.18 x 10(-3) mm(2)/s, endometrium 1.65+/-0.33 x 10(-3) mm(2)/s, and cervix 1.71+/-0.17 x 10(-3) mm(2)/s. There was a statistically significant difference among the ADC values of normal myometrium and leiomyomas (1.47+/-0.36 x 10(-3) mm(2)/s; P<0.009), endometrium and endometrial carcinomas (0.86+/-0.13 x 10(-3) mm(2)/s; P<0.001), myometrium-junctional zone and adenomyosis (1.24+/-0.20 x 10(-3) mm(2)/s; P<0.001), and cervix and cervical carcinomas (0.91+/-0.14 x 10(-3) mm(2)/s; P<0.001). The ADC values differed significantly between malignant (0.88+/-0.11) and benign lesions (1.55+/-0.33; P<0.01). A cut-off value for malignant lesions of 1.05 x 10(-3) mm(2)/s yielded a sensitivity, specificity, and accuracy of 95.83%, 94.55%, and 94.94%, respectively. The present study shows that ADC measurements have the potential to quantitatively differentiate between normal and cancerous tissues of the uterine zones. We propose adding DWI as an adjunct sequence in the MR protocol for the assessment of uterine lesions.

Preoperative imaging of salivary gland tumors is important for predicting and differentiating benign from malignant tumors, and for aiding management planning. We aimed to investigate the accuracy of combined quantitative diffusion-weighted magnetic resonance imaging (MRI) and routine contrast-enhanced MRI in the evaluation of salivary gland tumors and the differentiation of benign from malignant tumors. This study included 51 patients with a total of 16 benign and 35 malignant lesions that were detected by histopathological analysis. There was a statistically significant difference between the apparent diffusion coefficient values (ADC) of malignant and benign lesions (0.69 ± 0.22 × 10-3 mm2/s and 1.39 ± 0.52 × 10-3 mm2/s respectively). The optimal cut-off ADC value was 1.08 with 75% specificity and 97% sensitivity. The routine contrast-enhanced MRI had predicted benign and malignant tumors with 65% sensitivity and 44% specificity. The sensitivity and specificity were greatly increased when quantitative diffusion-weighted MRI was combined with routine contrast-enhanced MRI: 100%, and 88% respectively. A receiver operating curve was generated. The area under curve was 0.88 (p < 0.001, 95% CI: 0.76-0.99). Combined quantitative diffusion-weighted MRI with ADC measurements and routine contrast-enhanced magnetic resonance imaging are helpful tools for the evaluation of salivary gland tumors and help differentiate benign from malignant lesions.

The objective of this study was to determine the diagnostic performance of quantitative diffusion-weighted magnetic resonance imaging in detection of prostate cancer. A comprehensive search was performed for English articles published before May 2012 that fulfilled the following criteria: patients had histopathologically proved prostate cancer; diffusion-weighted imaging (DWI) was performed for the detection of prostate cancer, and data for calculating sensitivity and specificity were included. Methodological quality was assessed by using the quality assessment of diagnostic studies instrument. Publication bias analysis, homogeneity, inconsistency index, and threshold effect were performed by STATA version 12. Of 119 eligible studies, 12 with 1637 malignant and 4803 benign lesions were included. There was notable heterogeneity beyond threshold effect and publication bias. The sensitivity and specificity with 95% confidence interval (CI) estimates of DWI on a per-lesion basis were 77% (CI, 0.76-0.84) and 84% (CI, 0.78-0.89), respectively, and the area under the curve of summary receiver operating characteristic curve was 0.88 (CI, 0.85-0.90). The overall positive and negative likelihood ratios with 95% CI were 4.93 (3.39-7.17) and 0.278 (0.19-0.39), respectively. Quantitative DWI has a relative sensitivity and specificity to distinguish malignant from benign in prostate lesions. However, large-scale randomized control trials are necessary to assess its clinical value because of nonuniformed diffusion gradient b factor, diagnosis threshold, and small number of studies.

Quantitative diffusion-weighted magnetic resonance imaging as a powerful adjunct to fine needle aspiration cytology for assessment of thyroid nodules

Although identification of human papilloma virus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC) is essential in predicting treatment response, no imaging modality can currently determine whether a tumor is HPV-related. In this retrospective study, 26 patients with OPSCC confined to the lateral wall or the base of tongue underwent neck magnetic resonance imaging, using T1-, T2- and diffusion-weighted imaging (DWI). Apparent diffusion coefficients (ADCs) in a region of interest covering the largest available primary tumor area of OPSCC on a single slice of the ADC map were calculated using two b values (0 and 1,000 s/mm(2)). Mean and minimum ADCs were compared with HPV status, using p16 immunohistochemistry as a surrogate marker for HPV infection. Mean and minimum ADCs for HPV(+) OPSCC were significantly lower than those for HPV(-) OPSCC. A cut-off value of mean ADC for HPV(+) OPSCC of 1.027 × 10(-3) mm(2)/s yielded sensitivity and specificity of 83.33 and 78.57%, respectively. In conclusion, the present study indicates that ADC could be used to predict HPV status in patients with OPSCC.

Background: Early and accurate prediction of response to neoadjuvant therapy (NAT) would empower personalization of breast cancer treatment regimens based on expected response. Noninvasive, quantitative dynamic contrast-enhanced (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI), when performed during the course of NAT, can accurately predict the ultimate pathological response. While these techniques have been incorporated into clinical trials in the academic setting, they have not yet been translated to the community setting, where most cancer patients receive their care. Implementation of quantitative MRI in the community setting widely expands the potential impact it can provide by 1) allowing community settings to participate in clinical trials that require quantitative MRI, and 2) advancing quantitative MRI towards standard-of-care for prediction of response in breast cancer. Methods: Women with locally advanced breast cancer (N = 28) were imaged four times during the course of NAT: 1) prior to the start of NAT, 2) after 1 cycle of NAT, 3) after 2-4 cycles of NAT, and 4) 1 cycle after MRI #3. Imaging data was acquired on 3T Siemens Skyra scanners equipped with breast coils and sited in a community hospital and radiology clinic, respectively. DW-MRI and DCE-MRI were acquired over 10 slices of 5 mm thickness. DW-MRI was acquired with diagonal monopolar diffusion-encoding gradients with b-values of 0, 200, and 800 s/mm2 in a total scan time of 1 minute 39 seconds. Voxel wise tumor cellularity was quantified using the apparent diffusion coefficient (ADC). For DCE-MRI, a gadolinium-based contrast agent was administered intravenously at 2 mL/sec after the acquisition of baseline scans. DCE-MRI data was acquired dynamically with a temporal resolution of 7.27 seconds for a total acquisition time of 8 minutes. The volume transfer constant Ktrans was calculated using Patlak analysis of DCE-MRI data to characterize the tumor vasculature. The tumor was semi-automatically segmented using a manually drawn region of interest followed by fuzzy c-means clustering of DCE-MRI data to identify a functional tumor volume. Measurements of tumor volume were combined with both ADC and Ktrans to yield metrics of tumor cellularity and bulk tumor flow, respectively. Results: Women who achieved pathological complete response at the time of surgery (pCR; n=8) displayed significantly different treatment-induced changes in MRI-derived tumor parameters versus women who did not achieve pCR (non-pCR, n=20). After 1 cycle of NAT, women who achieved pCR had smaller functional tumor volume and lower cellularity (p &amp;lt; 0.05) than non-pCR study participants. At the third and fourth MRI, tumor volume, ADC, Ktrans, cellularity, and bulk tumor flow were all significantly different between the pCR and non-pCR cohorts (p &amp;lt; 0.05). Of note, longest tumor diameter was not predictive of pCR at any time point in this study. Conclusions: This study demonstrates that quantitative DCE- and DW-MRI can be implemented successfully in community care facilities within standard-of-care settings for imaging locally advanced breast cancer. Metrics extracted from the change in DW-MRI (ADC) and DCE-MRI (Ktrans) can accurately predict pathological complete response to neoadjuvant therapy and may be more sensitive to tumor response than the RECIST criteria. Furthermore, incorporating quantitative metrics with tumor volume further increases the ability to predict pathological response to NAT in locally advanced breast cancer. While there are still challenges to address to effectively implement these quantitative metrics into the clinical workflow, this study is first in its kind to transition a decade’s worth of quantitative MRI advancements from academic settings into standard-of-care. Citation Format: John Virostko, Anna G Sorace, Kalina P Slavkova, Anum S Kazerouni, Angela M Jarrett, Julie C DiCarlo, Stefanie Woodard, Sarah Avery, Boone W Goodgame, Debra Patt, Thomas E Yankeelov. Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-03.

The added value of qualitative and quantitative diffusion-weighted magnetic resonance imaging (DW-MRI) in differentiating benign from malignant breast lesions

BackgroundCongestive hepatomegaly might be the first sign for pulmonary hypertension. Apparent diffusion coefficient (ADC) value obtained with quantitative diffusion-weighted magnetic resonance imaging (DW-MRI) is affected by liver fibrosis and perfusion. We aimed to evaluate the diagnostic value of DW-MRI in cooperation with biochemical markers, ultrasonography (US) and echocardiography (TTE) in determining the degree of hepatic congestion secondary to pulmonary hypertension (PHT).Methods35 patients with PHT and 26 control subjects were included in the study. PHT was diagnosed if pulmonary artery systolic pressure (PASP) was measured above 35 mmHg with TTE. Study group was classified into mild and moderate PHT. DW-MRI was performed with b-factors of 0, 500 and 1000 sec/mm². Mean ADC, ADC-II (Average of the ADC values of right lobe anterior and posterior segments), US, TTE and blood biochemical parameters of both groups were compared.ResultsThere exists a positive correlation between liver size and the diameters of vena cava inferior, right atrium, right hepatic vein(RHV), mid-hepatic vein(MHV), left hepatic vein(LHV) (p < 0.01). There was a positive correlation between PASP and RHV, MHV, LHV. The patients had lower ejection fractions (p < 0.01) and higher LDH (p < 0.01) and ALP (p < 0.05) levels than the control group. The ADC values of the patients with moderate PASP were higher than those with a mild PASP (p < 0.05). Mean ADC was higher in patients with moderate PHT compared to control group (p = 0.009). There was a positive correlation between PASP and ADC values of right lobe posterior segment of the liver (p < 0.05). The ADC-II and mean ADC values of the patients with moderate PASP were higher than those of the control group (p < 0.01).ConclusionsCongestion due to moderate PHT might be diagnosed with DW-MRI. As PASP increase; mean ADC and ADC-II values increase.

Background/Aims:The development of infection in pancreatitis increases the mortality rate up to 32%. Therefore, it is important to identify patients who are at high risk of developing infection, at an early stage. The objectives of the study were (a) to analyze the quantitative parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) and apparent diffusion coefficient (ADC) in infected as well as sterile pancreatic collections (b) to establish “cut-off” values for ADC that can identify infected pancreatic collections.Materials and Methods:Prospective observational study of pancreatitis cases who underwent DW-MRI from August 2018 to July 2019 were enrolled in the study. The collections were analyzed for diffusion restriction. The average of the three ADC values from the wall and center of collection was noted.Results:Infected collections were seen in 7 and sterile collections observed in 11 cases. The optimal cut-off ADC value to differentiate sterile and infected collection in our study was 1.651 × 10-3 mm2/s (sensitivity of 81.8%; specificity of 100.0%). ROC curve for mean ADC from the wall showed a significant diagnostic accuracy with AUC: 0.91; 95% CI: 0.77-1.0 (P = 0.004).Conclusion:DW-MRI is a reliable noninvasive technique to differentiate sterile and infected pancreatic collections. ADC values from the periphery of the collection can predict infected pancreatic collections at an early stage. DW-MRI should not be considered as a substitute for aspiration cytology in patients with septic symptoms and absent diffusion restriction on MRI.