Apparent Diffusion Coefficient Measurements Research Articles

Prospective Assessment of Diffusion-Weighted-MRI as a Biomarker of Treatment Response and Disease Control in Head and Neck Cancer

<h3>Purpose/Objective(s)</h3> To determine diffusion-weighted MRI (DWI) parameters associated with tumor response and local control (LC) in head and neck (HNC) patients treated with definitive radiation therapy (RT). <h3>Materials/Methods</h3> Eighty-seven HNC patients enrolled in an active prospective imaging study at MD Anderson Cancer Center were included in the analysis. Patients had MRIs prior to, at mid-RT, and post-treatment completion. Inclusion criteria include adult with histologic evidence of malignant head and neck neoplasm indicated for curative-intent treatment with RT with/without chemotherapy; good performance status (ECOG score 0-2); and with no contraindications to MRI. Patients were scanned using a full-body MRI scanner with two large four-channel flex phased-array coils. We used fat-suppressed T2-weighted turbo spin echo for tumor segmentation which was co-registered to respective DWIs for extraction of apparent diffusion coefficient (ADC) measurements. Sequence parameters were (TR/TE (ms); pixel size/slice thickness (mm); b-values (s/mm2)): T2-weighted (5280/80; 0.5/2; N/A), BLADE (5900/50; 2/4; 0 & 800), RESOLVE (9380/63; 2/4; 0 & 800). Treatment response was assessed at mid-RT and at 8-12 weeks post-RT using RECIST 1.1 criteria and was defined as: complete response (CR) vs non-complete response (non-CR). Pre-RT ADC was correlated with RT response (CR vs non-CR) at mid- and post-RT time points. Mann-Whitney test was used to compare ADC values between the mid-treatment CR group and the non-CR group. Recursive partitioning analysis (RPA) was done to identify ADC threshold associated with relapse. <h3>Results</h3> Fifty-nine patients with grossly visible primary tumor volume prior to RT start were included in this analysis. Patients' disease and treatment criteria are shown in Table 1. Pre-treatment ADC was not correlated with tumor response or oncologic outcomes (P>0.05). For patients with CR at the end of RT, there was a significant increase in mean ADC at mid-RT compared to baseline ((1.8 ± 0.29) × 10^–3 mm²/s <i>vs</i> (1.37 ± 0.22) × 10^–3 mm²/s, <i>p</i> <0.0001). However, patients with no-CR had no statistically significant increase (p>0.05). Median follow-up was 32 months. Patients with ≤106% delta ADC at mid-RT had significantly worse local control at 2-year compared to patients with higher delta ADC (48% vs 96%, <i>p</i> <0.0001). <h3>Conclusion</h3> Delta ADC changes is a strong predictor of local recurrence in head and neck cancer patients. Multi-institutional data is needed for validation of our results.

The Role of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Benign From Malignant Thyroid Nodules: A Descriptive Observational Study.

Background Currently, no effective and reproducible imaging method can quantitatively differentiate between benign and malignant thyroid nodules. This study aimed to assess the role of diffusion-weighted imaging (DWI) in differentiating benign from malignant thyroid nodules. Methodology We conducted anobservational studyin the Department of Radiodiagnosis at R. L. Jalappa Hospital and Research Center, Kolar, India. The study was conducted from January 2020 to June 2021, among 43 patients with thyroid swelling or nodules. We recorded patient baseline data,pertinent clinical history, and relevant laboratory investigations. Patients underwent diffusion-weighted MRI of the neck. We used receiver operator curve analysis to determine the utility of the apparent diffusion coefficient (ADC) of the thyroid nodule in predicting the histopathological diagnosis. Data were analyzed using coGuide (V1.0.3, BDSS Corp., India). Results A total of 43 patients were enrolled in the study (35 women, 81.4%; 8 men, 18.6%). The mean (SD) age was 49.8 (14.3) years. Nodular hyperplasia was the most common histopathologic diagnosis of the nodule (25.5%), followed by lymphocytic thyroiditis (16.2%). The MRI and histopathological findings matched: both found 35 (81.4%) nodules as benign and 8 (18.6%) as malignant. The ADC value of thyroid nodules had excellent predictive validity in predicting malignancy, as indicated by the area under the curve of 0.925 (95% confidence interval [CI]0.804-1.000; p< 0.001). The sensitivity was 87.50% (95% CI47.35%-99.68%), specificity was 94.29% (95% CI80.84%-99.30%), and the total diagnostic accuracy obtained was 93.02% (95% CI80.94%-98.54%). Conclusions DWI with ADC measurement has the potential to differentiate between benign and malignant thyroid nodules.

Role of diffusion-weighted MRI in differentiation between benign and malignant anterior mediastinal masses.

Diffusion-weighted imaging (DWI) is considered to be a useful biomarker to characterize the cellularity of lesions, yet its application in the thorax to evaluate anterior mediastinal lesions has not been well investigated. The aims of our study were to describe the magnetic resonance (MR) characteristics of anterior mediastinal masses and to assess the role of apparent diffusion coefficient (ADC) value in distinguishing benign from malignant lesions of the anterior mediastinum. We conducted a retrospective cross-sectional study including 55 patients with anterior mediastinal masses who underwent preinterventional MR scanning with the following sequences: T1 VIBE DIXON pre and post-contrast, T2 HASTE, T2 TIRM, DWI-ADC map (b values of 0 and 2000 sec/mm2). The ADC measurements were obtained by two approaches: hot-spot ROI and whole-tumor histogram analysis. The lesions were grouped by three distinct ways: benign versus malignant, group A (benign lesions and type A, AB, B1 thymoma) versus group B (type B2, B3 thymoma and other malignant lesions), lymphoma versus other malignancies. The study was composed of 55 patients, with 5 benign lesions and 50 malignant lesions. The ADCmean, ADCmedian, ADC10, ADC90 in the histogram-based approach and the hot-spot-ROI-based mean ADC of the malignant lesions were significantly lower than those of benign lesions (P values< 0.05). The hot-spot-ROI-based mean ADC had the highest value in differentiation between benign and malignant mediastinal lesions, as well as between group A and group B; the ADC cutoffs (with sensitivity, specificity) to differentiate malignant from benign lesions and group A from group B were 1.17 x 10-3 mm2/sec (80%, 80%) and 0.99 x 10-3 mm2/sec (78.4%, 88.9%), respectively. The ADC values obtained by using the hot-spot-ROI-based and the histogram-based approaches are helpful in differentiating benign and malignant anterior mediastinal masses.

Utility of the Diffusion Weighted Sequence in Gynecological Imaging: Review Article.

Simple SummaryDiffusion weighted imaging (DWI) is a magnetic resonance imaging sequence with diverse clinical applications in malignant and nonmalignant gynecological conditions. It provides vital supplemental information in the diagnosis and management of various gynecological conditions. Radiologists should be aware of fundamental concepts, clinical applications and pitfalls of DWI. Additionally we briefly discuss potential scope of newer advanced techniques based on DWI including diffusion tensor imaging and diffusion-weighted whole-body imaging with background signal suppression.Functional imaging with diffusion-weighted imaging (DWI) is a complementary tool to conventional diagnostic magnetic resonance imaging sequences. It is being increasingly investigated to predict tumor response and assess tumor recurrence. We elucidate the specific technical modifications of DWI preferred for gynecological imaging, including the different b-values and planes for image acquisition. Additionally, we discuss the problems and potential pitfalls encountered during DWI interpretation and ways to overcome them. DWI has a wide range of clinical applications in malignant and non-malignant gynecological conditions. It provides supplemental information helpful in diagnosing and managing tubo-ovarian abscess, uterine fibroids, endometriosis, adnexal torsion, and dermoid. Similarly, DWI has diverse applications in gynecological oncology in diagnosis, staging, detection of recurrent disease, and tumor response assessment. Quantitative evaluation with apparent diffusion coefficient (ADC) measurement is being increasingly evaluated for correlation with various tumor parameters in managing gynecological malignancies aiding in preoperative treatment planning. Newer advanced DWI techniques of diffusion tensor imaging (DTI) and whole body DWI with background suppression (DWIBS) and their potential uses in pelvic nerve mapping, preoperative planning, and fertility-preserving surgeries are briefly discussed.

Deep-learned estimation of uncertainty in measurements of apparent diffusion coefficient from whole-body diffusion-weighted MRI

PurposeTo use deep learning to calculate the uncertainty in apparent diffusion coefficient (σADC) voxel-wise measurements to clinically impact the monitoring of treatment response and improve the quality of ADC maps. Materials and methodsWe use a uniquely designed diffusion-weighted imaging (DWI) acquisition protocol that provides gold-standard measurements of σADC to train a deep learning model on two separate cohorts: 16 patients with prostate cancer and 28 patients with mesothelioma. Our network was trained with a novel cost function, which incorporates a perception metric and a b-value regularisation term, on ADC maps calculated by combinations of 2 or 3 b-values (e.g. 50/600/900, 50/900, 50/600, 600/900 s/mm2). We compare the accuracy of the deep-learning based approach for estimation of σADC with gold-standard measurements. ResultsThe model accurately predicted the σADC for every b-value combination in both cohorts. Mean values of σADC within areas of active disease deviated from those measured by the gold-standard by 4.3% (range, 2.87–6.13%) for the prostate and 3.7% (range, 3.06–4.54%) for the mesothelioma cohort. We also showed that the model can easily be adapted for a different DWI protocol and field-of-view with only a few images (as little as a single patient) using transfer learning. ConclusionDeep learning produces maps of σADC from standard clinical diffusion-weighted images (DWI) when 2 or more b-values are available.

Impact of Adding Mean Apparent Diffusion Coefficient (ADCmean) Measurements to O-RADS MRI Scoring For Adnexal Lesions Characterization: A Combined O-RADS MRI/ADCmean Approach

Evaluate the impact of adding mean apparent diffusion coefficient (ADCmean) measurements to the Ovarian-Adnexal Imaging Reporting and Data System MRI (O-RADS MRI) scoring for adnexal lesion characterization using a combined O-RADS MRI/ADCmean reading approach. This prospective study included 90 women who underwent pelvic MRI for adnexal lesions diagnosis and characterization. Two readers scored the adnexal lesions using the O-RADS MRI scoring independently and in consensus. A third reader calculated ADCmean measurements. The final diagnoses were determined by histo-pathology (n = 77) or follow-up imaging (n = 13). Areas under the curves (AUCs) and diagnostic performance metrics were calculated for the O-RADS MRI scoring, ADCmean, and combined O-RADS MRI/ADCmean thresholds. P-value <0.05 was significant. 116 adnexal lesions (71 benign, 45 malignant) were analyzed. The optimal thresholds to predict malignant adnexal lesions were O-RADS MRI score >3 and ADCmean value ≤1.08×10-3 mm2/s (AUC 0.926 and 0.823; sensitivity 97.7% and 95.5%; specificity 87.3% and 68%; positive predictive value (PPV) 83% and 66.2%; positive likelihood ratio (PLR) 7.7 and 3.08, respectively). Compared to the O-RADS MRI scoring, a combined threshold of O-RADS MRI >3/ADCmean ≤1.08×10-3 mm2/s, yielded a reduction of false positives, a significant increase in the specificity (97.1%, p=0.005), PPV (95.4%, p=0.002), and PLR (33.1, p <0.0001), and non-significant change in the AUC (0.953, p=0.252), and sensitivity (93.3%, p=0.467). The diagnostic performance of O-RADS MRI scoring to characterize adnexal lesions could be improved by adding the ADCmean values through reducing false positives, increasing specificity, and maintaining good sensitivity.

Role of apparent diffusion coefficient measurement in differentiating histological subtypes of brain metastasis of lung cancer

SUMMARYOBJECTIVE:The aim of this study was to investigate the role of apparent diffusion coefficient of diffusion-weighted imaging in differentiating histological subtypes of brain metastasis of lung cancer.METHODS:Diffusion-weighted imaging of 158 patients (mean age: 61.2±10.68 years) with brain metastasis of lung cancer (36 small cell lung cancer and 122 non-small cell lung cancer) were retrospectively evaluated. The minimum and mean apparent diffusion coefficient values of the metastasis, apparent diffusion coefficient of edema around the metastasis, and apparent diffusion coefficient of contralateral brain parenchyma were measured. Normalized apparent diffusion coefficient was calculated by proportioning the mean apparent diffusion coefficient of the metastasis to the apparent diffusion coefficient of the contralateral brain parenchyma. Minimum and mean apparent diffusion coefficient of the metastasis, apparent diffusion coefficient of edema around metastasis, and normalized apparent diffusion coefficient were compared between small cell lung cancer and non-small cell lung cancer metastases.RESULTS:Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, and normalized apparent diffusion coefficient values of small cell lung cancer metastases (0.43±0.19×10−3mm2/s, 0.63±0.20×10−3mm2/s, and 0.81 [0.55–1.44], respectively) were significantly lower than those of non-small cell lung cancer metastases (0.71±0.26×10−3mm2/s, 0.93±0.29×10−3mm2/s, and 1.30 [0.60–3.20], respectively; p<0.001). Mean apparent diffusion coefficient of edema of small cell lung cancer metastases (1.21±0.28×10−3mm2/s) was significantly lower than that of non-small cell lung cancer metastases (1.39±0.26×10−3mm2/s, p=0.020). The best cutoff values of minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema for the differentiation of small cell lung cancer and non-small cell lung cancer were found to be 0.56×10−3mm2/s, 0.82×10−3mm2/s, 1.085, and 1.21×10−3mm2/s, respectively. The area under the receiver operating characteristic curve, sensitivity, and specificity values were, respectively, 0.812, 80.6, and 73.8% for minimum apparent diffusion coefficient; 0.825, 91.7, and 61.5% for mean apparent diffusion coefficient; 0.845, 80.6, and 73.8% for normalized apparent diffusion coefficient; and 0.698, 75.0, and 67.7% for apparent diffusion coefficient of edema.CONCLUSIONS:Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema around metastasis can differentiate histological subtypes of brain metastasis of lung cancer.

Changes in Apparent Diffusion Coefficient (ADC) in Serial Weekly MRI during Radiotherapy in Patients with Head and Neck Cancer: Results from the PREDICT-HN Study.

Background: The PREDICT-HN study aimed to systematically assess the kinetics of imaging MR biomarkers during head and neck radiotherapy. Methods: Patients with intact squamous cell carcinoma of the head and neck were enrolled. Pre-, during, and post-treatment MRI were obtained. Serial GTV and ADC measurements were recorded. The correlation between each feature and the GTV was calculated using Spearman’s correlation coefficient. The linear mixed model was used to evaluate the change in GTV over time. Results: A total of 41 patients completed the study. The majority (76%) had oropharyngeal cancer. A total of 36 patients had intact primary tumours that can be assessed on MRI, and 31 patients had nodal disease with 46 nodes assessed. Median primary GTV (GTVp) size was 14.1cc. The rate of GTVp shrinkage was highest between pre-treatment and week 4. Patients with T3-T4 tumours had a 3.8-fold decrease in GTVp compared to T1-T2 tumours. The ADC values correlated with residual GTVp. The median nodal volume (GTVn) was 12.4cc. No clinical features were found to correlate with GTVn reduction. The overall change in ADC for GTVn from pre-treatment was significant for 35th–95th percentiles in weeks 1–4 (p < 0.001). Conclusion: A discrepancy in the trajectory of ADC between primary and nodal sites suggested that they exhibit different treatment responses and should be analysed separately in future studies.

MRI: Evaluating the Application of FOCUS-MUSE Diffusion-Weighted Imaging in the Pancreas in Comparison With FOCUS, MUSE, and Single-Shot DWIs.

Diffusion-weighted imaging (DWI) is a useful technique to detect pancreatic lesion. In DWIs, field-of-view optimized and constrained undistorted single-shot (FOCUS) can improve the spatial resolution and multiplexed sensitivity-encoding (MUSE) can gain a high signal-to-noise ratio (SNR). Based on the advantage of FOCUS and MUSE, a new DWI sequence-named FOCUS-MUSE DWI (FOCUS combined with MUSE)-was developed to delineate the pancreas. To investigate the reliability of FOCUS-MUSE DWI compared to FOCUS, MUSE and single-shot (SS) DWI via the systematical evaluation of the apparent diffusion coefficient (ADC) measurements, SNR and image quality. Prospective. A total of 33 healthy volunteers and 9 patients with pancreatic lesion. A 3.0 T scanner. FOCUS-MUSE DWI, FOCUS DWI, MUSE DWI, SS DWI. For volunteers, ADC and SNR were measured by two readers in the pancreatic head, body, and tail. For all subjects, the diagnostic image quality score was assessed by three other readers on above four DWIs. Paired-sample T-test, intraclass correlation (ICC), Bland-Altman method, Friedman test, Dunn-Bonferroni post hoc test and kappa coefficient. A significance level of 0.05 was used. FOCUS-MUSE DWI had the best intersession repeatability of ADC measurements (head: 59.53, body: 101.64, tail: 42.30) among the four DWIs, and also maintained the significantly highest SNR (reader 1 [head: 19.68 ± 3.23, body: 23.42 ± 5.00, tail: 28.85 ± 4.96], reader 2 [head: 19.93 ± 3.52, body: 23.02 ± 5.69, tail: 29.77 ± 6.33]) except for MUSE DWI. Furthermore, it significantly achieved better image quality in volunteers (median value: 4 score) and 9 patients (most in 4 score). FOCUS-MUSE DWI improved the reliability of pancreatic images with the most stable ADC measurement, best image quality score and sufficient SNR among four DWIs. 2 TECHNICAL EFFICACY: Stage 2.

Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer.

Background Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 requires multiparametric MRI of the prostate, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging sequences; however, the contribution of DCE imaging remains unclear. Purpose To assess whether DCE imaging in addition to apparent diffusion coefficient (ADC) and normalized T2 values improves PI-RADS version 2.0 for prediction of clinically significant prostate cancer (csPCa). Materials and Methods In this retrospective study, clinically reported PI-RADS lesions in consecutive men who underwent 3-T multiparametric MRI (T2-weighted, DWI, and DCE MRI) from May 2015 to September 2016 were analyzed quantitatively and compared with systematic and targeted MRI-transrectal US fusion biopsy. The normalized T2 signal (nT2), ADC measurement, mean early-phase DCE signal (mDCE), and heuristic DCE parameters were calculated. Logistic regression analysis indicated the most predictive DCE parameters for csPCa (Gleason grade group ≥2). Receiver operating characteristic parameter models were compared using the Obuchowski test. Recursive partitioning analysis determined ADC and mDCE value ranges for combined use with PI-RADS. Results Overall, 260 men (median age, 64 years [IQR, 58-69 years]) with 432 lesions (csPCa [n = 152] and no csPCa [n = 280]) were included. The mDCE parameter was predictive of csPCa when accounting for the ADC and nT2 parameter in the peripheral zone (odds ratio [OR], 1.76; 95% CI: 1.30, 2.44; P = .001) but not the transition zone (OR, 1.17; 95% CI: 0.81, 1.69; P = .41). Recursive partitioning analysis selected an ADC cutoff of 0.897 × 10-3 mm2/sec (P = .04) as a classifier for peripheral zone lesions with a PI-RADS score assessed on the ADC map (hereafter, ADC PI-RADS) of 3. The mDCE parameter did not differentiate ADC PI-RADS 3 lesions (P = .11), but classified lesions with ADC PI-RADS scores greater than 3 with low ADC values (less than 0.903 × 10-3 mm2/sec, P < .001) into groups with csPCa rates of 70% and 97% (P = .008). A lesion size cutoff of 1.5 cm and qualitative DCE parameters were not defined as classifiers according to recursive partitioning (P > .05). Conclusion Quantitative or qualitative dynamic contrast-enhanced MRI was not relevant for Prostate Imaging Reporting and Data System (PI-RADS) 3 lesion risk stratification, while quantitative apparent diffusion coefficient (ADC) values were helpful in upgrading PI-RADS 3 and PI-RADS 4 lesions. Quantitative ADC measurement may be more important for risk stratification than current methods in future versions of PI-RADS. © RSNA, 2022 Online supplemental material is available for this article See also the editorial by Goh in this issue.

Diffusion-weighted and gadolinium-enhanced dynamic MRI in parotid gland tumors.

To evaluate the value of diffusion-weighted imaging and dynamic contrast-enhanced MRI for the diagnosis of parotid gland tumors. Retrospective review of patients with surgically treated parotid tumors between January 2009 and June 2020, who underwent a preoperative parotid gland MRI including standard morphological sequences, diffusion-weighted echoplanar imaging with apparent diffusion coefficient measurement and T1-weighted gadolinium-enhanced dynamic MRI sequences with Fat Saturation. The lesion was classified between malignant vs benign and precisions regarding its histological type were given when possible. Imaging findings were compared with pathology results. Inclusion of 133 patients (mean age: 53years). Multiparametric MRI had a sensitivity of 90.3%, a specificity of 77.5%, an overall accuracy of 80.5%, a positive predictive value of 54.9% and a negative predictive value of 96.3% to differentiate benign parotid tumor from malignant ones. Specificity (85.5%) and positive predictive value (67.6%) were improved for cases, where anatomical and functional MRI characteristics were conclusive and consistent with clinical findings. Combining diffusion-weighted and gadolinium-enhanced dynamic sequences, in addition to morphological ones enables high (> 90%) sensitivity to detect malignant parotid gland tumors. It also gives the possibility to characterize pleomorphic adenomas and Warthin tumors and to avoid fine-needle aspiration in cases of typical imaging presentation and reassuring clinical findings.

Repeatability and test-retest reproducibility of mean apparent diffusion coefficient measurements of focal and diffuse disease in relapsed multiple myeloma at 3T whole body diffusion-weighted MRI (WB-DW-MRI).

To assess the test-retest reproducibility and intra/interobserver agreement of apparent diffusion coefficient (ADC) measurements of myeloma lesions using whole body diffusion-weighted MRI (WB-DW-MRI) at 3T MRI. Following ethical approval, 11 consenting patients with relapsed multiple myeloma were prospectively recruited and underwent baseline WB-DW-MRI. For a single bed position, axial DWI was repeated after a short interval to permit test-retest measurements.Mean ADC measurement was performed by two experienced observers. Intra- and interobserver agreement and test-retest reproducibility were assessed, using coefficient of variation (CV) and interclass correlation coefficient (ICC) measures, for diffuse and focal lesions (small ≤10 mm and large >10 mm). 47 sites of disease were outlined (23 focal, 24 diffuse) in different bed positions (pelvis = 22, thorax = 20, head and neck = 5). For all lesions, there was excellent intraobserver agreement with ICC of 0.99 (0.98-0.99) and COV of 5%. For interobserver agreement, ICC was 0.89 (0.8-0.934) and COV was 17%. There was poor interobserver agreement for diffuse disease (ICC = 0.46) and small lesions (ICC = 0.54).For test-retest reproducibility, excellent ICC (0.916) and COV (14.5%) values for mean ADC measurements were observed. ICCs of test-retest were similar between focal lesions (0.83) and diffuse infiltration (0.80), while ICCs were higher in pelvic (0.95) compared to thoracic (0.81) region and in small (0.96) compared to large (0.8) lesions. ADC measurements of focal lesions in multiple myeloma are repeatable and reproducible, while there is more variation in ADC measurements of diffuse disease in patients with multiple myeloma. Mean ADC measurements are repeatable and reproducible in focal lesions in multiple myeloma, while the ADC measurements of diffuse disease in multiple myeloma are more subject to variation. The evidence supports the future potential role of ADC measurements as predictive quantitative biomarker in multiple myeloma.

Apparent diffusion coefficient values in Modic changes – interobserver reproducibility and relation to Modic type

BackgroundModic Changes (MCs) in the vertebral bone marrow were related to back pain in some studies but have uncertain clinical relevance. Diffusion weighted MRI with apparent diffusion coefficient (ADC)-measurements can add information on bone marrow lesions. However, few have studied ADC measurements in MCs. Further studies require reproducible and valid measurements. We expect valid ADC values to be higher in MC type 1 (oedema type) vs type 3 (sclerotic type) vs type 2 (fatty type). Accordingly, the purpose of this study was to evaluate ADC values in MCs for interobserver reproducibility and relation to MC type.MethodsWe used ADC maps (b 50, 400, 800 s/mm2) from 1.5 T lumbar spine MRI of 90 chronic low back pain patients with MCs in the AIM (Antibiotics In Modic changes)-study. Two radiologists independently measured ADC in fixed-sized regions of interests. Variables were MC-ADC (ADC in MC), MC-ADC% (0% = vertebral body, 100% = cerebrospinal fluid) and MC-ADC-ratio (MC-ADC divided by vertebral body ADC). We calculated mean difference between observers ± limits of agreement (LoA) at separate endplates. The relation between ADC variables and MC type was assessed using linear mixed-effects models and by calculating the area under the receiver operating characteristic curve (AUC).ResultsThe 90 patients (mean age 44 years; 54 women) had 224 MCs Th12-S1 comprising type 1 (n = 111), type 2 (n = 91) and type 3 MC groups (n = 22). All ADC variables had higher predicted mean for type 1 vs 3 vs 2 (p < 0.001 to 0.02): MC-ADC (10− 6 mm2/s) 1201/796/576, MC-ADC% 36/21/14, and MC-ADC-ratio 5.9/4.2/3.1. MC-ADC and MC-ADC% had moderate to high ability to discriminate between the MC type groups (AUC 0.73–0.91). MC-ADC-ratio had low to moderate ability (AUC 0.67–0.85). At L4-S1, widest/narrowest LoA were for MC-ADC 20 ± 407/12 ± 254, MC-ADC% 1.6 ± 18.8/1.4 ± 10.4, and MC-ADC-ratio 0.3 ± 4.3/0.2 ± 3.9. Difference between observers > 50% of their mean value was less frequent for MC-ADC (9% of MCs) vs MC-ADC% and MC-ADC-ratio (17–20%).ConclusionsThe MC-ADC variable (highest mean ADC in the MC) had best interobserver reproducibility, discriminated between MC type groups, and may be used in further research. ADC values differed between MC types as expected from previously reported MC histology.

Correlation of Apparent Diffusion Coefficient With Proliferation and Apoptotic Indexes in a Murine Model of Fibrosarcoma: Comparison of Four Methods for MRI Region of Interest Positioning.

Diffusion-weighted imaging (DWI) has demonstrated great potential in predicting the expression of tumor cell proliferation and apoptosis indexes. To evaluate the impact of four region of interest (ROI) methods on interobserver variability and apparent diffusion coefficient (ADC) values and to examine the correlation of ADC values with Ki-67, Bcl-2, and P53 labeling indexes (LIs) in a murine model of fibrosarcoma. Prospective, animal model. A total of 22 female BALB/c mice bearing intramuscular fibrosarcoma xenografts. A 3.0 T/T1-weighted fast spin-echo (FSE), T2-weighted fast relaxation fast spin-echo, and DWI PROPELLER FSE sequences. Four radiologists measured ADC values using four ROI methods (oval, freehand, small-sample, and whole-volume). Immunohistochemical assessment of Ki-67, Bcl-2, and P53 LIs was performed. Interclass correlation coefficient (ICC), one-way analysis of variance followed by LSD-t post hoc analysis, and Pearson correlation test were performed. The statistical threshold was defined as a P-value of <0.05. All ROI methods for ADC measurements showed excellent interobserver agreement (ICC range, 0.832-0.986). The ADC values demonstrated significant differences among the four ROI methods. The ADC values for oval, freehand, small-sample, and whole-volume ROI methods showed a moderately negative correlation with Ki-67 (r=-0.623; r=-0.629; r=-0.642, and r=-0.431) and Bcl-2 (r=-0.590; r=-0.597; r=-0.659, and r=-0.425) LIs, but no correlation with P53 LI (r=0.364, P=0.104; r=0.350, P=0.120; r=0.379, P=0.091; r=0.390, P=0.080). The ADC value can be used to evaluate cell proliferation and apoptosis indexes in a murine model of fibrosarcoma, employing the small-sample ROI as a reliable method. 1 TECHNICAL EFFICACY: Stage 3.

Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T

We compared the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes, readout-segmented EPI and zoomit EPI in the repeatability of apparent diffusion coefficient (ADC) measurements, cortico-medullary contrast to noise ratio (c-mCNR) and image quality. In this institutional review board-approved prospective study, some common clinically applicable diffusion-weighted imaging (b = 50, 400, 800 s/mm2) of kidney on 3.0 T MRI were performed on 22 volunteers using SS-EPI with breath-hold diffusion-weighted imaging (BH-DWI), free-breathing (FB-DWI), navigator-triggered (NT-DWI) and respiratory-triggered (RT-DWI), readout-segmented DWI (RS-DWI), and Zoomit DWI (Z-DWI). ADC and c-mCNR were measured in 12 anatomic locations (the upper, middle, and lower pole of the renal cortex and medulla), and image quality was assessed on these DWI sequences. A DWI with the optimal clinical utility was decided by systematically assessing the ADC repeatability, c-mCNR and image quality among the DWIs. For ADC measurements, Z-DWI had an excellent intra-observer agreement (intra-class correlation coefficients (ICCs): 0.876–0.944) and good inter-observer agreement (inter-class ICCs: 0.798–0.856) in six DWI sequences. Z-DWI had the highest ADC repeatability in most of the 12 anatomic locations of the kidneys (mean ADC absolute difference: 0.070–0.111 × 10−3 mm2/s, limit of agreement: 0.031–0.056 × 10−3 mm2/s). In all DWIs, Z-DWI yielded a slightly higher c-mCNR than other DWIs in most representative locations (P > 0.05), which was significantly higher than BH-DWI and FB-DWI in the middle pole of both kidneys and the upper pole of the left kidney (P < 0.05). In addition, Z-DWI yielded image quality that was similar to RT-DWI and NT-DWI (P > 0.05) and superior to BH-DWI, FB-DWI and RS-DWI (P < 0.05). Our results suggest that Z-DWI provides the highest ADC reproducibility, better c-mCNR and good image quality on 3.0 T MRI, making it the recommended sequence for clinical DWI of the kidney.

Comparison between diffusion-weighted magnetic resonance and positron-emission tomography in the evaluation of treated lymphomas with mediastinal involvement

BackgroundThe persistence of residual tissue after treatment is frequent in patients with mediastinal lymphomas and it is often characterized by 18F-Flurodeoxyglucose Positron Emission Tomography (18F-FDG PET) uptake. This study aims to investigate the usefulness of diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) sequence in residual tissues of treated mediastinal lymphomas and to compare it with 18F-FDG PET-CT.ResultsWe included 21 patients with mediastinal Hodgkin and non-Hodgkin lymphomas who showed residual masses on PET-CT imaging at end of treatment and underwent DWIBS-Magnetic Resonance Imaging (MRI). SUVmax and Apparent Diffusion Coefficient (ADC) values of residual masses were assessed quantitatively, including measurement of mean ADC. 15 patients showed radiotracer uptake at 18F-FDG PET-CT, among them only 3 had positive DWIBS-MRI with low ADC values (median value: 0.90 mm2/s). The mediastinal biopsy in these 3 “double positive” patients confirmed pathological residual tissue. All the patients with positive 18F-FDG PET-CT but negative DWIBS-MRI (n = 18) with high ADC values (median value: 2.05 mm2/s) were confirmed negative by biopsy.ConclusionsDWIBS-MRI examination combined with ADC measurement allowed to discriminate pathological and non-pathological residual tissue in patients with treated mediastinal lymphoma. These preliminary results seem to pave the way for a leading role of the MRI which could be a useful alternative to the 18F-FDG PET/CT.

Diagnostic value of whole-tumor apparent diffusion coefficient map radiomics analysis in predicting early recurrence of solitary hepatocellular carcinoma ≤ 5cm.

To evaluate the role of whole-tumor radiomics analysis of apparent diffusion coefficient (ADC) maps in predicting early recurrence (ER) of solitary hepatocellular carcinoma (HCC) ≤ 5cm and compare the diagnostic efficiency of whole-tumor and single-slice ADC measurements. One hundred and seventy patients with primary HCC were randomly divided into the training set (n = 119) and the test set (n = 51). The diagnostic efficiency was compared between the whole-tumor and single-slice ADC measurements. The clinical-radiological model was established by selected significant clinical characteristics and qualitative imaging features. The radiomics model was constructed using the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm. The significant clinical-radiological risk factors and radiomics features were integrated to develop the combined model. Receiver operating characteristic (ROC) curves were used for evaluating the predictive performance. Cirrhosis, age, and albumin were significantly associated with ER in the clinical-radiological model selected by the random forest classifier. The diagnostic efficiency of the whole-tumor ADC measurements was slight higher than that of the single-slice (AUC = 0.602 and 0.586, respectively). The clinical-radiological model (AUC = 0.84 and 0.82 in the training and test sets, respectively) showed better diagnostic performance than the radiomics model (AUC = 0.70 and 0.69 in the training and test sets, respectively) in predicting ER. The combined model showed optimal predictive performance with the highest AUC values of 0.88 and 0.85 in the training and test sets, respectively. The whole-tumor ADC measurements performed better than the single-slice ADC measurements. The clinical-radiological model performed better than the radiomics model for predicting ER in patients with solitary HCC ≤ 5cm.

Anatomical and diffusion-weighted imaging of brain abnormalities in third-trimester fetuses with cytomegalovirus infection.

In this study of cytomegalovirus (CMV)-infected fetuses with first-trimester seroconversion, we aimed to evaluate the detection of brain abnormalities using magnetic resonance imaging (MRI) and neurosonography (NSG) in the third trimester, and compare the grading systems of the two modalities. We also evaluated the feasibility of routine use of diffusion-weighted imaging (DWI) fetal MRI and compared the regional apparent diffusion coefficient (ADC) values between CMV-infected fetuses and presumed normal, non-infected fetuses in the third trimester. This was a retrospective review of MRI and NSG scans in fetuses with confirmed first-trimester CMV infection performed between September 2015 and August 2019. Brain abnormalities were recorded and graded using fetal MRI and NSG grading systems to compare the two modalities. To investigate feasibility of DWI, a four-point rating scale (poor, suboptimal, good, excellent) was applied to assess the quality of the images. Quantitative assessment was performed by placing a freehand drawn region of interest in the white matter of the frontal, parietal, temporal and occipital lobes and the basal ganglia, pons and cerebellum to calculate ADC values. Regional ADC measurements were obtained similarly in a control group of fetuses with negative maternal CMV serology in the first trimester, normal brain findings on fetal MRI and normal genetic testing. Fifty-three MRI examinations of 46 fetuses with confirmed first-trimester CMV infection were included. NSG detected 24 of 27 temporal cysts seen on MRI scans, with a sensitivity of 78% and an accuracy of 83%. NSG did not detect abnormal gyration visible on two (4%) MRI scans. Periventricular calcifications were detected on two MRI scans compared with 10 NSG scans. While lenticulostriate vasculopathy was detected on 11 (21%) NSG scans, no fetus demonstrated this finding on MRI. MRI grading correlated significantly with NSG grading of brain abnormalities (P < 0.0001). Eight (15%) of the DWI scans in the CMV cohort were excluded from further analysis because of insufficient quality. The ADC values of CMV-infected fetuses were significantly increased in the frontal (both sides, P < 0.0001), temporal (both sides, P < 0.0001), parietal (left side, P = 0.0378 and right side, P = 0.0014) and occipital (left side, P = 0.0002 and right side, P < 0.0001) lobes and decreased in the pons (P = 0.0085) when compared with non-infected fetuses. The ADC values in the basal ganglia and the cerebellum were not significantly different in CMV-infected fetuses compared with normal controls (all P > 0.05). Temporal and frontal ADC values were higher in CMV-infected fetuses with more severe brain abnormalities compared to fetuses with mild abnormalities. Ultrasound and MRI are complementary during the third trimester in the assessment of brain abnormalities in CMV-infected fetuses, with a significant correlation between the grading systems of the two modalities. On DWI in the third trimester, the ADC values in several brain regions are abnormal in CMV-infected fetuses compared with normal controls. Furthermore, they seem to correlate in the temporal area and, to a lesser extent, frontal area with the severity of brain abnormalities associated with CMV infection. Larger prospective studies are needed for further investigation of the microscopic nature of diffusion abnormalities and correlation of different imaging findings with postnatal outcome. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Reproducibility of apparent diffusion coefficient measurement in normal prostate peripheral zone at 1.5T MRI

PurposeThe purpose of this study was to quantify the influence of factors of variability on apparent diffusion coefficient (ADC) estimation in the normal prostate peripheral zone (PZ). Materials and methodsFifty healthy volunteers underwent in 2017 (n = 17) or 2020 (n = 33) two-point (0, 800 s/mm²) prostate diffusion-weighted imaging in the morning on 1.5 T scanners A and B from different manufacturers. Additional five-point (50, 150, 300, 500, 800 s/mm²) acquisitions were performed on scanner B in the morning and evening. ADC was measured in PZ at midgland using ADC maps reconstructed with various b-value combinations. ADC distributions from 2017 and 2020 were compared using Wilcoxon rank sum test. ADC obtained in the same volunteers were compared using Bland Altman methodology. The 95% confidence interval upper limit of the repeatability/reproducibility coefficient defined the lowest detectable ADC difference. ResultsForty-nine participants with a mean age of 24.6 ± 3.8 [SD] years (range: 21–37 years) were finally included. ADC distributions from 2017 and 2020 were not significantly different and were combined. Despite high individual variability, there was no significant bias (10 × 10−6 mm²/s, P = 0.58) between ADC measurements made on both scanners. On scanner B, differences in lowest b-values chosen within the 0–500 s/mm² range for two-point ADC computation induced significant biases (56-109 × 10−6 mm²/s, P < 0.0001). ADC was significantly lower in the morning (bias: 33 × 10−6 mm²/s, P = 0.006). The number of b-values had little influence on ADC values. The lowest detectable ADC difference varied from 85 × 10−6 to 311 × 10−6 mm²/s across scanners, b-value combinations and periods of the day. ConclusionsThe MRI scanner, the lowest b-value used and the period of the day induce substantial variability in ADC computation.

P885: PROSPECTIVE ASSESSMENT OF MYELOMA TUMOUR BURDEN AND BONE DISEASE USING DW-MRI AND EXPLORATORY BONE BIOMARKERS

Background: Key clinical priorities for multiple myeloma (MM) are to reduce tumour burden and complications, of which lytic bone disease is the major cause of morbidity. To guide treatment, there is a pressing need for biomarkers that can accurately quantify MM tumour burden and associated bone disease. To this end, Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) and bone turnover markers are promising radiological and serum metrics, respectively, although their clinical value in prospective assessment is unclear. Aims: LOOMIS was a single-centre observational cohort study that evaluated the relative merits of DW-MRI and bone turnover markers in prospectively assessing tumour burden and bone disease when added to standard clinical assessment, in patients with MM and monoclonal gammopathy of undetermined significance (MGUS). Methods: A total of 67 patients were enrolled (14 newly diagnosed MM, 12 relapsed MM, 15 smouldering MM, 14 MGUS and 12 healthy volunteers) between March 2018 and March 2020. At baseline (and 6-month follow-up for MM/MGUS), participants had a DW-MRI scan and serum measurements of established (P1NP, CTX-1, ALP) and exploratory (DKK1, sclerostin, RANKL:OPG ratio) bone turnover markers. MM/MGUS patients additionally had standard myeloma bloods and Dual-Energy X-ray Absorptiometry (DXA) at each visit, as correlates of tumour burden and bone loss. DW-MRI scans were double reported by expert Radiologists for Apparent Diffusion Coefficient (ADC) measurements of lytic bone lesion(s), and Myeloma Response Assessment and Diagnosis System (MY-RADS) Response Assessment Category (RAC) scoring. Patients were classified by International Myeloma Working Group (IMWG) response criteria as a clinical correlate of therapy response. Results: On assessment of baseline tumour burden, there was no correlation between single lesion DW-MRI ADC and serum paraprotein [p>0.05]; however, there was moderate positive correlation between serum DKK1 and serum paraprotein [r=0.39, p=0.04]. At follow-up, radiological MY-RADS RAC scoring correlated with conventional IMWG response criteria [p=0.015]; additionally, longitudinal relative change in serum DKK1 differed between IMWG-defined therapy responders (37% decrease) and non-responders (15% increase) [p<0.01]. On baseline assessment of bone loss, there was moderate positive correlation between serum sclerostin and DXA bone mineral density at femoral neck [r=0.40, p<0.01] and lumbar spine [r=0.54, p<0.001]. At follow-up, there was a moderate negative correlation between longitudinal % change in the RANKL:OPG ratio and % change in DXA bone mineral density at femoral neck [r= -0.45, p<0.01]. Summary/Conclusion: Our prospective trial validates DW-MRI-based MY-RADS RAC scoring as a qualitative radiological tool to assess therapy response. Whilst previous work has supported single lytic lesion ADC measurements as a correlate of tumour volume, we did not find this; small sample size and prior chemotherapy in our study may have limited our ability to detect this. In comparison, serum bone turnover markers such as DKK1 may provide a more global measure to quantify myeloma burden both at baseline diagnosis and longitudinally with therapy. Additionally, our data highlight serum sclerostin and RANKL:OPG ratio as potential biomarkers to assess and monitor bone loss. Overall, our study highlights emerging radiological and serum biomarkers of tumour burden and associated bone loss in MM and MGUS, which merit further exploration alongside uniformly treated cohorts, to better understand their clinical utility.