Diffusion-weighted Research Articles

Automated Prediction of Early Recurrence in Advanced Sinonasal Squamous Cell Carcinoma With Deep Learning and Multi-parametric MRI-based Radiomics Nomogram

Preoperative prediction of the recurrence risk in patients with advanced sinonasal squamous cell carcinoma (SNSCC) is critical for individualized treatment. To evaluate the predictive ability of radiomics signature (RS) based on deep learning and multiparametric MRI for the risk of 2-year recurrence in advanced SNSCC. Preoperative MRI datasets were retrospectively collected from 265 SNSCC patients (145 recurrences) who underwent preoperative MRI, including T2-weighted (T2W), contrast-enhanced T1-weighted (T1c) sequences and diffusion-weighted (DW). All patients were divided into 165 training cohort and 70 test cohort. A deep learning segmentation model based on VB-Net was used to segment regions of interest (ROIs) for preoperative MRI and radiomics features were extracted from automatically segmented ROIs. Least absolute shrinkage and selection operator (LASSO) and logistic regression (LR) were applied for feature selection and radiomics score construction. Combined with meaningful clinicopathological predictors, a nomogram was developed and its performance was evaluated. In addition, X-title software was used to divide patients into high-risk or low-risk early relapse (ER) subgroups. Recurrence-free survival probability (RFS) was assessed for each subgroup. The radiomics score, T stage, histological grade and Ki-67 predictors were independent predictors. The segmentation models of T2WI, T1c, and apparent diffusion coefficient (ADC) sequences achieved Dice coefficients of 0.720, 0.727, and 0.756, respectively, in the test cohort. RS-T2, RS-T1c and RS-ADC were derived from single-parameter MRI. RS-Combined (combined with T2WI, T1c, and ADC features) was derived from multiparametric MRI and reached area under curve (AUC) and accuracy of 0.854 (0.749-0.927) and 74.3% (0.624-0.840), respectively, in the test cohort. The calibration curve and decision curve analysis (DCA) illustrate its value in clinical practice. Kaplan-Meier analysis showed that the 2-year RFS rate for low-risk patients was significantly greater than that for high-risk patients in both the training and testing cohorts (p < 0.001). Automated nomograms based on multi-sequence MRI help to predict ER in SNSCC patients preoperatively.

The investigation of reduced field-of-view diffusion-weighted imaging (DWI) in patients with nasopharyngeal carcinoma: comparison with conventional DWI

Field-of-view optimized and constrained undistorted single-shot imaging (FOCUS) is a new sequence that shows enhanced anatomical details, improving the diffusion-weighted (DW) images. To investigate the value of FOCUS diffusion-weighted imaging (DWI) in the evaluation of nasopharyngeal carcinoma (NPC) and compare it with the single-shot echo planner imaging (SS-EPI) DWI approach. A total of 87 patients with NPC underwent magnetic resonance imaging, including FOCUS and SS-EPI DWI sequences. The signal-to-noise ratio (SNR), signal-intensity ratio (SIR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values of the nasopharyngeal lesions were measured and compared. According to the clinical stages of patients, T and N were divided into early and advanced stage groups, respectively. The mean ADC values of the two techniques were computed, and the area under the curve (AUC) was estimated to calculate the diagnostic efficiency. Subjective and objective image qualitative values of FOCUS were significantly higher than those of SS-EPI. The ADC values for FOCUS of early T and N stages were significantly lower than those of the advanced stages. FOCUS provides significantly better image quality in NPC compared to SS-EPI, with lower ADC values for early-stage disease than late-stage disease.

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis.

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM). For LNM prediction, the radiomics model was constructed by SVM, and Multi-Omics Graph cOnvolutional NETworks (MOGONET) was used for the effective classification of multiradiomics data. Multivariable logistic regression incorporating multiradiomics signatures and clinical risk factors was used to generate a nomogram, whose performance and clinical utility were assessed. Results showed that the nine most predictive features were separately selected from US, T2WI, DWI, and CE-T1WI images, and 18 features were selected in the combined model. The combined radiomics model showed better performance than models based on US, T2WI, DWI, and CE-T1WI. In a comparison of the combined radiomics and MOGONET model, receiver operating curve analysis showed that the area under the curve (AUC) value (95% CI) was 0.84 (0.76-0.93) and 0.84 (0.71-0.96) for the MOGONET model in the training and validation cohorts, respectively. The corresponding values (95% CI) for the combined radiomics model were 0.82 (0.74-0.90) and 0.77 (0.61-0.94), respectively. The MOGONET model had better performance and better prediction specificity compared with the combined radiomics model. The nomogram including the MOGONET signature showed a better predictive value (AUC: 0.81 vs. 0.88) in the training and validation (AUC: 0.74vs. 0.87) cohorts, as compared with the clinical model. Calibration curves showed good agreement in both cohorts. The applicability of the clinical multimodal radiomics (CMR) nomogram in clinical settings was validated by decision curve analysis. In patients with PTC, the CMR nomogram could improve the prediction of cervical LNM preoperatively and may be helpful in clinical decision-making.

Simultaneous Mapping of Water Diffusion Coefficients and Metabolite Distributions of the Brain Using MR Spectroscopic Imaging without Water Suppression.

To simultaneously map water diffusion coefficients and metabolite distributions of the brain in magnetic resonance spectroscopic imaging (MRSI) experiments within a clinically feasible time. A diffusion-preparation module was introduced in water-unsuppressed MRSI acquisition sequence to generate diffusion weighting of the water signals. Fast spatiospectral encodings were achieved using echo-planar spectroscopic imaging readouts with blipped phase encodings for sparse sampling. Navigator signals were embedded in the data acquisition sequence, which were used for detection of data corrupted by physiological motion in the diffusion preparation period. In data processing, a novel model-based method was developed to effectively use sparse (k, t)-space spectroscopic signals for reconstruction of the spatial distributions of water diffusion coefficients and metabolite concentrations. Both phantom experiments and in vivo experiments were carried out to evaluate the feasibility and performance of the proposed method. In an 8-minute scan, diffusion weighted images and apparent diffusion coefficients map at 2.0×1.0×1.0 mm3 were obtained simultaneously with metabolite maps at 2.0×3.0×3.0 mm3 nominal resolution. We demonstrated the feasibility of using the unsuppressed water signals from MRSI experiments to map the water diffusion coefficients of brain tissues and proposed a novel method to achieve simultaneous mapping of water diffusion coefficients and metabolite distributions. The proposed method provides a unique imaging tool for simultaneous diffusion and metabolic imaging. This method is expected to be useful for various brain imaging applications.

Role of Diffusion-Weighted Magnetic Resonance Imaging for Characterization of Mediastinal Lymphadenopathy.

To assess the diagnostic performance of diffusion-weighted (DW) magnetic resonance imaging (MRI) in the characterization of mediastinal lymph nodes and compare them with morphological parameters. A total of 43 untreated patients with mediastinal lymphadenopathy underwent DW and T2 weighted MRI followed by pathological examination in the period from January 2015 to June 2016. The presence of diffusion restriction, apparent diffusion coefficient (ADC) value, short axis dimensions (SAD), and T2 heterogeneous signal intensity of the lymph nodes were evaluated using receiver operating characteristic curve (ROC) and forward step-wise multivariate logistic regression analysis. The ADC of malignant lymphadenopathy was significantly lower (0.873 ± 0.109 × 10-3 mm2/s) than that of benign lymphadenopathy (1.663 ± 0.311 × 10-3 mm2/s) (p = 0.001). When an ADC of 1.0955 × 10-3 mm2/s was used as a threshold value for differentiating malignant from benign nodes, the best results were obtained with a sensitivity of 94%, a specificity of 96%, and an area under the curve (AUC) of 0.996. A model combining the other three MRI criteria showed less sensitivity (88.9%) and specificity (92%) compared to the ADC-only model. The ADC was the strongest independent predictor of malignancy. The addition of other parameters failed to show any increase in sensitivity and specificity.

Apparent diffusion coefficients of 31P metabolites in the human calf muscle at 7 T

PurposeIn this study, we aimed to measure the apparent diffusion coefficients (ADCs) of major phosphorous metabolites in the human calf muscle at 7 T with a diffusion-weighted (DW)-STEAM sequence.MethodsA DW-STEAM sequence with bipolar gradients was implemented at 7 T, and DW MR spectra were acquired in three orthogonal directions in the human calf muscle of six healthy volunteers (TE/TM/TR = 15 ms/750 ms/5 s) at three b-values (0, 800, and 1200 s/mm2). Frequency and phase alignments were applied prior to spectral averaging. Averaged DW MR spectra were analyzed with LCModel, and ADCs of 31P metabolites were estimated.ResultsFour metabolites (phosphocreatine (PCr), adenosine triphosphate (ATP), inorganic phosphate (Pi) and glycerol phosphorylcholine (GPC)) were quantified at all b-values with mean CRLBs below 10%. The ADC values of PCr, ATP, Pi, and GPC were (0.24 ± 0.02, 0.15 ± 0.04, 0.43 ± 0.14, 0.40 ± 0.09) × 10–3 mm2/s, respectively.ConclusionThe ADCs of four 31P metabolites were successfully measured in the human calf muscle at 7 T, among which those of ATP, Pi and GPC were reported for the first time in humans. This study paves the way to investigate 31P metabolite diffusion properties in health and disease on the clinical MR scanner.

Value of diffusion‐weighted MRI and lesion‐to‐spinal cord signal intensity ratio in pulmonary lesion characterization

BackgroundIn the scenario of lung lesions, the differential diagnosis is important, since the treatment is determined by the characteristics of the lesion. The goal in the evaluation of pulmonary lesions is to distinguish malignant lesions from benign lesions in a non-invasive manner as possible. Since, CT is not sufficient to accurately distinguish malignant nodules from benign nodules and patients with benign nodules might undergo invasive diagnostic methods, such as lung biopsy or video-assisted thoracoscopic surgery, to rule out a malignancy. Now, MRI performed by using diffusion-weighted (DW) can offer both qualitative and quantitative information that can be helpful for tumour assessment. Moreover, lesion‐to‐spinal cord signal intensity ratio (LSR) has also been shown to be useful for the differentiation of lung lesions. Quantitative tumour assessment is possible by the calculation of ADC.ResultsA total of 30 patients were eligible for inclusion in our final analysis; with male/female case number about 10/20 (33.3%/ 66.7%) and age range from 20 to 74 (46.8 ± 14.9) were subjected to MRI study and MRI diffusion. Sensitivity analysis showed that ADC mean, and ADC min value can significantly predict malignant lung lesions using cutoff point < 1.53 and < 1.34 respectively, with sensitivity 75%, 56.3%, and specificity 92.9%, 100% with p values 0.001, and 0.005 respectively. SI lesion can significantly predict malignant lung lesions using cutoff point > 502.8, with sensitivity 92.9% and specificity 68.7%, AUC 89.3% and p value 0.0001. Lesion-to-spinal cord signal intensity ratio (LSR) can significantly predict malignant lung lesions using cutoff point > 1.3, with sensitivity 85.7% and specificity 75%, AUC 79.7% and p value 0.006.ConclusionsThis study confirmed that the DWI combined with ADC value and LSR is effective and valuable tool in differentiation of pulmonary lesions whether benign or malignant which is considered to be noninvasive alternative tool for the characterization of pulmonary lesions. We recommend before invasive intervention to perform diffusion MRI and LSR as and important aid for proper diagnosis.

Accuracy of Diffusion Weighted Imaging in the diagnosis and evaluation of Acute Ischemic Strokes

Objective: To assess the accuracy of application of diffusion weighted imaging in the diagnosis and evaluation of acute onset ischemic strokes. Study Design: Cross sectional validation study. Place and Duration: Department of Diagnostic Radiology, Mardan Medical Complex, Hospital, Mardan from 15th October 2020 to 15th April 2021. Methodology: Patients whose presentation was highly suggestive of acute stroke, were undergone a non-contrast Computed tomography scan of the brain immediately by Asteion VP single slice. Those found negative for acute hemorrhage on Computed tomography images were subjected to Magnetic resonance imaging on Achieva 1.5 Tesla. Diffusion-weighted imaging technique of MRI scan was done in addition to the conventional T1W, T2W, and FLAIR scans of MRI which were also done. DWI was performed as early as possible not later than 24 hours after symptoms onset. Both DWI imaging technique and conventional routine T1W, T2W and FLAIR scans of MRI were repeated after 7 days. Results: The mean age of the sample was 57.6 + 5.9 years. On Diffusion-weighted imaging, stroke was observed in 60.2% of patients. Later on follow-up conventional magnetic resonance imaging scans were done after 7 days, stroke was recorded in 69.9% of patients confirming the diagnostic accuracy of DWI imaging in sub-acute stroke in early diagnosis. Conclusion: Conventional MRI scans like T1W, T2W and FLAIR have diagnostic accuracy only after some days. It has poor diagnostic accuracy in early onset sub-acute ischemic strokes. On the other hand, DWI imaging scans of MRI can be a useful tool for early detection of ischemic strokes as it diagnosed stroke in 60.2% of patients which were later confirmed by conventional MRI scans done after 7 days. Conventional MRI scans have high accuracy of detection of strokes but only after some days. So DW1 imaging may be applied for early diagnosis of strokes in sub-acute onset strokes. Keywords: Ischemic stroke, Magnetic Resonance Imaging, Diffusion Weighted Imaging, Hemorrhage, Computed Tomography How to Cite This: Afridi SQ, Baig H, Janan Z, Begum T, Shuaib M. Accuracy of diffusion-weighted imaging in the diagnosis and Evaluation of acute ischemic strokes. Isra Med J. 2022; 14(3): 99-103. DOI: https://doi.org/10.55282/imj.oa1314

A New Method for Classifying Intracerebral Hemorrhage (ICH) Based on Diffusion Weighted –Magnetic Resonance Imaging (DW-MRI)

A New Method for Classifying Intracerebral Hemorrhage (ICH) Based on Diffusion Weighted –Magnetic Resonance Imaging (DW-MRI)

Multiparametric magnetic resonance imaging for radiation therapy response monitoring in soft tissue sarcomas: a histology and MRI co-registration algorithm.

Rationale: To establish a spatially exact co-registration procedure between in vivo multiparametric magnetic resonance imaging (mpMRI) and (immuno)histopathology of soft tissue sarcomas (STS) to identify imaging parameters that reflect radiation therapy response of STS. Methods: The mpMRI-Protocol included diffusion-weighted (DWI), intravoxel-incoherent motion (IVIM), and dynamic contrast-enhancing (DCE) imaging. The resection specimen was embedded in 6.5% agarose after initial fixation in formalin. To ensure identical alignment of histopathological sectioning and in vivo imaging, an ex vivo MRI scan of the specimen was rigidly co-registered with the in vivo mpMRI. The deviating angulation of the specimen to the in vivo location of the tumor was determined. The agarose block was trimmed accordingly. A second ex vivo MRI in a dedicated localizer with a 4 mm grid was performed, which was matched to a custom-built sectioning machine. Microtomy sections were stained with hematoxylin and eosin. Immunohistochemical staining was performed with anti-ALDH1A1 antibodies as a radioresistance and anti-MIB1 antibodies as a proliferation marker. Fusion of the digitized microtomy sections with the in vivo mpMRI was accomplished through nonrigid co-registration to the in vivo mpMRI. Co-registration accuracy was qualitatively assessed by visual assessment and quantitatively evaluated by computing target registration errors (TRE). Results: The study sample comprised nine tumor sections from three STS patients. Visual assessment after nonrigid co-registration showed a strong morphological correlation of the histopathological specimens with ex vivo MRI and in vivo mpMRI after neoadjuvant radiation therapy. Quantitative assessment of the co-registration procedure using TRE analysis of different pairs of pathology and MRI sections revealed highly accurate structural alignment, with a total median TRE of 2.25 mm (histology - ex vivo MRI), 2.22 mm (histology - in vivo mpMRI), and 2.02 mm (ex vivo MRI - in vivo mpMRI). There was no significant difference between TREs of the different pairs of sections or caudal, middle, and cranial tumor parts, respectively. Conclusion: Our initial results show a promising approach to obtaining accurate co-registration between histopathology and in vivo MRI for STS. In a larger cohort of patients, the method established here will enable the prospective identification and validation of in vivo imaging biomarkers for radiation therapy response prediction and monitoring in STS patients via precise molecular and cellular correlation.

Standardized preprocessed derivatives for the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) Study

AbstractBackgroundThe Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) cohort of the pan‐Canadian Consortium on Neurodegeneration in Aging (CCNA) provides imaging on participants following a standardized protocol. This imaging contribution to deep phenotyping is done to study the full spectrum of age‐related dementias in more than 1,100 individuals (50‐90y) with subjective or mild cognitive impairment, Alzheimer’s disease, other dementias, or otherwise cognitively unimpaired. To accelerate discovery, we propose to release biomarkers extracted from these acquisitions. Here we present preliminary (N=385, AD=39) preprocessing methods, quality control, and available derivatives of the resting‐state functional (rsfMRI), diffusion weighted (DWI), and structural magnetic resonance images.MethodfMRI data was preprocessed using fMRIprep v20.2.1. Sørensen–Dice similarity measure was computed between individual masks and group templates using our internal BIDS app. Functional connectome of 101 regions from Dictionary of Functional Modes (DiFuMo) 64 dimension atlas were calculated with confounds removed. Mean network connectivity for the Yeo7 networks was summarized from connectomes. DWI data underwent robust quality control and preprocessing using Tractoflow. Bundle extraction and mean metric computation was done using freewater_flow, rbx_flow and tractometry_flow. Structural scans were preprocessed and segmented using iterativeN3 and MAGeT‐brain to obtain subcortical and cerebellar volumes. As a validation, a subset of variables associated with aging in the literature was tested for association with participant age using simple correlation.ResultThe functional Dice score was 0.915 (SD=0.017, N=390) and structural was 0.988 (SD=0.004, N=381). Age was significantly associated with mean DMN connectivity (r=‐0.226, p&lt;0.001), bilateral inferior fronto‐occipital fasciculus freewater (r=0.533, p&lt;0.001), and bilateral thalamus volume (r=‐0.243, p&lt;0.001).ConclusionDerivatives obtained include: functional connectomes using DiFuMo64, network connectivity from Yeo7, DWI measures for major fiber tracts, and segmented subcortical and cerebellar volumes. The results of the quality and validity checks indicate the derivatives would be useful for the study of age‐related dementias. Full quality control and release of the complete COMPASS‐ND preprocessed imaging dataset and derivatives should be completed in 2022. For information on access see ccna‐ccnv.ca.

Detection of bone marrow metastases in children and young adults with solid cancers with diffusion-weighted MRI.

To compare the diagnostic accuracy of diffusion-weighted (DW)-MRI with b-values of 50s/mm2 and 800s/mm2 for the detection of bone marrow metastases in children and young adults with solid malignancies. In an institutional review board-approved prospective study, we performed 51 whole-body DW-MRI scans in 19 children and young adults (14 males, 5 females; age range: 1-25years) with metastasized cancers before (n = 19 scans) and after (n = 32 scans) chemotherapy. Two readers determined the presence of focal bone marrow lesions in 10 anatomical areas. A third reader measured ADC and SNR of focal lesions and normal marrow. Simultaneously acquired 18F-FDG-PET scans served as the standard of reference. Data of b = 50s/mm2 and 800s/mm2 images were compared with the Wilcoxon signed-rank test. Inter-reader agreement was evaluated with weighted kappa statistics. The SNR of bone marrow metastases was significantly higher compared to normal bone marrow on b = 50s/mm2 (mean ± SD: 978.436 ± 1239.436 vs. 108.881 ± 109.813, p < 0.001) and b = 800s/mm2 DW-MRI (499.638 ± 612.721 vs. 86.280 ± 89.120; p < 0.001). On 30 out of 32 post-treatment DW-MRI scans, reconverted marrow demonstrated low signal with low ADC values (0.385 × 10-3 ± 0.168 × 10-3mm2/s). The same number of metastases (556/588; 94.6%; p > 0.99) was detected on b = 50s/mm2 and 800s/mm2 images. However, both normal marrow and metastases exhibited low signals on ADC maps, limiting the ability to delineate metastases. The inter-reader agreement was substantial, with a weighted kappa of 0.783 and 0.778, respectively. Bone marrow metastases in children and young adults can be equally well detected on b = 50s/mm2 and 800s/mm2 images, but ADC values can be misleading.

Preoperative identification of cytokeratin 19 status of hepatocellular carcinoma based on diffusion kurtosis imaging.

To explore the potential value of diffusion kurtosis imaging (DKI) for identification of cytokeratin 19 (CK19) status of HCCs. This study was approved by the local institute review board and written informed consent was obtained. 73 patients with pathologically confirmed HCCs were included in this prospective study. All the diffusion-weighted (DW) images were acquired using a 3.0-T MR scanner with 4 b-values (0, 800, 1500 and 2000s/mm2). The mean diffusion value (MD) and mean kurtosis coefficient (MK) from DKI, apparent diffusion coefficient (ADC) from DW imaging (b = 0, 500s/mm2), and tumor-to-liver signal intensity ratios on ADC map (SIRADC) and DW images with b-value of 500s/mm2 (SIRb500) were calculated and compared between CK19-positive (n = 23) and CK19-negative (n = 50) HCC groups. Univariate and multivariate logistic regression analyses were used to identify risk factors for the positive expression of CK19. Increased a-fetoprotein level (p = 0.021) and SIRb500 (p = 0.006) and decreased ADC (p = 0.021) and MD (p < 0.001) were significantly correlated with CK19-positive HCCs at univariate analysis. Decreased MD value (odds ratio: 0.042, p = 0.002) and a-fetoprotein level (odds ratio: 5.139, p = 0.015) were the independent risk factors for CK19-positive HCCs at multivariate analysis. The area under the curve of MD value by receiver operating characteristic analysis was 0.823 with a sensitivity of 86.96% and a specificity of 76% for the prediction of CK19-positive HCCs. The decreased MD value derived from DKI is potential quantitative biomarker for predicting CK19-positive HCCs.

Motion-robust, blood-suppressed, reduced-distortion diffusion MRI of the liver.

To evaluate feasibility and reproducibility of liver diffusion-weighted (DW) MRI using cardiac-motion-robust, blood-suppressed, reduced-distortion techniques. DW-MRI data were acquired at 3T in an anatomically accurate liver phantom including controlled pulsatile motion, in eight healthy volunteers and four patients with known or suspected liver metastases. Standard monopolar and motion-robust (M1-nulled, and M1-optimized) DW gradient waveforms were each acquired with single-shot echo-planar imaging (ssEPI) and multishot EPI (msEPI). In the motion phantom, apparent diffusion coefficient (ADC) was measured in the motion-affected volume. In healthy volunteers, ADC was measured in the left and right liver lobes separately to evaluate ADC reproducibility between the two lobes. Image distortions were quantified using the normalized cross-correlation coefficient, with an undistorted T2-weighted reference. In the motion phantom, ADC mean and SD in motion-affected volumes substantially increased with increasing motion for monopolar waveforms. ADC remained stable in the presence of increasing motion when using motion-robust waveforms. M1-optimized waveforms suppressed slow flow signal present with M1-nulled waveforms. In healthy volunteers, monopolar waveforms generated significantly different ADC measurements between left and right liver lobes ( , reproducibility coefficients (RPC)= mm /s for monopolar-msEPI), while M1-optimized waveforms showed more reproducible ADC values ( , mm /s for M1-optimized-msEPI). In phantom and healthy volunteer studies, motion-robust acquisitions with msEPI showed significantly reduced image distortion ( ) compared to ssEPI. Patient scans showed reduction of wormhole artifacts when combining M1-optimized waveforms with msEPI. Synergistic effects of combined M1-optimized diffusion waveforms and msEPI acquisitions enable reproducible liver DWI with motion robustness, blood signal suppression, and reduced distortion.

Intravoxel incoherent motion (IVIM) MRI in pediatric patients with synovitis of the knee joint: a prospective pilot study

BackgroundDiagnosing synovial inflammation by administration of gadolinium-based contrast agents is limited by invasiveness and possible side effects, especially in children and adolescents.PurposeWe investigated diagnostic accuracy of diffusion-weighted (DWI) MRI with intravoxel incoherent motion (IVIM) imaging compared to contrast-enhanced MRI for detecting synovitis of the knee in a population of pediatrics and young adults. In addition we compared quantitative measures of synovial diffusion and perfusion to a group of healthy volunteers.MethodsIn this prospective study, 8 pediatric patients with 10 symptomatic knees (6 girls and 2 boys, mean age 13 years) with known or suspected synovitis underwent pre- and post-contrast 3.0 T MRI of the knee joint and additional DWI sequences between October 2016 and July 2019. For comparison we enrolled 5 healthy young adults (2 women and 3 men, median age 27 years) with contrast-free MRI of both knees. Post-contrast T1w images and DWI images at b = 1000s/mm2 with apparent diffusion coefficient (ADC) maps of patients were separately rated by two independent and blinded readers with different levels of experience for the presence or absence and degree of synovitis along with the level of confidence. We measured signal intensity on DWI of synovium, joint effusion and muscle with regions of interests and calculated the IVIM-parameters tissue diffusion coefficient (D) and perfusion fraction (f) for patients and volunteers.ResultsAll patients showed at least some synovial contrast enhancement, 8 (80%) children knees were diagnosed with synovitis on contrast-enhanced (= ce)-T1w, the diagnostic standard. Ratings by the first and second reader on ce-T1w and DWI showed full agreement (kappa = 1) in diagnosing synovitis and substantial agreement (k = 0,655) for the degree of synovial enhancement. Interobserver agreement on DWI showed fair agreement (k = 0,220) between both readers. Diagnostic confidence was lower on DWI. Mean D- and f-values of muscle was comparable between patients and volunteers. Effusion mean D was higher, mean f was lower, synovial mean D was lower, mean f higher in patients than in volunteers. All differences were statistically significant (p < 0.001).ConclusionsDiffusion-weighted MRI with IVIM imaging remains a promising, though reader-dependent alternative to i.v. contrast-enhanced imaging in pediatric patients to reliably diagnose, or rule out, synovitis of the knee joint. We detected significantly restricted synovial diffusion and increased perfusion in patients compared to healthy volunteers.Trial registrationEthical Comitee University Hospital Ulm, Nr. 320/16.

Intra-Treatment Tumor Apparent Diffusion Coefficient, a Quantitative Imaging Metric, is Associated with Neck Nodal Recurrence in De-Escalated Treatment of HPV-Positive Oropharyngeal Cancer (OPC)

<h3>Purpose/Objective(s)</h3> De-escalation strategies for the treatment of HPV-associated OPC show promise for effective, less toxic treatment. However, identifying accurate markers of more aggressive subsets of HPV OPC remains challenging. The 30 Reduction in Radiation for OPC (ROC) trial prospectively used intra-treatment ¹⁸F-FMISO imaging to selectively de-escalate patients to 30Gy chemoradiotherapy, however, a subset of patients still developed nodal recurrence. We hypothesized that diffusion-weighted (DW) MRI-derived quantitative imaging metrics, such as apparent diffusion coefficient (ADC), a surrogate marker of tumor cellularity based on water diffusion patterns, might help identify patients at high risk of recurrence and enable broader use of de-escalation strategies<b>.</b> <h3>Materials/Methods</h3> The 30 ROC trial enrolled patients with p16-positive OPC, cT0-2, N1-2c (AJCC 7^th ed). All patients had pre-treatment ¹⁸F-FMISO (fluoromisonidazole) PET scan and those with baseline nodal hypoxia underwent a 2^nd intra-treatment scan. All patients underwent primary site surgery where negative margin was not required. All patients had gross neck nodal disease. Those with intra-treatment resolution of nodal hypoxia or without initial hypoxia were de-escalated to 30Gy (non-hypoxic group) with 2 cycles of concurrent chemotherapy, while those with persistent radiographic hypoxia (hypoxic group) were treated to 70Gy. Standard T1, T2 weighted, and multiple b-value DW-MRI data were acquired pre-treatment and weekly during the first 4 weeks of treatment. Two radiation oncologists delineated nodal tumor regions of interest (ROIs) in a blinded fashion with ITK-SNAP on DW images (b= 0 s/mm²). Multiple b-value DW data were fitted to a monoexponential model to calculate ADC (mm²/s). The data analysis was performed on ROIs and voxel-wise using the in-house developed tool MRI-QAMPER. Standard statistical analysis was performed using MRI and clinical response data based on RECISTv1.1 provided by a radiologist. <h3>Results</h3> 158 patients were enrolled, of whom 95 had pre-treatment DW-MRI data available with tumor ROI with ADC values. Based on overall ¹⁸F-FMISO imaging, 12.6% (12/95) exhibited persistent hypoxia and 87.4% (83/95) had resolved/no hypoxia. All patients with nodal recurrences were in the de-escalated non-hypoxic group (8/83). Pre-treatment ADC was not different between overall hypoxic and non-hypoxic groups. Among de-escalated patients, those who developed nodal recurrence exhibited significantly different intra-treatment ADC at week 3 (before completing 30Gy) relative to those who did not recur (P<0.05, Wilcoxon rank-sum test). <h3>Conclusion</h3> The quantitative imaging metric, ADC, reflects both the restricted and hindered Brownian motion of water molecules in tumor tissue. Thus, ADC may be a useful intra-treatment marker to identify patients at risk for nodal recurrence to benefit from the incorporation of an upfront planned neck dissection after 30Gy as part of the de-escalation strategy.

A Comparison of Modalities to Differentiate Radiation Necrosis from Tumor Progression: A Diagnostic Meta-Analysis

<h3>Purpose/Objective(s)</h3> Cerebral radiation necrosis is a complication following radiation treatment to the brain. It is hypothesized that radiation treatment causes vascular injury, leading to tissue ischemia and then radiation necrosis. Radiation necrosis is a delayed phenomenon, occurring several months to years after the completion of radiation therapy. Radiation necrosis can be difficult to diagnose as it appears similar to tumor progression on standard magnetic resonance imaging (MRI). The ability to distinguish the two is important for further treatment strategies, and there is no current guideline on which imaging modality should be used. Various imaging modalities have been studied as an alternative to MRI, including, but not limited to, MR perfusion techniques (MRP), MR spectroscopy (MRS), single photon emission computed tomography (SPECT), and positron emission tomography (PET). We aim to review the existing literature and perform a diagnostic meta-analysis comparing these different imaging modalities to differentiate radiation necrosis from tumor progression. <h3>Materials/Methods</h3> A systematic review adherent to PRISMA guidelines was performed using Scopus and PubMed databases. Sensitivities and specificities were pooled using the inverse-variance method, and 95% confidence intervals were calculated. To compare modalities, Euclidean distances are calculated as the absolute distance from the point (1.0, 1.0) of a theoretical ideal classifier on a graph of sensitivity vs. specificity. For evaluation of Euclidean distance, the lower the value, the closer the test is to optimal, which would be a sensitivity and specificity of 1. <h3>Results</h3> The analysis includes 113 studies with a total of 200 imaging data points, including the following imaging modalities: MRI (n = 13), MRS (n = 21), MRP (n = 12), Dynamic Contrast Enhanced (DCE) MRI (n = 4), Dynamic Susceptibility Contrast MRI (n = 20), MR arterial spin labeling (ASL) (n = 3), Diffusion Weighted Imaging (n = 11), Diffusion Tensor Imaging (DTI) (n = 2), PET (n = 88), and SPECT (n = 26). MRS had the highest pooled sensitivity at 0.92 (95% CI: 0.84 - 0.96), followed by DCE MRI (0.88; 95% CI: 0.70 - 0.96) and then SPECT (0.88; 95% CI: 0.82 - 0.93). The highest pooled specificities were DTI at 0.90 (95% CI: 0.69 - 0.98), SPECT at 0.88 (95% CI: 0.83 - 0.92), and DCE MRI at 0.85 (95% CI: 0.71 - 0.93). For Euclidean distances, SPECT had the lowest at 0.163 (95% CI: 0.106 - 0.248), followed by MRS (0.167; 95% CI: 0.100 - 0.275), and DCE MRI (0.185; 95% CI: 0.077 - 0.414). MRI had the highest Euclidean distance at 0.373 (95% CI: 0.238 - 0.542). <h3>Conclusion</h3> The results from this diagnostic meta-analysis evaluating pooled sensitivities, pooled specificities, and Euclidean distances indicate that SPECT and MRS appear to be promising imaging modalities for the differentiation of radiation necrosis from tumor progression. This study may have implications in the formation of imaging guidelines for this purpose.

Added value of 3T MRI and the MRI-halo sign in assessing resectability of locally advanced pancreatic cancer following induction chemotherapy (IMAGE-MRI): prospective pilot study

BackgroundRestaging of locally advanced pancreatic cancer (LAPC) after induction chemotherapy using contrast-enhanced computed tomography (CE-CT) imaging is imprecise in evaluating local tumor response. This study explored the value of 3 Tesla (3 T) contrast-enhanced (CE) and diffusion-weighted (DWI) magnetic resonance imaging (MRI) for local tumor restaging.MethodsThis is a prospective pilot study including 20 consecutive patients with LAPC with RECIST non-progressive disease on CE-CT after induction chemotherapy. Restaging CE-CT, CE-MRI, and DWI-MRI were retrospectively evaluated by two abdominal radiologists in consensus, scoring tumor size and vascular involvement. A halo sign was defined as replacement of solid perivascular (arterial and venous) tumor tissue by a zone of fatty-like signal intensity.ResultsAdequate MRI was obtained in 19 patients with LAPC after induction chemotherapy. Tumor diameter was non-significantly smaller on CE-MRI compared to CE-CT (26 mm vs. 30 mm; p = 0.073). An MRI-halo sign was seen on CE-MRI in 52.6% (n = 10/19), whereas a CT-halo sign was seen in 10.5% (n = 2/19) of patients (p = 0.016). An MRI-halo sign was not associated with resection rate (60.0% vs. 62.5%; p = 1.000). In the resection cohort, patients with an MRI-halo sign had a non-significant increased R0 resection rate as compared to patients without an MRI-halo sign (66.7% vs. 20.0%; p = 0.242). Positive and negative predictive values of the CE-MRI-halo sign for R0 resection were 66.7% and 66.7%, respectively.Conclusions3 T CE-MRI and the MRI-halo sign might be helpful to assess the effect of induction chemotherapy in patients with LAPC, but its diagnostic accuracy has to be evaluated in larger series.

Rapid Diffusion Magnetic Resonance Imaging Using Slice-Interleaved Encoding.

In this paper, we present a robust reconstruction scheme for diffusion MRI (dMRI) data acquired using slice-interleaved diffusion encoding (SIDE). When combined with SIDE undersampling and simultaneous multi-slice (SMS) imaging, our reconstruction strategy is capable of significantly reducing the amount of data that needs to be acquired, enabling high-speed diffusion imaging for pediatric, elderly, and claustrophobic individuals. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume per diffusion wavevector, SIDE acquires in each repetition time (TR) a volume that consists of interleaved slice groups, each group corresponding to a different diffusion wavevector. This strategy allows SIDE to rapidly acquire data covering a large number of wavevectors within a short period of time. The proposed reconstruction method uses a diffusion spectrum model and multi-dimensional total variation to recover full DW images from DW volumes that are slice-undersampled due to unacquired SIDE volumes. We formulate an inverse problem that can be solved efficiently using the alternating direction method of multipliers (ADMM). Experiment results demonstrate that DW images can be reconstructed with high fidelity even when the acquisition is accelerated by 25 folds.

MP-PCA denoising for diffusion MRS data: promises and pitfalls

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4 T in rat brain and at 3 T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.