How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

PURPOSE

Further acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge.

METHODS

The effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis. ADC bias was assessed by Lin's Concordance correlation coefficient (CCC) followed by bootstrapping to calculate confidence intervals (CI). ADC random measurement error (RME) was assessed by the mean coefficient of variation (CV¯) and non-parametric statistical tests.

RESULTS

The simulations predicted increasingly negative bias and loss of precision towards lower SNR. These effects were confirmed in phantom measurements of increasing acceleration, for which CCC decreased from 0.947 to 0.279 and CV¯ increased from 0.043 to 0.439, and of decreasing flip angle, for which CCC decreased from 0.990 to 0.063 and CV¯ increased from 0.037 to 0.508. At high acceleration and low flip angle, C-SENSE AI reconstruction yielded best denoised ADC maps. For the lowest investigated flip angle, CCC = {0.630, 0.771 and 0.987} and CV¯={0.508, 0.426 and 0.254} were obtained for {SENSE, C-SENSE, C-SENSE AI}, the improvement by C-SENSE AI being significant as compared to the other methods (CV: p = 0.033 for C-SENSE AI vs. C-SENSE and p < 0.001 for C-SENSE AI vs. SENSE; CCC: non-overlapping CI between reconstruction methods). For the highest investigated acceleration factor, CCC = {0.479,0.926,0.960} and CV¯={0.519,0.119,0.118} were found, confirming the reduction of bias and RME by C-SENSE AI as compared to C-SENSE (by trend) and to SENSE (CV: p < 0.001; CCC: non-overlapping CI).

CONCLUSION

ADC bias and random measurement error in DWI at low SNR, typically associated with scan acceleration, can be effectively reduced by deep-learning based C-SENSE AI reconstruction.

Multi-modal 3-Dimensional Visualization of Pediatric Neuroblastoma: Aiding Surgical Planning Beyond Anatomical Information

BACKGROUND

Patient-specific 3D models of neuroblastoma and relevant anatomy are useful tools for surgical planning. However, these models do not represent the heterogenous biology of neuroblastoma. This heterogeneity is visualized with the ADC and 123I-MIGB-SPECT-CT imaging. Combining these multi-modal data into preoperative 3D heatmaps, may allow differentiation of the areas of vital and non-vital tumor tissue. We developed a workflow to create multi-modal preoperative 3D models for neuroblastoma surgery.

METHODS

We included 7 patients who underwent neuroblastoma surgery between 2022 and 2023. We developed 3D models based on the contrast enhanced T1-weighted MRI scans. Subsequently, we aligned the corresponding ADC and 123I-MIBG-SPECT-CT images using rigid transformation. We estimated registration precision using the Dice score and the target registration error (TRE). 3D heatmaps were computed based on ADC and 123I-MIBG uptake.

RESULTS

The registration algorithm had a median Dice score of 0.81 (0.75-0.90) for ADC and 0.77 (0.65-0.91) for 123I-MIBG-SPECT. For the ADC registration, the median TRE of renal vessels was 4.90 mm (0.86-10.18) and of the aorta 4.67 mm (1.59-12.20). For the 123I -MIBG-SPECT imaging the TRE of the renal vessels was 5.52 mm (1.71-10.97) and 5.28 mm (3.33-16.77) for the aorta.

CONCLUSIONS

We successfully developed a registration workflow to create multi-modal 3D models which allows the surgeon to visualize the tumor and its biological behavior in relation to the surrounding tissue. Future research will include linking of pathological results to imaging data, to validate these multi-modal 3D models.

LEVEL OF EVIDENCE

Level IV.

TYPE OF STUDY

Clinical Research.

Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC)

PURPOSE

To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers.

METHODS

This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63-83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant.

RESULTS

In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177).

CONCLUSION

In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.

Delivering a Quantitative Imaging Agenda

In a digital image, each voxel contains quantitative information dependent on the technique used to generate the image [...].

Direct jet coaxial electrospinning of axon-mimicking fibers for diffusion tensor imaging

Hollow polymer microfibers with variable microstructural and hydrophilic properties were proposed as building elements to create axon-mimicking phantoms for validation of diffusion tensor imaging (DTI). The axon-mimicking microfibers were fabricated in a mm-thick 3D anisotropic fiber strip, by direct jet coaxial electrospinning of PCL/polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide (PEO) as core. Hydrophilic PCL-PSi fiber strips were first obtained by carefully selecting appropriate solvents for the core and appropriate fiber collector rotating and transverse speeds. The porous cross-section and anisotropic orientation of axon-mimicking fibers were then quantitatively evaluated using two ImageJ plugins-nearest distance (ND) and directionality based on their scanning electron microscopy (SEM) images. Third, axon-mimicking phantom was constructed from PCL-PSi fiber strips with variable porous-section and fiber orientation and tested on a 3T clinical MR scanner. The relationship between DTI measurements (mean diffusivity [MD] and fractional anisotropy [FA]) of phantom samples and their pore size and fiber orientation was investigated. Two key microstructural parameters of axon-mimicking phantoms including normalized pore distance and dispersion of fiber orientation could well interpret the variations in DTI measurements. Two PCL-PSi phantom samples made from different regions of the same fiber strips were found to have similar MD and FA values, indicating that the direct jet coaxial electrospun fiber strips had consistent microstructure. More importantly, the MD and FA values of the developed axon-mimicking phantoms were mostly in the biologically relevant range.

Distinguishing mesorectal tumor deposits from metastatic lymph nodes by using diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging in rectal cancer

OBJECTIVES

This study aimed to identify whether apparent diffusion coefficient (ADC) values and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are helpful in distinguishing mesorectal tumor deposits (TD) from metastatic lymph nodes (MLN) in rectal cancer (RC).

METHODS

Thirty patients (59 lesions, including 30 TD and 29 MLN) with RC who underwent pretreatment-MRI between February 2016 and August 2018 were enrolled. The morphological features, ADC values, and semi-quantitative parameters of DCE-MRI, including relative enhancement (RE), maximum enhancement (ME), maximum relative enhancement (MRE), time to peak (TTP), wash-in rates (WIR), wash-out rates (WOR), brevity of enhancement (BRE), and area under the curve (AUC) were measured on lesions (TD or MLN) and RC. The parameters were compared between TD and MLN, tumor with and without TD group by using Fisher's exact test, independent-samples t-test, and Mann-Whitney U test. The ratio (lesion-to-tumor) of the parameters was compared between TD and MLN. Receiver operating characteristic curve analysis and binary logistic regression analysis were used to assess the diagnostic ability of single and combined metrics for distinguishing TD from MLN.

RESULTS

The morphological features, including size, shape, and border, were significantly different between TD and MLN. TD exhibited significantly lower RE, MRE, RE-ratio, MRE-ratio, ADC_min-ratio, and ADC_mean-ratio than MLN. RE-ratio showed the highest AUC (0.749) and accuracy (77.97%) among single parameters. The combination of DCE-MRI and DWI parameters together showed higher diagnostic efficiency (AUC = 0.825).

CONCLUSIONS

Morphological features, ADC values, and DCE-MRI parameters can preoperatively help distinguish TD from MLN in RC.

KEY POINTS

• DWI and DCE-MRI can facilitate early detection and distinguishing mesorectal TD (tumor deposits) from MLN (metastatic lymph nodes) in rectal cancer preoperatively. • TD has some specific morphological features, including relatively larger size, lower short- to long-axis ratio, irregular shape, and ill-defined border on T2-weighted MR images in rectal cancer. • The combination of ADC values and semi-quantitative parameters of DCE-MRI (RE, MRE) can help to improve the diagnostic efficiency of TD in rectal cancer.

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

Background

Modic 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.

Methods

We 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).

Results

The 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%).

Conclusions

The 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05610-4.

Temporal and sequence-related variability in diffusion-weighted imaging of presumed cerebrovascular accidents in the dog brain

Diffusion-weighted MRI (DWI) is often used to guide clinical interpretation of intraparenchymal brain lesions when there is suspicion for a cerebrovascular accident (CVA). Despite widespread evidence that imaging and patient parameters can influence diffusion-weighted measurements, such as apparent diffusion coefficient (ADC), there is little published data on such measurements for naturally occurring CVA in clinical cases in dogs. We describe a series of 22 presumed and confirmed spontaneous canine CVA with known time of clinical onset imaged on a single 3T magnet between 2011 and 2021. Median ADC values of < 1.0x10⁻³ mm²/s were seen in normal control tissues as well as within CVAs. Absolute and relative ADC values in CVAs were well-correlated (R² = 0.82). Absolute ADC values < 1.0x10⁻³ mm²/s prevailed within ischemic CVAs, though there were exceptions, including some lesions of < 5 days age. Some lesions showed reduced absolute but not relative ADC values when compared to matched normal contralateral tissue. CVAs with large hemorrhagic components did not show restricted diffusion. Variation in the DWI sequence used impacted the ADC values obtained. Failure to identify a region of ADC < 1.0x10⁻³ mm²/s should not exclude CVA from the differential list when clinical suspicion is high.

Comparison of TGSE-BLADE DWI, RESOLVE DWI, and SS-EPI DWI in healthy volunteers and patients after cerebral aneurysm clipping

Diffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air-bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip.

Local ablation of hepatocellular carcinoma by interstitial brachytherapy: prediction of outcome by diffusion-weighted imaging

BACKGROUND

Interstitial brachytherapy (iBT) has become a viable treatment option in the therapy of early and intermediate stage hepatocellular carcinoma (HCC). Prognostic imaging tools to predict patient outcome are missing.

PURPOSE

To assess the predictive value of baseline diffusion-weighted imaging in HCC before iBT with regard to local tumor control and overall survival (OS).

MATERIAL AND METHODS

We retrospectively identified 107 patients who underwent iBT for HCC from 2011 to 2018 from our database. Apparent diffusion coefficient (ADC) values for each treated lesion were analyzed in region of interest measurements. Additionally, explorative combined ratios adjusting total measured lesion area and mean measured lesion area per patient by ADC values were calculated. Measurements underwent a univariate and multivariate Cox regression analysis. The log rank test was then used to verify prognostic cutoff levels for median survival time.

RESULTS

A total of 189 lesions in 81 patients were measured. Median survival of patients was 46.0 months. Neither ADC parameter was indicative of local tumor control. Lesion size >5 cm was associated with lower local tumor control (hazard ratio [HR]=4.292, 95% confidence interval [CI]=1.285-14.331; P = 0.018). Average measured lesion area divided by ADC_min (ADC_{area mean, min}) was identified to independently predict OS (HR=1.994, 95% CI=1.172-3.392; P = 0.011). A cutoff based on the variable's median (0.29 × 10-4 AU) identified patients with poor outcome (OS 36 vs. 61 months) for lower ADC_{area mean, min} values as verified by the log-rank test (P = 0.040).

CONCLUSION

Pre-treatment ADC_{area mean, min} may serve as an independent predictor of OS in patients with HCC undergoing iBT.

Quantitative MRI of Pancreatic Cystic Lesions: A New Diagnostic Approach

The commonly used magnetic resonance (MRI) criteria can be insufficient for discriminating mucinous from non-mucinous pancreatic cystic lesions (PCLs). The histological differences between PCLs’ fluid composition may be reflected in MRI images, but cannot be assessed by visual evaluation alone. We investigate whether additional MRI quantitative parameters such as signal intensity measurements (SIMs) and radiomics texture analysis (TA) can aid the differentiation between mucinous and non-mucinous PCLs. Fifty-nine PCLs (mucinous, n = 24; non-mucinous, n = 35) are retrospectively included. The SIMs were performed by two radiologists on T2 and diffusion-weighted images (T2WI and DWI) and apparent diffusion coefficient (ADC) maps. A total of 550 radiomic features were extracted from the T2WI and ADC maps of every lesion. The SIMs and TA features were compared between entities using univariate, receiver-operating, and multivariate analysis. The SIM analysis showed no statistically significant differences between the two groups (p = 0.69, 0.21–0.43, and 0.98 for T2, DWI, and ADC, respectively). Mucinous and non-mucinous PLCs were successfully discriminated by both T2-based (83.2–100% sensitivity and 69.3–96.2% specificity) and ADC-based (40–85% sensitivity and 60–96.67% specificity) radiomic features. SIMs cannot reliably discriminate between PCLs. Radiomics have the potential to augment the common MRI diagnosis of PLCs by providing quantitative and reproducible imaging features, but validation is required by further studies.

Preoperative Localization of Parathyroid Adenomas with Diffusion MR Imaging: Readout-segmented versus Single-shot Echo-planar Imaging

PURPOSE

To evaluate whether readout-segmented echo-planar imaging (RS-EPI) diffusion-weighted imaging (DWI) can reduce image distortion and improve the lesion identification in parathyroid adenomas (PTAs) compared to single-shot EPI (SS-EPI) DWI, and to determine whether PTAs can be differentiated from other soft tissue structures of the head and neck region by using the apparent diffusion coefficient (ADC) value.

METHODS

We retrospectively analyzed the preoperative MR images including DWI of 24 patients with surgically confirmed PTA. RS-EPI and SS-EPI DWI were evaluated by two independent readers for the identification of the lesions and distortion. The ADC values of the PTAs were compared with those of thyroid glands and cervical lymph nodes.

RESULTS

RS-EPI provided significantly less distortion compared to SS-EPI. RS-EPI tended to have better lesion identification compared with SS-EPI without a statistically significant difference. On SS-EPI, the PTAs had significantly higher ADC values compared with the cervical lymph nodes. On RS-EPI, the PTAs had significantly higher ADC values compared with the thyroid glands and cervical lymph nodes.

CONCLUSION

RS-EPI reduces the DWI distortion in PTAs. The ADC value obtained using RS-EPI enables the differentiation of PTAs from nearby structures, such as thyroid glands and cervical lymph nodes.

Whole-body diffusion-weighted MRI of normal lymph nodes: prospective apparent diffusion coefficient histogram and nodal distribution analysis in a healthy cohort

BACKGROUND

Whole body DWI (WB-DWI) enables the identification of lymph nodes for disease evaluation. However, quantitative data of benign lymph nodes across the body are lacking to allow meaningful comparison of diseased states. We evaluated apparent diffusion coefficient (ADC) histogram parameters of all visible lymph nodes in healthy volunteers on WB-DWI and compared differences in nodal ADC values between anatomical regions.

METHODS

WB-DWI was performed on a 1.5 T MR system in 20 healthy volunteers (7 female, 13 male, mean age 35 years). The b900 images were evaluated by two radiologists and all visible nodes from the neck to groin areas were segmented and individual nodal median ADC recorded. All segmented nodes in a patient were summated to generate the total nodal volume. Descriptors of the global ADC histogram, derived from individual node median ADCs, including mean, median, skewness and kurtosis were obtained for the global volume and each nodal region per patient. ADC values between nodal regions were compared using one-way ANOVA with Bonferroni post hoc tests and a p-value ≤0.05 was deemed statistically significant.

RESULTS

One thousand sixty-seven lymph nodes were analyzed. The global mean and median ADC of all lymph nodes were 1.12 ± 0.27 (10^- 3 mm²/s) and 1.09 (10^- 3 mm²/s). The average median ADC skewness was 0.25 ± 0.02 and average median ADC kurtosis was 0.34 ± 0.04. The ADC values of intrathoracic, portal and retroperitoneal nodes were significantly higher (1.53 × 10^- 3, 1.75 × 10^- 3 and 1.58 × 10^- 3 mm²/s respectively) than in other regions. Intrathoracic, portal and mesenteric nodes were relatively uncommon, accounting for only 3% of the total nodes segmented.

CONCLUSIONS

The global mean and median ADC of all lymph nodes were 1.12 ± 0.27 (10^- 3 mm²/s) and 1.09 (10^- 3 mm²/s). Intrathoracic, portal and retroperitoneal nodes display significantly higher ADCs. Normal intrathoracic, portal and mesenteric nodes are infrequently visualized on WB-DWI of healthy individuals.

TRIAL REGISTRATION

Royal Marsden Hospital committee for clinical research registration number 09/H0801/86, 19.10.2009.

New and Advanced Magnetic Resonance Imaging Diagnostic Imaging Techniques in the Evaluation of Cranial Nerves and the Skull Base

The skull base and cranial nerves are technically challenging to evaluate using magnetic resonance (MR) imaging, owing to a combination of anatomic complexity and artifacts. However, improvements in hardware, software and sequence development seek to address these challenges. This section will discuss cranial nerve imaging, with particular attention to the techniques, applications and limitations of MR neurography, diffusion tensor imaging and tractography. Advanced MR imaging techniques for skull base pathology will also be discussed, including diffusion-weighted imaging, perfusion and permeability imaging, with a particular focus on practical applications.

Development of a standardized MRI protocol for pancreas assessment in humans

Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes.

Whole-body diffusion-weighted MRI in lymphoma-comparison of global apparent diffusion coefficient histogram parameters for differentiation of diseased nodes of lymphoma patients from normal lymph nodes of healthy individuals

Background

Morphologic features yield low diagnostic accuracy to distinguish between diseased and normal lymph nodes. The purpose of this study was to compare diseased lymphomatous and normal lymph nodes using global apparent diffusion coefficient (gADC) histogram parameters derived from whole-body diffusion-weighted MRI (WB-DWI).

Methods

1.5 Tesla WB-DWI of 23 lymphoma patients and 20 healthy volunteers performed between 09/2010 and 07/2015 were retrospectively reviewed. All diseased nodal groups in the lymphoma cohort and all nodes visible on b900 images in healthy volunteers were segmented from neck to groin to generate a total diffusion volume (tDV). A connected component-labelling algorithm separated spatially distinct nodes. Mean, median, skewness, kurtosis, minimum, maximum, interquartile range (IQR), standard deviation (SD), 10^th and 90^th centile of the gADC distribution were derived from the tDV of each patient/volunteer and from spatially distinct nodes. gADC and regional nodal ADC parameters were compared between malignant and normal nodes using t-tests and ROC curve analyses. A P value ≤0.05 was deemed statistically significant.

Results

Mean, median, IQR, 10th and 90th centiles of gADC and regional nodal ADC values were significantly lower in diseased compared with normal lymph nodes. Skewness, kurtosis and tDV were significantly higher in lymphoma. The SD, min and max gADC showed no significant difference between the two groups (P>0.128). The diagnostic accuracies of gADC parameters by AUC from highest to lowest were: 10th centile, mean, median, 90th centile, skewness, kurtosis and IQR. A 10th centile gADC threshold of 0.68×10^-3 mm²/s identified diseased lymphomatous nodes with 91% sensitivity and 95% specificity.

Conclusions

WB-DWI derived gADC histogram parameters can distinguish between malignant lymph nodes of lymphoma patients and normal lymph nodes of healthy individuals.

Diffusion-Weighted Magnetic Resonance Imaging as a Noninvasive Parameter for Differentiating Benign and Malignant Intraperitoneal Collections

Background and Objective: The imaging differentiation of benign from malignant intraperitoneal collections (IPCs) relies on the tumoral morphological modifications of the peritoneum, which are not always advocating for malignancy. We aimed to assess ascitic fluid with the apparent diffusion coefficient (ADC) to determine non-invasive, stand-alone, differentiation criteria for benign and malignant intraperitoneal effusions. Materials and Methods: Sixty-one patients with known IPCs who underwent magnetic resonance examinations for reasons such as tumor staging, undetermined abdominal mass and disease follow up were retrospectively included in this study. All subjects had a final diagnosis of the fluid based on pathological examinations, which were divided into benign (n = 37) and malignant (n = 24) IPCs groups. ADC values were measured separately by two radiologists, and the average values were used for comparing the two groups by consuming the independent samples t-test. The receiver operating characteristic analysis was performed to test the ADC values' diagnostic ability to distinguish malignant from benign collections. Results: The differentiation between benign and malignant IPCs based on ADC values was statistically significant (p = 0.0034). The mean ADC values were higher for the benign (3.543 × 10^-3 mm²/s) than for the malignant group (3.057 × 10^-3 mm²/s). The optimum ADC cutoff point for the diagnosis of malignant ascites was <3.241 × 10^-3 mm²/s, with a sensitivity of 77.78% and a specificity of 80%. Conclusions: ADC represents a noninvasive and reproducible imaging parameter that may help to assess intraperitoneal collections. Although successful in distinguishing malignant from benign IPCs, further research must be conducted in order to certify if the difference in ADC values is a consequence of the physical characteristics of the ascitic fluids or their appurtenance to a certain histopathological group.

Are superior cervical sympathetic ganglia avid on whole body 68Ga-PSMA-11 PET/magnetic resonance?: a comprehensive morphologic and molecular assessment in patients with prostate cancer

OBJECTIVES

Recent reports warn against erroneous mistaking of celiac and stellate sympathetic ganglia for metastatic lymph nodes on multimodal prostate-specific membrane antigen (PSMA)-ligand PET imaging. The aim was to check the intensity of Ga-PSMA-11 uptake and magnetic resonance (MR) features of superior cervical ganglia (SCG) on PET/MR imaging.

METHODS

In 89 patients 106 SCG were reliably identified on Ga-PSMA-11 PET/MR. For each SCG, qualitative assessment (visual subjective avidity, diffusion restriction, shape, and the presence of central hypointensity) and quantitative measurements [dimensions, maximal standardized uptake value (SUVmax), mean apparent diffusion coefficient (ADC)] were performed.

RESULTS

Mean SUVmax in SCG amounted to 1.88 ± 0.63 (range: 0.87-4.42), with considerable metabolic activity (SUVmax ≥ 2) in 37.7% of SCG; mean thickness was 3.18 ± 1.08 mm. In subjective visual evaluation, SCG avidity was classified as mistakable or potentially mistakable with underlying malignancy in 32.1% of cases. Mean ADC values amounted 1749.83 ± 428.83 × 10mm/s. In visual assessment, 74.5% of ganglia showed moderate to high diffusion restriction. An oval or longitudinal shape on transverse MR plane was presented by 59.4% of SCG. The central hypointensity was detected on MR T2-weighted images only in 10.4% of SCG.

CONCLUSION

SCG, similar to other sympathetic ganglia, show Ga-PSMA-11 uptake. SCG avidity may be of significance, especially in view of frequently occurring SCG oval or longitudinal shape, and moderate to high diffusion restriction in visual assessment, potentially suggesting malignancy on transverse MR plane. Diagnostic imaging specialists and clinicians should be aware of the above.

Is the level of diffusion restriction in celiac and cervico-thoracic sympathetic ganglia helpful in their proper recognition on PSMA ligand PET/MR?

AIM

 To check if diffusion weighted imaging (DWI) might be helpful in proper recognition of celiac (CG) and cervicothoracic (CTG) sympathetic ganglia on the whole-body multimodal PSMA-ligand PET/MR imaging, in the view of their common misleading avidity on PET potentially suggestive of malignant lesions, including metastatic lymph nodes.

METHODS

 The thickness and the level of diffusion restriction was assessed qualitatively and quantitatively in 406 sympathetic ganglia (189 CTG in 101 males and 217 CG in 116 males) on DWI maps (b-value 0 and 800 s/mm²) and apparent diffusion coefficient (ADC) maps (mean ADC) of the whole-body PET/MR 68Ga-PSMA-11 PET/MR. To form a reference group of a matching ganglia size, the smallest lymph node was chosen from each patient with metastases and underwent the same procedure.

RESULTS

 Very low and low level of diffusion restriction was noted in the majority of sympathetic ganglia (81.0 % CTG, 67.3 % CG, and 73.6 % of all). In the majority (91.7 %) of metastatic lymph nodes the level of diffusion restriction was moderate to high.The mean ADC values in sympathetic ganglia were statistically significantly higher in CTG, CG and all ganglia than in metastatic lymph nodes (p < 0.001; the effect size was large).

CONCLUSIONS

 Sympathetic celiac and cervicothoracic ganglia present very low and low level of diffusion restriction in visual DWI assessment, and significantly higher than metastatic lymph nodes mean ADC values in the majority of cases, which may serve as additional factors aiding differential diagnosis on multimodal PSMA-ligand PET/MR imaging.Therefore, PSMA-ligand PET/MR appears potentially superior to PSMA-ligand PET/CT in proper identification of sympathetic ganglia.

Apparent Diffusion Coefficient for Distinguishing Between Malignant and Benign Lesions in the Head and Neck Region: A Systematic Review and Meta-Analysis

Background: The purpose of the present meta-analysis was to provide evident data about use of apparent diffusion coefficient (ADC) values for distinguishing malignant and benign lesions in the head and neck region.

Material and Methods: MEDLINE and Scopus databases were screened for associations between ADC and malignancy/benignancy of head and neck lesions up to December 2018. Overall, 22 studies met the inclusion criteria. The following data were extracted: authors, year of publication, study design, number of patients/lesions, lesion type, mean value, and standard deviation of ADC. The primary endpoint of the systematic review was the analysis of the association between lesion nature and ADC values. The methodological quality of the involved studies was checked according to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for benign and malignant lesions.

Results: The acquired 22 studies comprised 1,227 lesions. Different malignant lesions were diagnosed in 818 cases (66.7%) and benign lesions in 409 cases (33.3%). The mean ADC value of the malignant lesions was 1.04 × 10⁻³ mm²/s, and the mean value of the benign lesions was 1.46 × 10⁻³ mm²/s. Lymphomas and sarcomas showed the lowest calculated mean ADC values, 0.7 and 0.79 × 10⁻³ mm²/s, respectively. Adenoid cystic carcinomas had the highest ADC values (1.5 × 10⁻³ mm²/s). None of the analyzed malignant tumors had mean ADC values above 1.75 × 10⁻³ mm²/s.

Conclusion: ADC values play a limited role in distinguishing between malignant and benign lesions in the head and neck region. It may be only suggested that lesions with mean ADC values above 1.75 × 10⁻³ mm²/s are probably benign. Further large studies are needed for the analysis of the role of diffusion-weighted imaging (DWI)/ADC in the discrimination of benign and malignant lesions in the head and neck region.

Whole-body magnetic resonance imaging in paediatric Hodgkin lymphoma - evaluation of quantitative magnetic resonance metrics for nodal staging

BACKGROUND

Whole-body MRI is used for staging paediatric Hodgkin lymphoma, commonly using size thresholds, which fail to detect disease in normal-size lymph nodes.

OBJECTIVE

To investigate quantitative whole-body MRI metrics for nodal characterisation.

MATERIALS AND METHODS

Thirty-seven children with Hodgkin lymphoma underwent 1.5-tesla (T) whole-body MRI using short tau inversion recovery (STIR) half-Fourier-acquisition single-shot turbo-spin-echo and diffusion-weighted imaging (DWI). 18Flourine-2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/CT was acquired as the reference standard. Two independent readers assessed 11 nodal sites. The readers measured short-axis-diameter, apparent diffusion coefficient, (ADC) and normalised T2-signal intensity of the largest lymph node at each site. We used receiver operating characteristics (ROC)/area-under-the-curve (AUC) analysis for each MRI metric and derived sensitivity and specificity for nodes with short-axis diameter ≥10 mm. Sub-analysis of sensitivity and specificity was performed with application of ADC cut-off values (<0.77, <1.15 and <1.79×10-3 mm2 s-1) to 5- to 9-mm nodes.

RESULTS

ROC/AUC values for reader 1/reader 2 were 0.80/0.80 and 0.81/0.81 for short-axis-diameter measured using DWI and STIR half-Fourier-acquisition single-shot turbo spin echo, respectively; 0.67/0.72 for normalised T2 signal intensity and 0.74/0.67 for ADC. Sensitivity and specificity for a short-axis diameter ≥10 mm were 84.2% and 66.7% for Reader 1 and 82.9% and 68.9% for Reader 2. Applying a short-axis-diameter ≥10-mm threshold followed by ADC cut-offs to normal-size 5- to 9-mm nodes resulted in sensitivity and specificity for Reader 1 of 88.8% and 60%, 92.1% and 56.7%, and 100% and 16.7%; and for Reader 2, 86.1% and 67.2%, 95.3% and 65.6%, and 100% and 19.7%; and ADC thresholds of <0.77, <1.15, and <1.79×10-3 mm2 s-1, respectively.

CONCLUSION

Nodal size measurement provides the best single classifier for nodal disease status in paediatric Hodgkin lymphoma. Combined short-axis diameter and ADC thresholds marginally improve sensitivity and drop specificity compared with size classification alone.

Quantitative diffusion magnetic resonance imaging for prediction of human papillomavirus status in head and neck squamous-cell carcinoma: A systematic review and meta-analysis

PURPOSE

Head and neck squamous-cell carcinoma (HNSCC) related to human papillomavirus (HPV) infection represents a distinct biological and prognostic subtype compared to the HPV-negative form. Prior studies suggest a correlation between the apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) of primary tumor lesion and HPV status in HNSCC. In this meta-analysis, we compared the average ADC of primary lesion between HPV-positive and HPV-negative HNSCC.

METHODS

A comprehensive literature search of PubMed and Embase was performed. Studies comparing the average ADC on echo-planar DWI of primary tumor lesions between HPV-positive and HPV-negative HNSCC were included. The standardized mean difference was calculated using fixed- and random-effects models. Tau-squared estimates of total heterogeneity and Higgins inconsistency index (I² test) were determined.

RESULTS

A total of five studies, pooling data of 264 patients, were included for meta-analysis. Among these five studies, three had included oral cavity, hypopharyngeal, and/or laryngeal HNSCC in addition to oropharyngeal subsite. Primary lesions were comprised of 185 HPV-negative and 79 HPV-positive HNSCC. The meta-analysis showed lower average ADC values in HPV-positive HNSCC compared to the HPV-negative form, with a standardized mean difference of 0.961 (95% confidence interval 0.644-1.279; p < 0.0001). Since there was no significant heterogeneity in analysis (p = 0.3852), both random- and fixed-effects models resulted in the same estimates of overall effect.

CONCLUSIONS

HPV-positive HNSCC primary lesions have a lower average ADC compared to the HPV-negative form, highlighting the potential application of quantitative diffusion magnetic resonance imaging as a noninvasive imaging biomarker for prediction of HPV status.

Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator

PURPOSE

Systems for magnetic resonance (MR-) guided radiotherapy enable daily MR imaging of cancer patients during treatment, which is of interest for treatment response monitoring and biomarker discovery using quantitative MRI (qMRI). Here, the performance of a 1.5 T MR-linac regarding qMRI was assessed on phantoms. Additionally, we show the feasibility of qMRI in a prostate cancer patient on this system for the first time.

MATERIALS AND METHODS

Four 1.5 T MR-linac systems from four institutes were included in this study. T₁ and T₂ relaxation times, and apparent diffusion coefficient (ADC) maps, as well as dynamic contrast enhanced (DCE) images were acquired. Bland-Altman statistics were used, and accuracy, repeatability, and reproducibility were determined.

RESULTS

Median accuracy for T₁ ranged over the four systems from 2.7 to 14.3%, for T₂ from 10.4 to 14.1%, and for ADC from 1.9 to 2.7%. For DCE images, the accuracy ranged from 12.8 to 35.8% for a gadolinium concentration of 0.5 mM and deteriorated for higher concentrations. Median short-term repeatability for T₁ ranged from 0.6 to 5.1%, for T₂ from 0.4 to 1.2%, and for ADC from 1.3 to 2.2%. DCE acquisitions showed a coefficient of variation of 0.1-0.6% in the signal intensity. Long-term repeatability was 1.8% for T₁, 1.4% for T₂, 1.7% for ADC, and 17.9% for DCE. Reproducibility was 11.2% for T₁, 2.9% for T₂, 2.2% for ADC, and 18.4% for DCE.

CONCLUSION

These results indicate that qMRI on the Unity MR-linac is feasible, accurate, and repeatable which is promising for treatment response monitoring and treatment plan adaptation based on daily qMRI.