Advantages of high b-value diffusion-weighted imaging for preoperative differential diagnosis between embryonal and ependymal tumors at 3 T MRI

Exploratory high b value diffusion-weighted MR for quantitative differentiation of ileocecal inflammatory conditions and tumors

OBJECTIVES

To explore the quantitative analysis of high b value (2000 s/mm2) diffusion-weighted imaging (DWI) for the differentiation of ileocecal inflammatory conditions and tumors, compared with conventional b value (800 s/mm2) DWI.

METHODS

Sixty-six patients with 30 tumors and 36 inflammatory conditions underwent MR enterography with conventional and high b values DWI. Quantitative apparent diffusion coefficient (ADC) values and signal intensity ratios (SIRs) of lesions of the psoas muscle were measured from the two b value DWIs. The receiver operating characteristic (ROC) curve was applied to determine the diagnostic value of ADC and SIR for differentiating tumors from inflammatory conditions.

RESULTS

The ADC values of tumors were significantly lower than those of inflammatory conditions in 800 s/mm2 (p = 0.001) and 2000 s/mm2 (p < 0.001) DWI. In addition, tumors exhibited significantly higher SIR values compared to inflammatory conditions (p < 0.001 in 800 s/mm2 and 2000 s/mm2 DWI). Areas under the curve (AUC) of ADC and SIR derived from high b value (0.828 for ADC, 0.947 for SIR) were superior to those from conventional b value DWI (0.731 and 0.849, respectively). Compared to ADC, SIR values achieved better AUCs in both two b values DWI.

CONCLUSIONS

Quantitative ADC values and SIR could be used as non-invasive tools to distinguish ileocecal tumors from inflammatory conditions. The use of high b value DWI would improve this ability. Furthermore, SIR obtained from high b value DWI was the most promising quantitative parameter.

CRITICAL RELEVANCE STATEMENT

This study indicated that quantitative DWI parameters might be applied as non-invasive imaging biomarkers for distinguishing bowel tumors from inflammatory conditions. The SIR from high b value DWI could improve the differentiation, providing invaluable information for establishing appropriate therapeutic strategies.

KEY POINTS

Differentiation between bowel inflammatory conditions and tumors is still a dilemma. Quantitative DWI contributed to distinguishing ileocecal tumors from inflammatory conditions. SIR from DWI is a promising parameter for differentiating these pathologies.

Machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma and supratentorial glioblastoma

Objective

To develop a machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma (STEE) and supratentorial glioblastoma (GBM).

Methods

We conducted a retrospective analysis on MRI datasets obtained from 140 patients who were diagnosed with STEE (n=48) and GBM (n=92) from two institutions. Initially, we compared seven different machine learning algorithms to determine the most suitable signature (rad-score). Subsequently, univariate and multivariate logistic regression analyses were performed to identify significant clinical predictors that can differentiate between STEE and GBM. Finally, we developed a nomogram by visualizing the rad-score and clinical features for clinical evaluation.

Results

The TreeBagger (TB) outperformed the other six algorithms, yielding the best diagnostic efficacy in differentiating STEE from GBM, with area under the curve (AUC) values of 0.735 (95% CI: 0.625-0.845) and 0.796 (95% CI: 0.644-0.949) in the training set and test set. Furthermore, the nomogram incorporating both the rad-score and clinical variables demonstrated a robust predictive performance with an accuracy of 0.787 in the training set and 0.832 in the test set.

Conclusion

The nomogram could serve as a valuable tool for non-invasively discriminating between STEE and GBM.

Using Ultrahigh b -Value Diffusion-Weighted Imaging to Noninvasively Assess Renal Fibrosis in a Rabbit Model of Renal Artery Stenosis

OBJECTIVE

This study aimed to investigate the feasibility of diffusion-weighted imaging with ultrahigh b values ( ub DWI) for the evaluation of renal fibrosis (RF) induced by renal artery stenosis (RAS) in a rabbit model.

METHODS

Thirty-two rabbits underwent left RAS operation, whereas 8 rabbits received sham surgery. All rabbits underwent ub DWI ( b = 0-4500 s/mm 2 ). The standard apparent diffusion coefficient (ADC st ), molecular diffusion coefficient ( D ), perfusion fraction ( f ), perfusion-related diffusion coefficient ( D *) and ultrahigh apparent diffusion coefficient (ADC uh ) were longitudinally assessed before operation and at weeks 2, 4, and 6 after operation. The degree of interstitial fibrosis and the expression of aquaporin (AQP) 1 and AQP2 were determined through pathological examination.

RESULTS

In the stenotic kidney, the ADC st , D , f , and ADC uh values of the renal parenchyma significantly decreased compared with those at baseline (all P < 0.05), whereas the D * values significantly increased after RAS induction ( P < 0.05). The ADC st , D , D *, and f were weakly to moderately correlated with interstitial fibrosis as well as with the expression of AQP1 and AQP2. Furthermore, the ADC uh negatively correlated with interstitial fibrosis ( ρ = -0.782, P < 0.001) and positively correlated with AQP1 and AQP2 expression ( ρ = 0.794, P < 0.001, and ρ = 0.789, P < 0.001, respectively).

CONCLUSIONS

Diffusion-weighted imaging with ultrahigh b values shows the potential for noninvasive assessment of the progression of RF in rabbits with unilateral RAS. The ADC uh derived from ub DWI could reflect the expression of AQPs in RF.

Differentiating between adult intracranial medulloblastoma and ependymoma using MRI

AIM

To investigate the value of routine magnetic resonance imaging (MRI) examination combined with diffusion-weighted imaging (DWI) in the differential diagnosis of adult intracranial medulloblastomas and ependymomas.

MATERIALS AND METHODS

MRI images of 18 medulloblastomas and 18 ependymomas in adult patients were analysed retrospectively, and the differences in MRI features of lesions and apparent diffusion coefficient (ADC) of solid lesions between the two groups were recorded. Independent sample t-tests and χ2 tests were used to analyse the differences in MRI signs and maximum ADC (ADC_max), minimum ADC (ADC_min), and mean ADC (ADC_mean) values between the two groups. The receiver operating characteristic (ROC) curve was used to determine the differential diagnostic efficacy and optimal threshold for each ADC value.

RESULTS

Age, tumour location, and tumour enhancement were significantly different between adult medulloblastoma and ependymoma (p<0.05). The ADC_max (0.69 ± 0.11 versus 1.04 ± 0.20 × 10^-3 mm²/s, p<0.001), ADC_min (0.57 ± 0.12 versus 0.96 ± 0.21 × 10^-3 mm²/s, p<0.001), and ADC_mean (0.62 ± 0.11 versus 1.00 ± 0.20 × 10^-3 mm²/s, p<0.001) values were significantly lower in adult medulloblastoma than in ependymoma. The areas under the ROC curves of ADC_max, ADC_min, and ADC_mean were 0.951, 0.957, and 0.966, respectively. The optimal ADC_mean threshold was 0.75 × 10^-3 mm²/s, with a sensitivity of 88.9% and a specificity of 88.9%.

CONCLUSION

Routine MRI examination combined with DWI helps differentiate between intracranial infratentorial medulloblastoma and ependymoma in adults.

Single shot zonal oblique multislice SE-EPI diffusion-weighted imaging with low to ultra-high b-values for the differentiation of benign and malignant vertebral spinal fractures

Purpose

To investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI).

Materials and Methods

66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0,400; 0,1000 and 0,2000s/mm². ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae.

Results

ADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0,400/0,1000/0,2000s/mm² ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm² trace images respectively. In qualitative analyses, only b = 2000s/mm² trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm² respectively. The model incorporating only qualitative metrics from b = 2000s/mm² achieved an AUC of 0.97.

Conclusion

By using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.

Supratentorial Extraventricular Ependymomas: Imaging Features and the Added Value of Apparent Diffusion Coefficient

OBJECTIVE

To improve the understanding and the diagnosis of intracranial ependymal tumors.

METHODS

The clinical, radiological and prognostic features of 48 supratentorial extraventricular ependymomas and 74 intraventricular ependymomas were summarized and compared.

RESULTS

Supratentorial extraventricular ependymomas, most often located in the frontal lobe (33.3%) and classified as grade III (75.0%), had relatively large eccentric cysts (3.07 ± 2.03 cm), significant enhancement (84.8%), low apparent diffusion coefficient (ADC) values, and associated with higher mortality (41.3%). The majority of intraventricular lesions occurred in the fourth ventricle (86.5%) and classified as grade II (78.4%), had relatively small and multiple cystic changes (1.04 ± 0.87 cm), slight or moderate enhancement (76.9%), high ADC values and associated with lower mortality (20.7%). There were few significant differences between grade II and grade III tumors in these 2 groups, respectively. Young age, high grade and low ADC values are worse prognostic indicators for patients with supratentorial extraventricular ependymomas, but not for those with intraventricular ependymomas.

CONCLUSIONS

Conventional radiological features, combined with clinical manifestations and quantitative information provided by diffusion-weighted imaging, may not only enhance the diagnosis and assist in determining prognosis but also provide a better pathophysiological understanding of intracranial ependymal tumors.

Advanced MRI Findings in Medulloblastomas: Relationship to Genetic Subtypes, Histopathology, and Immunohistochemistry

BACKGROUND AND PURPOSE

For diagnosis of medulloblastoma, the updated World Health Organization classification now demands for genetic typing, defining more precisely the tumor biology, therapy, and prognosis. We investigated potential associations between magnetic resonance imaging (MRI) parameters including apparent diffusion coefficient (ADC) and neuropathologic features of medulloblastoma, focusing on genetic subtypes.

METHODS

This study was a retrospective single-center analysis of 32 patients (eight females, median age = 9 years [range, 1-57], mean 12.6 ± 11.3) from 2012 to 2019. Genetic subtypes (wingless [WNT]; sonic hedgehog [SHH]; non-WNT/non-SHH), histopathology, immunohistochemistry (p53, Ki67), and the following MRI parameters were correlated: tumor volume, location (midline, pontocerebellar, and cerebellar hemisphere), edema, hydrocephalus, metastatic disease (presence/absence and each), contrast-enhancement (minor, moderate, and distinct), cysts (none, small, and large), hemorrhage (none, minor, and major), and ADC_mean . The ADC_mean was calculated using manually set regions of interest within the solid tumor. Statistics comprised univariate and multivariate testing.

RESULTS

Out of 32 tumors, three tumors were WNT activated (9.4%), 13 (40.6%) SHH activated, and 16 (50.0%) non-WNT/non-SHH. Hemispherical location (n = 7/8, P = .003) and presence of edema (8/8; P < .001, specificity 100%, positive predictive value 100%) were significantly associated with SHH activation. The combined parameter "no edema + no metastatic disease + cysts" significantly discriminated WNT-activated from SHH-activated medulloblastoma (P = .036). ADC_mean (10^-6 mm² /s) was 484 for WNT-activated, 566 for SHH-activated, and 624 for non-WNT/non-SHH subtypes (P = .080). A significant negative correlation was found between ADC_mean and Ki67 (r = -.364, P = .040).

CONCLUSION

MRI analysis enabled noninvasive differentiation of SHH-activated medulloblastoma. ADC alone was not reliable for genetic characterization, but associated with tumor proliferation rate.

Radiology Profile as a Potential Instrument to Differentiate Between Posterior Fossa Ependymoma (PF-EPN) Group A and B

OBJECTIVE

Posterior fossa ependymoma (PF-EPN) was categorized into PF-EPN-A and PF-EPN-B subgroups based on the DNA methylation profiling. PF-EPN-A was reported to have poorer prognosis compared with PF-EPN-B. In this study, we particularly evaluated preoperative imaging to distinguish PF-EPN-A from PF-EPN-B.

METHODS

Sixteen cases of PF-EPN were treated in our institution from 1999 to 2018. The patients were divided into PF-EPN-A and PF-EPN-B groups based on H3K27me3 immunostaining positivity. We evaluated progression-free survival, overall survival, as well as preoperative magnetic resonance imaging and computed tomography scan images in both groups. Based on T1WI and Gd-T1WI magnetic resonance images, the tumor contrast rate was determined from dividing the volume of gadolinium enhanced tumor by the overall tumor volume.

RESULTS

Nine cases (4 male, 5 female) were grouped as PF-EPN-A, and 7 (4 male, 3 female) as PF-EPN-B. The median age of PF-EPN-A and PF-EPN-B were 4 and 43 years old, respectively. In the PF-EPN-A group, the progression-free survival median value was 32.6 months, and the overall survival median was 96.9 months. In contrast, PFS in PF-EPN-B did not reach a median value (P < 0.05) and all the patients were alive (P < 0.05) at the end of the study. With imaging, tumor contrast rate in PF-EPN-B was more than 50% and significantly different from PF-EPN-A (P = 0.0294). Calcification was mainly observed in PF-EPN-A, whereas cystic formation was only seen in PF-EPN-B.

CONCLUSIONS

Contrast rate less than 50%, based on the magnetic resonance images, was characteristic in the PF-EPN-A group. Comparatively, cystic component and absence of calcification were more characteristic in the PF-EPN-B group.

Advantage of high b value diffusion-weighted imaging for differentiation of common pediatric brain tumors in posterior fossa

PURPOSE

The pediatric posterior fossa (PF) brain tumors with higher frequencies are embryonal tumors (ET), ependymal tumors (EPN) and pilocytic astrocytomas (PA), however, it is often difficult to make a differential diagnosis among them with conventional MRI. The ADC calculated from DWI could be beneficial for diagnostic work up.

METHOD

We acquired DWI at b = 1000 and 4000(s/mm²). The relationship between ADC and the three types of brain tumors was evaluated with Mann-Whitney U test. We also performed simple linear regression analysis to evaluate the relationship between ADC and cellularity, and implemented receiver operating characteristic curve (ROC curve) to test the diagnostic performance among tumors.

RESULTS

The highest ADC (b1000/b4000 × 10^-3 mm²/s) was observed in PA (1.02-1.91/0.73-1.28), followed by PF-EPN (0.83-1.28/0.60-0.79) and the lowest was ET (0.41-0.75/0.29-0.47). There was significant difference among the groups in both ADC value (b-1000/b-4000: ET vs. PF-EPN p < 0.0001/0.0001, ET vs. PA p < 0.0001/0.0001, PF-EPN vs. PA p < 0.0001/0.0001). ROC analysis revealed that ADC in both b-values showed complete separation between ET and PF-EPN. And it also revealed that ADC at b-4000 could differentiate PF-EPN and PA (96.0%) better than ADC at b-1000 (90.1%). The stronger negative correlation was observed between the ADC and cellularity at b-4000 than at b-1000 (R²  = 0.7415 vs.0.7070) CONCLUSIONS: ADC of ET was significantly lower than the other two groups, and ADC of PA was significantly higher than the other two groups in both b-1000 and b-4000. Our results showed that ADC at b-4000 was more useful than ADC at b-1000 especially for differentiation between PF-EPN and PA.