MR Imaging of Adverse Effects and Ocular Growth Decline after Selective Intra-Arterial Chemotherapy for Retinoblastoma

This retrospective multicenter study examines therapy-induced orbital and ocular MRI findings in retinoblastoma patients following selective intra-arterial chemotherapy (SIAC) and quantifies the impact of SIAC on ocular and optic nerve growth. Patients were selected based on medical chart review, with inclusion criteria requiring the availability of posttreatment MR imaging encompassing T2-weighted and T1-weighted images (pre- and post-intravenous gadolinium administration). Qualitative features and quantitative measurements were independently scored by experienced radiologists, with deep learning segmentation aiding total eye volume assessment. Eyes were categorized into three groups: eyes receiving SIAC (Rb-SIAC), eyes treated with other eye-saving methods (Rb-control), and healthy eyes. The most prevalent adverse effects post-SIAC were inflammatory and vascular features, with therapy-induced contrast enhancement observed in the intraorbital optic nerve segment in 6% of patients. Quantitative analysis revealed significant growth arrest in Rb-SIAC eyes, particularly when treatment commenced ≤ 12 months of age. Optic nerve atrophy was a significant complication in Rb-SIAC eyes. In conclusion, this study highlights the vascular and inflammatory adverse effects observed post-SIAC in retinoblastoma patients and demonstrates a negative impact on eye and optic nerve growth, particularly in children treated ≤ 12 months of age, providing crucial insights for clinical management and future research.

Correlation of gene expression with magnetic resonance imaging features of retinoblastoma: a multi-center radiogenomics validation study

OBJECTIVES

To validate associations between MRI features and gene expression profiles in retinoblastoma, thereby evaluating the repeatability of radiogenomics in retinoblastoma.

METHODS

In this retrospective multicenter cohort study, retinoblastoma patients with gene expression data and MRI were included. MRI features (scored blinded for clinical data) and matched genome-wide gene expression data were used to perform radiogenomic analysis. Expression data from each center were first separately processed and analyzed. The end product normalized expression values from different sites were subsequently merged by their Z-score to permit cross-sites validation analysis. The MRI features were non-parametrically correlated with expression of photoreceptorness (radiogenomic analysis), a gene expression signature informing on disease progression. Outcomes were compared to outcomes in a previous described cohort.

RESULTS

Thirty-six retinoblastoma patients were included, 15 were female (42%), and mean age was 24 (SD 18) months. Similar to the prior evaluation, this validation study showed that low photoreceptorness gene expression was associated with advanced stage imaging features. Validated imaging features associated with low photoreceptorness were multifocality, a tumor encompassing the entire retina or entire globe, and a diffuse growth pattern (all p < 0.05). There were a number of radiogenomic associations that were also not validated.

CONCLUSIONS

A part of the radiogenomic associations could not be validated, underlining the importance of validation studies. Nevertheless, cross-center validation of imaging features associated with photoreceptorness gene expression highlighted the capability radiogenomics to non-invasively inform on molecular subtypes in retinoblastoma.

CLINICAL RELEVANCE STATEMENT

Radiogenomics may serve as a surrogate for molecular subtyping based on histopathology material in an era of eye-sparing retinoblastoma treatment strategies.

KEY POINTS

• Since retinoblastoma is increasingly treated using eye-sparing methods, MRI features informing on molecular subtypes that do not rely on histopathology material are important. • A part of the associations between retinoblastoma MRI features and gene expression profiles (radiogenomics) were validated. • Radiogenomics could be a non-invasive technique providing information on the molecular make-up of retinoblastoma.

MRI Features for Identifying MYCN-amplified RB1 Wild-type Retinoblastoma

Background MYCN-amplified RB1 wild-type (MYCNARB1+/+) retinoblastoma is a rare but clinically important subtype of retinoblastoma due to its aggressive character and relative resistance to typical therapeutic approaches. Because biopsy is not indicated in retinoblastoma, specific MRI features might be valuable to identify children with this genetic subtype. Purpose To define the MRI phenotype of MYCNARB1+/+ retinoblastoma and evaluate the ability of qualitative MRI features to help identify this specific genetic subtype. Materials and Methods In this retrospective, multicenter, case-control study, MRI scans in children with MYCNARB1+/+ retinoblastoma and age-matched children with RB1-/- subtype retinoblastoma were included (case-control ratio, 1:4; scans acquired from June 2001 to February 2021; scans collected from May 2018 to October 2021). Patients with histopathologically confirmed unilateral retinoblastoma, genetic testing (RB1/MYCN status), and MRI scans were included. Associations between radiologist-scored imaging features and diagnosis were assessed with the Fisher exact test or Fisher-Freeman-Halton test, and Bonferroni-corrected P values were calculated. Results A total of 110 patients from 10 retinoblastoma referral centers were included: 22 children with MYCNARB1+/+ retinoblastoma and 88 control children with RB1-/- retinoblastoma. Children in the MYCNARB1+/+ group had a median age of 7.0 months (IQR, 5.0-9.0 months) (13 boys), while children in the RB1-/- group had a median age of 9.0 months (IQR, 4.6-13.4 months) (46 boys). MYCNARB1+/+ retinoblastomas were typically peripherally located (in 10 of 17 children; specificity, 97%; P < .001) and exhibited plaque or pleomorphic shape (in 20 of 22 children; specificity, 51%; P = .011) with irregular margins (in 16 of 22 children; specificity, 70%; P = .008) and extensive retina folding with vitreous enclosure (specificity, 94%; P < .001). MYCNARB1+/+ retinoblastomas showed peritumoral hemorrhage (in 17 of 21 children; specificity, 88%; P < .001), subretinal hemorrhage with a fluid-fluid level (in eight of 22 children; specificity, 95%; P = .005), and strong anterior chamber enhancement (in 13 of 21 children; specificity, 80%; P = .008). Conclusion MYCNARB1+/+ retinoblastomas show distinct MRI features that could enable early identification of these tumors. This may improve patient selection for tailored treatment in the future. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rollins in this issue.

Automatic segmentation and quantification of the optic nerve on MRI using a 3D U-Net

Purpose

Pathological conditions associated with the optic nerve (ON) can cause structural changes in the nerve. Quantifying these changes could provide further understanding of disease mechanisms. We aim to develop a framework that automatically segments the ON separately from its surrounding cerebrospinal fluid (CSF) on magnetic resonance imaging (MRI) and quantifies the diameter and cross-sectional area along the entire length of the nerve.

Approach

Multicenter data were obtained from retinoblastoma referral centers, providing a heterogeneous dataset of 40 high-resolution 3D T2-weighted MRI scans with manual ground truth delineations of both ONs. A 3D U-Net was used for ON segmentation, and performance was assessed in a tenfold cross-validation (n = 32 ) and on a separate test-set (n = 8 ) by measuring spatial, volumetric, and distance agreement with manual ground truths. Segmentations were used to quantify diameter and cross-sectional area along the length of the ON, using centerline extraction of tubular 3D surface models. Absolute agreement between automated and manual measurements was assessed by the intraclass correlation coefficient (ICC).

Results

The segmentation network achieved high performance, with a mean Dice similarity coefficient score of 0.84, median Hausdorff distance of 0.64 mm, and ICC of 0.95 on the test-set. The quantification method obtained acceptable correspondence to manual reference measurements with mean ICC values of 0.76 for the diameter and 0.71 for the cross-sectional area. Compared with other methods, our method precisely identifies the ON from surrounding CSF and accurately estimates its diameter along the nerve's centerline.

Conclusions

Our automated framework provides an objective method for ON assessment in vivo.

Magnetic resonance imaging based radiomics prediction of Human Papillomavirus infection status and overall survival in oropharyngeal squamous cell carcinoma

OBJECTIVES

Human papillomavirus- (HPV) positive oropharyngeal squamous cell carcinoma (OPSCC) differs biologically and clinically from HPV-negative OPSCC and has a better prognosis. This study aims to analyze the value of magnetic resonance imaging (MRI)-based radiomics in predicting HPV status in OPSCC and aims to develop a prognostic model in OPSCC including HPV status and MRI-based radiomics.

MATERIALS AND METHODS

Manual delineation of 249 primary OPSCCs (91 HPV-positive and 159 HPV-negative) on pretreatment native T1-weighted MRIs was performed and used to extract 498 radiomic features per delineation. A logistic regression (LR) and random forest (RF) model were developed using univariate feature selection. Additionally, factor analysis was performed, and the derived factors were combined with clinical data in a predictive model to assess the performance on predicting HPV status. Additionally, factors were combined with clinical parameters in a multivariable survival regression analysis.

RESULTS

Both feature-based LR and RF models performed with an AUC of 0.79 in prediction of HPV status. Fourteen of the twenty most significant features were similar in both models, mainly concerning tumor sphericity, intensity variation, compactness, and tumor diameter. The model combining clinical data and radiomic factors (AUC = 0.89) outperformed the radiomics-only model in predicting OPSCC HPV status. Overall survival prediction was most accurate using the combination of clinical parameters and radiomic factors (C-index = 0.72).

CONCLUSION

Predictive models based on MR-radiomic features were able to predict HPV status with sufficient performance, supporting the role of MRI-based radiomics as potential imaging biomarker. Survival prediction improved by combining clinical features with MRI-based radiomics.

MRI can reliably differentiate optic nerve inflammation from tumor invasion in retinoblastoma with orbital cellulitis

OBJECTIVE

To investigate prevalence and MRI phenotype of retinoblastoma-associated orbital cellulitis. Additionally, this study aimed to identify postlaminar optic nerve enhancement patterns differentiating between inflammation and tumor invasion.

DESIGN

A monocenter cohort study assessed the prevalence of orbital cellulitis features on MRI in retinoblastoma patients. A multicenter case-control study compared MRI features of the retinoblastoma-associated orbital cellulitis cases with retinoblastoma controls.

SUBJECTS

A consecutive retinoblastoma patient cohort of 236 patients (311 eyes) was retrospectively investigated. Subsequently, 30 retinoblastoma cases with orbital cellulitis were compared with 30 matched retinoblastoma controls without cellulitis.

METHODS

In the cohort study, retinoblastoma MRI scans were scored on presence of inflammatory features. In the case-control study MRI scans were scored on intraocular features and postlaminar optic nerve enhancement patterns. Postlaminar enhancement patterns were compared with histopathologic assessment of postlaminar tumor invasion. Interreader agreement was assessed and exact tests with Bonferroni-correction were adopted for statistical comparisons.

MAIN OUTCOME MEASURES

Prevalence of retinoblastoma-associated orbital cellulitis on MRI was calculated. Frequency of intra-ocular MRI features were compared between orbital cellulitis cases and controls. Sensitivity and specificity of postlaminar optic nerve patterns for detection of postlaminar tumor invasion was assessed.

RESULTS

The MRI prevalence of retinoblastoma-associated orbital cellulitis was 6.8% (16/236). Retinoblastoma with orbital cellulitis showed significantly more tumor necrosis, uveal abnormalities (inflammation, hemorrhage and necrosis), lens luxation (all P < 0.001), and a larger eye size (P = 0.012). The inflammatory pattern of optic nerve enhancement (strong enhancement similar to adjacent choroid) was solely found in orbital cellulitis cases, of which none (0/16) showed tumor invasion on histopathology. Of patients with invasive pattern enhancement, 50% (5/10) showed tumor invasion on histopathology. Considering these different enhancement patterns, i.e. suggestive for either inflammation or tumor invasion, increased specificity for detection of postlaminar tumor invasion within the context of orbital cellulitis from 32% (95%CI:16-52%) to 89% (95%CI:72-98%).

CONCLUSIONS

Retinoblastoma cases presenting with orbital cellulitis show MRI findings of a larger eye size, extensive tumor necrosis, uveal abnormalities, and lens luxation. MRI contrast enhancement patterns within the postlaminar optic nerve can differentiate between tumor invasion and inflammatory changes.

MR Imaging Features to Differentiate Retinoblastoma from Coats' Disease and Persistent Fetal Vasculature

Simple Summary

Retinoblastoma is a rare cancer that develops in the retina of children. Accurate differentiation between retinoblastoma and conditions that show similarities with retinoblastoma (pseudoretinoblastoma or retinoblastoma mimickers) is vital for guiding treatment. The most common pseudoretinoblastoma conditions are Coats’ disease and persistent fetal vasculature (PFV). In this study, we aimed to improve pretreatment differentiation between these diseases on MR imaging. We compared pre-treatment MR images of retinoblastoma, Coats’ disease and PFV on 20 predefined MR imaging features. An assessment strategy was proposed incorporating MR imaging features that best differentiate retinoblastoma from pseudoretinoblastoma, including three newly identified MR imaging features.

Abstract

Retinoblastoma mimickers, or pseudoretinoblastoma, are conditions that show similarities with the pediatric cancer retinoblastoma. However, false-positive retinoblastoma diagnosis can cause mistreatment, while false-negative diagnosis can cause life-threatening treatment delay. The purpose of this study is to identify the MR imaging features that best differentiate between retinoblastoma and the most common pseudoretinoblastoma diagnoses: Coats’ disease and persistent fetal vasculature (PFV). Here, six expert radiologists performed retrospective assessments (blinded for diagnosis) of MR images of patients with a final diagnosis based on histopathology or clinical follow-up. Associations between 20 predefined imaging features and diagnosis were assessed with exact tests corrected for multiple hypothesis testing. Sixty-six patients were included, of which 33 (50%) were retinoblastoma and 33 (50%) pseudoretinoblastoma patients. A larger eye size, vitreous seeding, and sharp-V-shaped retinal detachment were almost exclusively found in retinoblastoma (p < 0.001–0.022, specificity 93–97%). Features that were almost exclusively found in pseudoretinoblastoma included smaller eye size, ciliary/lens deformations, optic nerve atrophy, a central stalk between optic disc and lens, Y-shaped retinal detachment, and absence of calcifications (p < 0.001–0.022, specificity 91–100%). Additionally, three newly identified imaging features were exclusively present in pseudoretinoblastoma: intraretinal macrocysts (p < 0.001, 38% [9/24] in Coats’ disease and 20% [2/10] in PFV), contrast enhancement outside the solid lesion (p < 0.001, 30% [7/23] in Coats’ disease and 57% [4/7] in PFV), and enhancing subfoveal nodules (38% [9/24] in Coats’ disease). An assessment strategy was proposed for MR imaging differentiation between retinoblastoma and pseudoretinoblastoma, including three newly identified differentiating MR imaging features.