In-utero ultrasonography detection of fetal retinoblastoma and neonatal selective ophthalmic artery chemotherapy

Impact of RB1 gene screening from blood collected on a single day from 411 family members of 113 Retinoblastoma survivors in India

OBJECTIVES

To analyse the profile and implication of genetic testing in a cohort of retinoblastoma (RB) patients and their families conducted on a single day during World Retinoblastoma Awareness Week 2017.

METHODS

Retrospective analysis of blood samples were collected from 411 subjects, including 113 probands at a camp organised for RB awareness and were analysed for RB1 mutations by Sanger sequencing and Multiplex Ligation-dependent Probe Amplification (MLPA). If germline mutations were detected, the parents and siblings of the proband were tested for the same mutation.

RESULTS

Germline RB1 mutations were identified in 61/113(54%) probands with a mutation detection rate of 96% (47/49) and 22% (14/64) for bilateral and unilateral RB, respectively. Ten novel pathogenic mutations were identified. Splice mutation was most common (31%) followed by nonsense mutation (26%). The mean age at RB diagnosis was significantly lower in patients having germline RB1 mutation (mean 10.7 months ±2.5) compared to those without (mean 27.2 months ±6.5) (p = <0.0001). Parental transmission of the mutant allele was detected in 15/61(25%) cases of which 11(18%) parents were unaffected indicating incomplete penetrance. The origin of the variant allele was both paternal (n = 7) and maternal (n = 4) wherein 5 were bilateral and 6 unilateral.

CONCLUSIONS

The detection of a germline mutation impacts the proband and family members due to its implications on change in prognosis, frequency of subsequent evaluations, screening for ocular and non-ocular cancers, and surveillance of family and future progeny.

Retinoblastoma: present scenario and future challenges

With an average incidence of 1 in every 18,000 live births, retinoblastoma is a rare type of intraocular tumour found to affect patients during their early childhood. It is curable if diagnosed at earlier stages but can become life-threateningly malignant if not treated timely. With no racial or gender predisposition, or even environmental factors known to have been involved in the incidence of the disease, retinoblastoma is often considered a clinical success story in pediatric oncology. The survival rate in highly developed countries is higher than 95% and they have achieved this because of the advancement in the development of diagnostics and treatment techniques. This includes developing the already existing techniques like chemotherapy and embarking on new strategies like enucleation, thermotherapy, cryotherapy, etc. Early diagnosis, studies on the etiopathogenesis and genetics of the disease are the need of the hour for improving the survival rates. According to the Knudson hypothesis, also known as the two hit hypothesis, two hits on the retinoblastoma susceptibility (RB) gene is often considered as the initiating event in the development of the disease. Studies on the molecular basis of the disease have also led to deciphering the downstream events and thus in the discovery of biomarkers and related targeted therapies. Furthermore, improvements in molecular biology techniques enhanced the development of efficient methods for early diagnosis, genetic counseling, and prevention of the disease. In this review, we discuss the genetic and molecular features of retinoblastoma with a special emphasis on the mutation leading to the dysregulation of key signaling pathways involved in cell proliferation, DNA repair, and cellular plasticity. Also, we describe the classification, clinical and epidemiological relevance of the disease, with an emphasis on both the traditional and innovative treatments to tackle retinoblastoma. Video Abstract.

Explainable AI for Retinoblastoma Diagnosis: Interpreting Deep Learning Models with LIME and SHAP

Retinoblastoma is a rare and aggressive form of childhood eye cancer that requires prompt diagnosis and treatment to prevent vision loss and even death. Deep learning models have shown promising results in detecting retinoblastoma from fundus images, but their decision-making process is often considered a "black box" that lacks transparency and interpretability. In this project, we explore the use of LIME and SHAP, two popular explainable AI techniques, to generate local and global explanations for a deep learning model based on InceptionV3 architecture trained on retinoblastoma and non-retinoblastoma fundus images. We collected and labeled a dataset of 400 retinoblastoma and 400 non-retinoblastoma images, split it into training, validation, and test sets, and trained the model using transfer learning from the pre-trained InceptionV3 model. We then applied LIME and SHAP to generate explanations for the model's predictions on the validation and test sets. Our results demonstrate that LIME and SHAP can effectively identify the regions and features in the input images that contribute the most to the model's predictions, providing valuable insights into the decision-making process of the deep learning model. In addition, the use of InceptionV3 architecture with spatial attention mechanism achieved high accuracy of 97% on the test set, indicating the potential of combining deep learning and explainable AI for improving retinoblastoma diagnosis and treatment.

Recent advancements in the management of retinoblastoma and uveal melanoma

Retinoblastoma in children and uveal melanoma in adults can pose a serious threat to both vision and life. For many decades, enucleation was often the only option to treat these intraocular malignancies. For retinoblastoma, intra-arterial chemotherapy is often utilized as the primary treatment at advanced academic centers and has dramatically improved local tumor control and eye salvage rates. For uveal melanoma, both plaque brachytherapy and proton beam irradiation have served as widely utilized therapies with a local failure rate of approximately 1–10%, depending on the series. Major recent advancements have allowed for a better understanding of the genomics of uveal melanoma and the impact of certain mutations on metastatic susceptibility. Gene expression profile stratifies uveal melanomas into two classes: low-risk (class 1) and high-risk (class 2). A loss-of-function mutation of BAP1 is associated with a class 2 gene expression profile and therefore confers worse prognosis due to elevated risk of metastasis. On the other hand, gain-of-function mutations of EIF1AX and SF3B1 correspond to a gene expression profile of class 1A and class 1B and confer a better prognosis. Preferentially expressed antigen in melanoma (PRAME) is an antigen that increases metastatic susceptibility when expressed in uveal melanoma cells. In addition to plaque brachytherapy and proton beam irradiation, both of which have demonstrated superb clinical outcomes, scientists are actively investigating newer therapeutic modalities as either primary therapy or adjuvant treatment, including a novel nanoparticle therapy and immunotherapy.

Prenatal diagnosis of bilateral retinoblastomas by multimodality fetal imaging: case report and review of the literature

Retinoblastoma is the prototypic genetic tumor. Caused by mutations in the RB1 gene, retinoblastomas are heritable in 40% of the cases and, in such cases, tumors are bilateral in 80%, unilateral in 15%, and trilateral in 5% of the cases. Trilateral retinoblastoma is a term that describes bilateral retinoblastomas plus a midline suprasellar or pineal neuroectodermal tumor. Patients with a germline RB1 mutation have 45% chance of having an offspring with retinoblastoma. Prenatal diagnosis is important because the doubling time is fast, ranging from 7 to 15 days. Thus, late diagnosis during infancy is associated with larger tumors and increased risk of death, need for globe enucleation and vision loss. We report a case of bilateral retinoblastomas diagnosed by targeted high-resolution ultrasonography of the orbits at 32 weeks of gestation in a patient at risk. This report demonstrates the feasibility of accurately detecting even tiny retinoblastomas by ultrasound with current technology. We also review prenatally published cases to date and comment on the technical strengths and limitations of ultrasound and fetal MRI for prenatal diagnosis of retinoblastomas.