Development and validation of radiomic signature for predicting overall survival in advanced-stage cervical cancer

BackgroundThe role of artificial intelligence and radiomics in prediction model development in cancer has been increasing every passing day. Cervical cancer is the 4th most common cancer in women worldwide, contributing to 6.5% of all cancer types. The treatment outcome of cervical cancer patients varies and individualized prediction of disease outcome is of paramount importance.PurposeThe purpose of this study is to develop and validate the digital signature for 5-year overall survival prediction in cervical cancer using robust CT radiomic and clinical features.Materials and MethodsPretreatment clinical features and CT radiomic features of 68 patients, who were treated with chemoradiation therapy in our hospital, were used in this study. Radiomic features were extracted using an in-house developed python script and pyradiomic package. Clinical features were selected by the recursive feature elimination technique. Whereas radiomic feature selection was performed using a multi-step process i.e., step-1: only robust radiomic features were selected based on our previous study, step-2: a hierarchical clustering was performed to eliminate feature redundancy, and step-3: recursive feature elimination was performed to select the best features for prediction model development. Four machine algorithms i.e., Logistic regression (LR), Random Forest (RF), Support vector classifier (SVC), and Gradient boosting classifier (GBC), were used to develop 24 models (six models using each algorithm) using clinical, radiomic and combined features. Models were compared based on the prediction score in the internal validation.ResultsThe average prediction accuracy was found to be 0.65 (95% CI: 0.60–0.70), 0.72 (95% CI: 0.63–0.81), and 0.77 (95% CI: 0.72–0.82) for clinical, radiomic, and combined models developed using four prediction algorithms respectively. The average prediction accuracy was found to be 0.69 (95% CI: 0.62–0.76), 0.79 (95% CI: 0.72–0.86), 0.71 (95% CI: 0.62–0.80), and 0.72 (95% CI: 0.66–0.78) for LR, RF, SVC and GBC models developed on three datasets respectively.ConclusionOur study shows the promising predictive performance of a robust radiomic signature to predict 5-year overall survival in cervical cancer patients

Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology

Cancer is a fatal disease and the second most cause of death worldwide. Treatment of cancer is a complex process and requires a multi-modality-based approach. Cancer detection and treatment starts with screening/diagnosis and continues till the patient is alive. Screening/diagnosis of the disease is the beginning of cancer management and continued with the staging of the disease, planning and delivery of treatment, treatment monitoring, and ongoing monitoring and follow-up. Imaging plays an important role in all stages of cancer management. Conventional oncology practice considers that all patients are similar in a disease type, whereas biomarkers subgroup the patients in a disease type which leads to the development of precision oncology. The utilization of the radiomic process has facilitated the advancement of diverse imaging biomarkers that find application in precision oncology. The role of imaging biomarkers and artificial intelligence (AI) in oncology has been investigated by many researchers in the past. The existing literature is suggestive of the increasing role of imaging biomarkers and AI in oncology. However, the stability of radiomic features has also been questioned. The radiomic community has recognized that the instability of radiomic features poses a danger to the global generalization of radiomic-based prediction models. In order to establish radiomic-based imaging biomarkers in oncology, the robustness of radiomic features needs to be established on a priority basis. This is because radiomic models developed in one institution frequently perform poorly in other institutions, most likely due to radiomic feature instability. To generalize radiomic-based prediction models in oncology, a number of initiatives, including Quantitative Imaging Network (QIN), Quantitative Imaging Biomarkers Alliance (QIBA), and Image Biomarker Standardisation Initiative (IBSI), have been launched to stabilize the radiomic features

Antigenicity and immunogenicity of differentially glycosylated HCV E2 envelope proteins expressed in mammalian and insect cells

Development of a prophylactic vaccine for hepatitis C virus (HCV) remains a global health challenge. Cumulative evidence supports the importance of antibodies targeting the HCV E2 envelope glycoprotein to facilitate viral clearance. However, a significant challenge for a B cell-based vaccine is focusing the immune response on conserved E2 epitopes capable of eliciting neutralizing antibodies not associated with viral escape. We hypothesized that glycosylation might influence the antigenicity and immunogenicity of E2. Accordingly, we performed head-to-head molecular, antigenic and immunogenic comparisons of soluble E2 (sE2) produced in (i) mammalian (HEK293) cells, which confer mostly complex and high mannose type glycans; and (ii) insect (Sf9) cells, which impart mainly paucimannose type glycans. Mass spectrometry demonstrated that all 11 predicted N-glycosylation sites were utilized in both HEK293- and Sf9-derived sE2, but that N-glycans in insect sE2 were on average smaller and less complex. Both proteins bound CD81 and were recognized by conformation-dependent antibodies. Mouse immunogenicity studies revealed that similar polyclonal antibody responses were generated against antigenic domains A–E of E2. Although neutralizing antibody titers showed that Sf9-derived sE2 induced moderately stronger responses than HEK293-derived sE2 against the homologous HCV H77c isolate, the two proteins elicited comparable neutralization titers against heterologous isolates. Given that global alteration of HCV E2 glycosylation by expression in different hosts did not appreciably affect antigenicity or overall immunogenicity, a more productive approach to increasing the antibody response to neutralizing epitopes may be complete deletion, rather than just modification, of specific N-glycans proximal to these epitopes

A rare variant of Caffey's disease – X-rays, bone scan and FDG PET findings

An 18-month-old boy with history of fever of 4 months duration and with swelling of the limbs was referred for a bone scan. There were multiple swellings over his upper and lower limbs, with bowing of the lower limbs. His radiological skeletal survey revealed marked periosteal new bone formation surrounding the diaphysis of long bones. A bone scan done with 99m Tc-MDP showed diffusely increased tracer uptake in all the long bones. A fluorodeoxyglucose positron emission tomography (FDG PET) scan done to assess the metabolic activity showed patchy FDG uptake in the long bones, ankle joint and anterior ends of few ribs. His clinical and imaging findings led to the diagnosis of Caffey's disease

PET/CT: Current status in India

PET/CT is a new modality with integration of PET and CT systems. In India, since December 2004 there has been a steady increase in the number of imaging systems. From stand-alone PET/CT systems with on-site cyclotrons, mostly in the government sector, the modality has matured to such an extent that, today, the majority of the PET/CT scanners and cyclotrons are in the private setup; also, scanners situated in different locations (and even different cities) share the isotope produced from one cyclotron. This shows how much this field has developed and reflects the confidence of the end users. The current status of PET/CT in India is indeed healthy and heartening and the future certainly looks promising

A pictoral review on somatostatin receptor scintigraphy in neuroendocrine tumors: The role of multimodality imaging with SRS and GLUT receptor imaging with FDG PET-CT

Somatostatin receptor scintigraphy is considered as a comprehensive imaging modality for many neuroendocrine tumors. Multiple radiotracers using combinations of gamma or positron emitting radionuclides and tracers are now available. Newer radiopharmaceuticals using 99m Tc labeled with TOC, TATE, NOC are good alternatives to the 68 - Gallium radiotracers where the PET facility is not available. The pictoral depicts the role of SRS using 99mTC - HYNIC -TOC radiotracers in staging and treatment planning of NETs. Characterization of the tumor biology using combined SRS and FDG PET/CT is also demonstrated with a proposed categorization method. The emerging role of SRS in tailored targeted radionuclide therapy is outlined in brief

Dosimetry in Lu-177-PSMA-617 prostate-specific membrane antigen targeted radioligand therapy:a systematic review

BACKGROUND: 177Lu-prostate-specific membrane antigen (PSMA) gained popularity as a choice of agent in the treatment of patients with advanced prostate cancer or metastatic castration-resistant stage of prostate carcinoma (mCRPC) diseases. However, this treatment may cause fatal effects, probably due to unintended irradiation of normal organs. We performed an extensive systematic review to assess the organs at risk and the absorbed dose received by tumor lesions in 177Lu-PSMA therapy. DESIGN: In this review, published peer-reviewed articles that cover clinical dosimetry in patients following peptide radionuclide ligand therapy using 177Lu-PSMA have been included. Two senior researchers independently checked the articles for inclusion. A systematic search in the database was made using PubMed, Publons and DOAJ. All selected articles were categorized into three groups: (1) clinical studies with the technical description of dosimetry in 177Lu-PSMA therapy (2) organ dosimetry in 177Lu-PSMA therapy or (3) tumor dosimetry in 177Lu-PSMA therapy. RESULT: In total, 182 citations were identified on PSMA therapy and 17 original articles on 177Lu-PSMA dosimetry were recognized as eligible for review. The median absorbed dose per unit of administered activity for kidneys, salivary, liver, spleen, lacrimal and bone marrow was 0.55, 0.81, 0.1, 0.1, 2.26 and 0.03 Gy/GBq, respectively. The median absorbed dose per unit of activity for tumor lesions was found in a range of 2.71-10.94 Gy/GBq. CONCLUSION: 177Lu-PSMA systemic radiation therapy (SRT) is a well-tolerated and reliable treatment option against the management of the mCRPC stage of prostate carcinoma. Lacrimal glands and salivary glands are the major critical organs in 177Lu-PSMA SRT. Besides, tumors receive 3-6 times higher absorbed doses compared to organs at risk