Publications

BACKGROUND: Head and neck squamous cell carcinoma is often treated with radiotherapy, frequently combined with chemotherapy, to improve overall survival (OS). Despite advancements, locoregional control (LRC) remains a significant challenge, with 15%-50% of patients experiencing locoregional recurrence, negatively impacting OS and quality of life. Hypoxia within tumor cells is a critical factor contributing to treatment failure, necessitating higher radiation doses to achieve similar therapeutic effects as in normoxic cells. This study aims to investigate the role of dose escalation using [18F] fluoromisonidazole (FMISO) positron emission tomography/computed tomography (PET CT) to target hypoxic sub-volumes in head and neck cancer (HNC) to improve LRC.

METHODS: The dose-escalated hypoxia-adjusted radiotherapy trial is an open-label, parallel, randomised, single-centre, phase II study. Patients with HNC will undergo [18F]. FMISO PET CT to identify hypoxic regions. Normoxic patients will be labeled as Arm 1 and will not be part of the primary assessment. Patients with hypoxia will be stratified into two arms (2 and 3). Arm 2 will receive standard radiotherapy of 70 Gy in 2 Gy fractions, while Arm 3 will receive an additional boost to the hypoxic sub-volumes, delivering a total of 80 Gy (Phase 2). All patients in Arms 2 and 3 will also receive concurrent chemotherapy with cisplatin. Patients will be monitored weekly for treatment tolerance, with acute adverse events recorded according to National Cancer Institute Common Terminology Criteria for Adverse Events v5.0. The primary endpoint is LRC, defined as the time from randomisation to the first histopathologically confirmed relapse of locoregional disease. Secondary endpoints include OS, locoregional relapse-free survival, acute and late toxicity and patient-reported outcomes assessed using the European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-H&N35 questionnaires.

DISCUSSION: This study addresses a critical gap in the management of HNC by targeting hypoxic regions within tumours, potentially improving LRC and, consequently, OS. The use of [18F] FMISO PET CT for identifying hypoxic sub-volumes allows for tailored radiation dose escalation, which could overcome the radioresistance associated with hypoxia. By comparing outcomes among standard radiotherapy (Arm 2) and dose-escalated treatment (Arm 3), this trial aims to establish a more effective therapeutic strategy for HNC patients.

TRIAL REGISTRATION: This trial is registered with the Clinical Trials Registry of India (CTRI/2024/04/065373), registered on 08th April 2024 on ctri.nic.in and clinicaltrials.gov (NCT06087614) registered on 18th September 2023 on clinicaltrials.gov.

BACKGROUND: Advanced laryngeal carcinoma (LC) has a poor prognosis with limited treatment options. Managing oligometastasis is challenging, and there are currently no standard recommendations.

METHODS: We reported a case of a 64-year-old male with locally advanced LC who developed oligometastatic disease in the bones and liver 21 months after concurrent cisplatin-based chemoradiotherapy. Initially, due to negative PD-L1 expression, the patient was treated docetaxel, cisplatin and cetuximab combination. Chemotherapy after 10 months, new hepatic progression was confirmed by biopsy. Given the asymptomatic, single-site progression in a cirrhotic liver, microwave ablation was performed. Isolated bone progressions were treated with stereotactic body radiation therapy at 2 and 4 months, and nivolumab replaced cetuximab.

RESULTS: The patient has shown no evidence of disease progression for 22 months, with excellent tolerance.

CONCLUSION: The synergy between nivolumab and local therapies appears promising for managing oligometastasis in laryngeal cancer.

Metastatic castration-resistant prostate cancer (mCRPC) remains a formidable clinical challenge despite advancements in therapy. This narrative review explores the role of artificial intelligence (AI), machine learning and deep learning in addressing therapeutic resistance in mCRPC. AI-driven approaches leverage integrated datasets encompassing genomics, proteomics and clinical parameters to uncover molecular mechanisms, predict treatment responses and identify biomarkers of resistance. These methodologies promise personalised treatment strategies tailored to individual patient profiles. However, data heterogeneity and regulatory considerations are challenges that hinder the translation of AI insights into clinical practice. By synthesising current literature, this review examines the progress, potential and limitations of AI applications in combating therapeutic resistance in mCRPC, highlighting implications for future research and clinical implementation.

PURPOSE: To evaluate discrete wavelet transform (DWT) features as quantitative biomarkers of macular cone function from pattern electroretinography (PERG) in macular-predominant inherited retinal diseases (mpIRDs).

METHODS: In total, 486 PERG recordings from 123 participants were obtained from the PERG-Institute of Applied Ophthalmobiology open-access data set and analyzed. Twenty mother wavelets were screened with an energy-to-entropy ratio criterion; six (haar, sym2, sym4, db4, coif1, fk4) were retained for feature generation. After feature cleaning and correlation pruning, a final set of 141 features was obtained and averaged per participant to avoid visit bias. Group separation was assessed with nonparametric statistics. Inverse-DWT signal reconstruction was performed with the sym2 wavelet to algorithmically determine time-frequency indices needed to preserve N35, P50, and N95 peaks. The smallest set of indices that achieved this was retained.

RESULTS: Sym2-D6-2 (38-75 ms, 13-27 Hz) emerged as the top discriminative feature (res = 0.644, common-language effect size = 0.875) and correlated strongly with the clinical macular cone marker |P50-N35| (rcorr = 0.95) across 67 normal participants (262 recordings). Compared with |P50-N35|, the same index showed tighter, nonoverlapping group distributions, a higher diagnostic area under the curve (0.875 vs. 0.835), and a larger effect size (res = 0.644 vs. 0.576).

CONCLUSIONS: DWT-derived time-frequency features, particularly sym2-D6-2, provide robust, multidimensional biomarkers of macular cone function. These quantitative endpoints hold promise for monitoring disease progression and evaluating therapeutics in mpIRDs.

TRANSLATIONAL RELEVANCE: Sym2-D6-2 provides an objective metric of macular cone function that could serve as a quantitative endpoint in mpIRD trials.

Studies of visual face processing often use flat images as proxies for real faces due to their ease of manipulation and experimental control. Although flat images capture many features of a face, they lack the rich three-dimensional (3D) structural information available when binocularly viewing real faces (e.g., binocular cues to a long nose). We used functional magnetic resonance imaging to investigate the contribution of naturalistic binocular depth information to univariate activation levels and multivariate activation patterns in depth- and face-selective human brain regions. We used two cameras to capture images of real people from the viewpoints of the two eyes. These images were presented with natural viewing geometry (such that the size, distance, and binocular disparities were comparable to a real face at a typical viewing distance). Participants viewed stereopairs under four conditions: accurate binocular disparity (3D), zero binocular disparity (two-dimensional [2D]), reversed binocular disparity (pseudoscopic 3D), and no binocular disparity (monocular 2D). Although 3D faces (both 3D and pseudoscopic 3D) elicited higher activation levels than 2D faces, as well as distinct activation patterns, in depth-selective occipitoparietal regions (V3A, V3B, IPS0, IPS1, hMT+), face-selective occipitotemporal regions (OFA, FFA, pSTS) showed limited sensitivity to internal facial disparities. These results suggest that 2D images are a reasonable proxy for studying the neural basis of face recognition in face-selective regions, although contributions from 3D structural processing within the dorsal visual stream warrant further consideration.