PCPankaj Chaturvedi

Pankaj Chaturvedi

*This is an algorithmically generated author record based on publicly available information.

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Pankaj Chaturvedi has a total of 29 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Imaging-Based Tumor Margin Patterns and Primary Tumor Categories and Their Association with Adverse Histopathological Features in Oral Tongue Squamous Cell Carcinoma

    by Nivedita Chakrabarty, Tapish Dadlani, Abhishek Mahajan, Arjun Singh, Swapnil Rane, Sarbani Ghosh Laskar, Ankush Shetake, Vanita Noronha, Kumar Prabhash, Pankaj Chaturvedi

    Background: This retrospective study introduces imaging inner tumor margin patterns (iITMP) and evaluates their correlation with pathological Worst pattern of invasion (WPOI) in oral tongue squamous cell carcinoma (OTSCC). Associations of iITMP with pathological primary tumor category (pT), histologic grade, perineural invasion (PNI), nodal metastasis, and extranodal extension (ENE) were assessed. Correlations between imaging depth of invasion (iDOI) and pathological DOI (pDOI), and between imaging primary tumor (iT) and pT, PNI, and ENE were evaluated. Methods: Baseline magnetic resonance imaging (MRI) from January 2021 to December 2022 of 224 upfront-operated OTSCC patients was reviewed by two blinded radiologists using contrast-enhanced thin-slice. iITMP (types 1–3) were classified based on inner tumor margin morphology. iDOI was measured after excluding peritumoral hyperenhancement. Correlation between categorical and continuous variables were assessed using Kappa statistics and Spearman’s test respectively. Associations between categorical variables were analyzed using Fisher’s exact or Pearson’s chi-squared tests. Univariable and multivariable analyses were additionally performed. Results: The mean patient age was 47 ± 11 years. Substantial agreement was observed between iITMP and WPOI, and between iT and pT. iDOI strongly correlated with pDOI. iITMP was significantly associated with pT, irregular (iITMP2) and infiltrative (iITMP3) margins were associated with PNI only on univariate analysis, while iITMP was not an independent predictor on multivariable analysis. iT significantly correlated with PNI and ENE. Conclusions: iITMP strongly correlate with WPOI and is substantially associated with pT categories. iT categories show significant association with PNI and ENE. Therefore, iITMP and iT may serve as potential imaging biomarkers of adverse histopathological features in OTSCC.

  • Open Access

    Decoding Osteoradionecrosis of the Jaw: Radiological Progression and a Novel CT-Based Grading System

    by Vasundhara Patil, Pritesh Shah, Abhishek Mahajan, Nilesh Sable, Anuradha Shukla, Gauri Bornak, Swapnil Rane, Sandeep Gurav, Sarbani Ghosh Laskar, Gouri Pantvaidya, et al.

    Background: Osteoradionecrosis (ORN) of the jaw is a severe, progressive complication of radiation therapy for head and neck malignancies. ORN features radiologically overlaps osteomyelitis and tumor recurrence. This study analyzes jaw ORN imaging characteristics and progression and proposes an ORN CT-based grading system that builds on current ClinRAD grades. Materials and Methods: A retrospective cohort study of 35 patients with biopsy-proven or clinically diagnosed ORN following radiation therapy. Initial and follow-up imaging were assessed to evaluate the radiological evolution of ORN. The imaging findings were statistically analyzed using IBM SPSS v26, and literature comparisons were made. Results: The median onset of ORN post-radiotherapy was 27–28 months (range: 2–119 months). The most common clinical presentations included non-healing ulcers (49%), pain (34%), and discharging sinuses (31%). Mandibular involvement was predominant (51%), with focal bone alterations being more frequent (63%). CT findings at clinical suspicion of ORN included resorption (100%), erosions (100%), sclerosis (86%), and fragmentation (83%). Follow-up imaging showed increased bone erosion (77%), fragmentation (92%), and sclerosis (92%). A CT-based grading system is proposed to classify ORN progression. Conclusions: ORN follows a predictable radiological progression, beginning with trabecular resorption and cortical erosion, leading to fragmentation and sequestrum formation. The proposed grading system provides a structured approach for early diagnosis. The proposed grading system provides a structured approach for diagnosis. Larger studies of imaging analyses are required to validate these findings and refine diagnostic criteria.