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Purpose: We evaluated the geometric and dosimetric-based distribution of mucosal and nodal recurrences in patients with metastatic head and neck squamous cell carcinoma to cervical lymph nodes of unknown primary after intensity modulated radiation therapy using validated typology-indicative taxonomy. Methods and Materials: We reviewed the data of 260 patients who were irradiated between 2000 and 2015 and had a median follow-up time for surviving patients of 61 months. The mucosal and nodal recurrences were manually delineated on computed tomography images demonstrating the recurrences. The images were overlaid on the treatment plan using deformable image registration. The locations of the recurrences were determined relative to the original planning target volumes and doses using centroid-based approaches. Subsequently, the pattern of failures were classified into 5 types based on combined spatial and dosimetric criteria: A (central high dose), B (peripheral high dose), C (central elective dose), D (peripheral elective dose), and E (extraneous dose). For patients with type A failure with simultaneous nontype A lesions, the overall pattern of failures was defined as type A. Results: Thirty-two patients had mucosal or nodal recurrences. The most common clinical nodal stage was N2b (66%). Preradiation therapy neck dissections were performed in 6 patients. The median dose delivered to clinical tumor volume 1 was 66 Gy. The majority (84%) had total/partial pharyngeal mucosa elective irradiation. Twenty-three patients had nodal recurrences, 8 had mucosal recurrences, and 1 had both nodal and mucosal recurrences. Twenty-one patients (91%) had type A nodal failure, and 7 of the mucosal failures (89%) were type C. Conclusions: The majority of nodal recurrences occurred within the high-dose area, demanding the need for identification of radioresistant areas within malignant nodes. Future studies should focus on either dose escalation of high-risk volumes or novel radiosensitizers.

Mouse models are powerful tools to study lung cancer initiation and progression in vivo and have contributed significantly to recent advances in therapy. Using micro-computed tomography to monitor and study parenchymal and extra-parenchymal metastases in existing murine models of lung cancer is challenging owing to a lack of radiographic contrast and difficulty in achieving respiratory gating. To facilitate the analysis of these in vivo imaging studies and study of tumor progression in murine models we developed a novel, rapid, semi-automated method of calculating thoracic tumor burden from computed tomography images. This method, in which commercially available software is used to calculate the mass of the thoracic cavity (MTC), takes into account the aggregate tumor burden in the thoracic cavity. The present study showed that in tumor-free mice, the MTC does not change over time and is not affected by breathing, whereas in tumor-bearing mice, the increase in the MTC is a measure of tumor mass that correlates well with tumor burden measured by lung weight. Tumor burden calculated with our MTC method correlated with that measured by lung weight as well as or better than that calculated using four established methods. To test this method, we assessed metastatic tumor development and response to a pharmacologic PLK1 inhibitor in an orthotopic xenograft mouse model. PLK1 inhibition significantly inhibited tumor growth. Our results demonstrate that the MTC method can be used to study dynamic changes in tumor growth and response to therapeutics in genetically engineered mouse models and orthotopic xenograft mouse models of lung cancer.