Semiautomated volumetric response evaluation as an imaging biomarker in superior sulcus tumors

Volumetric tumor response assessment is inefficient without overt clinical benefit compared to conventional, manual veterinary response assessment in canine nasal tumors

Accurate assessment of tumor response to therapy is critical in guiding management of veterinary oncology patients and is most commonly performed using response evaluation criteria in solid tumors criteria. This process can be time consuming and have high intra- and interobserver variability. The primary aim of this serial measurements, secondary analysis study was to compare manual linear tumor response assessment to semi-automated, contoured response assessment in canine nasal tumors. The secondary objective was to determine if tumor measurements or clinical characteristics, such as stage, would correlate to progression-free interval. Three investigators evaluated paired CT scans of skulls of 22 dogs with nasal tumors obtained prior to and following radiation therapy. The automatically generated tumor volumes were not useful for canine nasal tumors in this study, characterized by poor intraobserver agreement between automatically generated contours and hand-adjusted contours. The radiologist's manual linear method of determining response evaluation criteria in solid tumors categorization and tumor volume is significantly faster (P < .0001) but significantly underestimates nasal tumor volume (P < .05) when compared to a contour-based method. Interobserver agreement was greater for volume determination using the contour-based method when compared to response evaluation criteria in solid tumors categorization utilizing the same method. However, response evaluation criteria in solid tumors categorization and percentage volume change were strongly correlated, providing validity to response evaluation criteria in solid tumors as a rapid method of tumor response assessment for canine nasal tumors. No clinical characteristics or tumor measurements were significantly associated with progression-free interval.

Trimodality therapy for Pancoast tumors: T4 is not a contraindication to radical surgery

OBJECTIVE

This study aims to evaluate the impact of T stage and extended surgery on the outcome of patients with Pancoast tumors after induction chemoradiation therapy.

METHODS

Forty-six consecutive patients who underwent chemoradiation therapy (platin-based, 45-66 Gy) followed by surgery between 1998 and 2013 were retrospectively reviewed and analyzed.

RESULTS

In 28 (61%) patients with T4 tumors, extended procedures (more than rib resection) were performed. There were 37 (80%) lobectomies, 6 (13%) pneumonectomies, and 3 (7%) sublobar resections. A total of 44 (96%) patients had R0 resection. About 30-day mortality was 0%, major surgical complications occurred in 9 (19.6%) patients. Overall survival (OS) at 5-years was 63%. Disease-free survival (DFS) at 5-years was 45%. At multivariate cox regression analysis adjusted for clinical factors, T factor (T3/T4) and extended surgical procedures did not impact survival. However, pathological positive N stage had a negative impact on OS and lack of pathological response negatively impacted both OS and DFS.

CONCLUSION

Trimodality treatment including radical resection for Pancoast tumors provides good surgical outcome and favorable long-term results. Survival of patients with T4 tumors and extended surgical procedures comparable to that of patients with T3 tumors undergoing rib resection only.

Emerging Role of MRI for Radiation Treatment Planning in Lung Cancer

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and allows for specific scanning sequences to optimize differentiation between various tissue types and properties. Moreover, it offers the potential for real-time motion imaging. This makes magnetic resonance imaging an ideal candidate imaging modality for radiation treatment planning in lung cancer. Although the number of clinical research protocols for the application of magnetic resonance imaging for lung cancer treatment is increasing (www.clinicaltrials.gov) and the magnetic resonance imaging sequences are becoming faster, there are still some technical challenges. This review describes the opportunities and challenges of magnetic resonance imaging for radiation treatment planning in lung cancer.