Anesthetic choices and breast cancer recurrence: A retrospective cohort study of risk factors

Background: The impact of anesthetic techniques for breast cancer surgery traditionally has been centered on the incidence of acute pain syndromes and complications immediately after surgery. Evaluating anesthesia management beyond short-term effects is an emerging science. Several animal studies have concluded that regional anesthesia independently reduces cancer recurrence and metastasis. A small number of retrospective clinical studies indicate that reductions in cancer recurrence are attributable to anesthesia technique; however, individual risk factors need to be taken into consideration. ^ Purpose: The aims were to: 1) investigate differences in patient, disease and treatment factors between women who received surgical treatment for breast cancer with paravertebral regional and general anesthesia compared to women who received general anesthesia alone; 2) explore patient, disease and treatment factors associated with recurrence of breast cancer; and 3) test the association between type of anesthesia and breast cancer recurrence and survival over 22–46 months following surgery. ^ Methods: This retrospective cohort study included 358 patients with stage 0-III disease who received a partial or total mastectomy without axillary node dissection between October 2006 and October 2008 at a large academic cancer center. Follow-up ended in August 2010 with a median follow-up time of 28.8 months. ^ Results: The patient demographics were equally represented across anesthesia groups. Mean BMI (kg/m2) was greater for the patients who received general anesthesia (GA) alone (29±6.8) compared to those that received paravertebral regional block (PVB) with GA (28±5.1), p=0.001. The PVB with GA group had more advanced stages of disease (p=0.01) and longer surgeries (p=0.01) than the GA only group. Breast cancer recurrence was detected in only 1.7% of the study population. The mean age was 51±18 in those who had a recurrence compared to 58±11 in the non-recurrent group (p=0.06). Overall, no association between anesthesia type and recurrence was found (p=0.53), with an unadjusted estimated hazard ratio of 1.84 (95% CI 0.34–10.08). ^ Conclusions: In contrast to previous retrospective studies in cancer patients receiving surgical and anesthesia treatment, this study was unable to detect a difference in relating type of anesthesia with decreased breast cancer recurrence. Nonetheless, a significant association between BMI and type of anesthesia was observed and should be taken into account in future studies. Because the overall rate of recurrence was very small in this population, a larger study would be needed to detect any differences in rates of recurrence attributable to type of anesthesia. ^

Evaluation of deformable image registration for improved 4D CT-derived ventilation for image guided radiotherapy

Recent treatment planning studies have demonstrated the use of physiologic images in radiation therapy treatment planning to identify regions for functional avoidance. This image-guided radiotherapy (IGRT) strategy may reduce the injury and/or functional loss following thoracic radiotherapy. 4D computed tomography (CT), developed for radiotherapy treatment planning, is a relatively new imaging technique that allows the acquisition of a time-varying sequence of 3D CT images of the patient's lungs through the respiratory cycle. Guerrero et al. developed a method to calculate ventilation imaging from 4D CT, which is potentially better suited and more broadly available for IGRT than the current standard imaging methods. The key to extracting function information from 4D CT is the construction of a volumetric deformation field that accurately tracks the motion of the patient's lungs during the respiratory cycle. The spatial accuracy of the displacement field directly impacts the ventilation images; higher spatial registration accuracy will result in less ventilation image artifacts and physiologic inaccuracies. Presently, a consistent methodology for spatial accuracy evaluation of the DIR transformation is lacking. Evaluation of the 4D CT-derived ventilation images will be performed to assess correlation with global measurements of lung ventilation, as well as regional correlation of the distribution of ventilation with the current clinical standard SPECT. This requires a novel framework for both the detailed assessment of an image registration algorithm's performance characteristics as well as quality assurance for spatial accuracy assessment in routine application. Finally, we hypothesize that hypo-ventilated regions, identified on 4D CT ventilation images, will correlate with hypo-perfused regions in lung cancer patients who have obstructive lesions. A prospective imaging trial of patients with locally advanced non-small-cell lung cancer will allow this hypothesis to be tested. These advances are intended to contribute to the validation and clinical implementation of CT-based ventilation imaging in prospective clinical trials, in which the impact of this imaging method on patient outcomes may be tested.