Clinical Utility of the 12-Gene DCIS Score Assay: Impact on Radiotherapy Recommendations for Patients with Ductal Carcinoma In Situ.

OBJECTIVE: The aim of this study was to determine the impact of the results of the 12-gene DCIS Score assay on (i) radiotherapy recommendations for patients with pure ductal carcinoma in situ (DCIS) following breast-conserving surgery (BCS), and (ii) patient decisional conflict and state anxiety. METHODS: Thirteen sites across the US enrolled patients (March 2014-August 2015) with pure DCIS undergoing BCS. Prospectively collected data included clinicopathologic factors, physician estimates of local recurrence risk, DCIS Score results, and pre-/post-assay radiotherapy recommendations for each patient made by a surgeon and a radiation oncologist. Patients completed pre-/post-assay decisional conflict scale and state-trait anxiety inventory instruments. RESULTS: The analysis cohort included 127 patients: median age 60 years, 80 % postmenopausal, median size 8 mm (39 % ≤5 mm), 70 % grade 1/2, 88 % estrogen receptor-positive, 75 % progesterone receptor-positive, 54 % with comedo necrosis, and 18 % multifocal. Sixty-six percent of patients had low DCIS Score results, 20 % had intermediate DCIS Score results, and 14 % had high DCIS Score results; the median result was 21 (range 0-84). Pre-assay, surgeons and radiation oncologists recommended radiotherapy for 70.9 and 72.4 % of patients, respectively. Post-assay, 26.4 % of overall recommendations changed, including 30.7 and 22.0 % of recommendations by surgeons and radiation oncologists, respectively. Among patients with confirmed completed questionnaires (n = 32), decision conflict (p = 0.004) and state anxiety (p = 0.042) decreased significantly from pre- to post-assay. CONCLUSIONS: Individualized risk estimates from the DCIS Score assay provide valuable information to physicians and patients. Post-assay, in response to DCIS Score results, surgeons changed treatment recommendations more often than radiation oncologists. Further investigation is needed to better understand how such treatment changes may affect clinical outcomes.

Comparison of standardized uptake value-based positron emission tomography and computed tomography target volumes in esophageal cancer patients undergoing radiotherapy.

PURPOSE: To study various standardized uptake value (SUV)-based approaches to ascertain the best strategy for delineating metabolic tumor volumes (MTV). METHODS AND MATERIALS: Twenty-two consecutive previously treated esophageal cancer patients with positron emission tomography (PET) imaging and computed tomography (CT)-based radiotherapy plans were studied. At the level of the tumor epicenter, MTVs were delineated at 11 different thresholds: SUV ≥2, ≥2.5, ≥3, ≥3.5 (SUV(n)); ≥40%, ≥45%, and ≥50% of the maximum (SUV(n%)); and mean liver SUV + 1, 2, 3, and 4 standard deviations (SUV(Lnσ)). The volume ratio and conformality index were determined between MTVs, and the corresponding CT/endoscopic ultrasound-based gross tumor volume (GTV) at the epicenter. Means were analyzed by one-way analysis of variance for repeated measures and further compared using a paired t test for repeated measures. RESULTS: The mean conformality indices ranged from 0.33 to 0.48, being significantly (p < 0.05) closest to 1 at SUV(2.5) (0.47 ± 0.03) and SUV(L4σ) (0.48 ± 0.03). The mean volume ratios ranged from 0.39 to 2.82, being significantly closest to 1 at SUV(2.5) (1.18 ± 0.36) and SUV(L4σ) (1.09 ± 0.15). The mean value of the SUVs calculated using the SUV(L4σ) approach was 2.4. CONCLUSIONS: Regardless of the SUV thresholding method used (i.e., absolute or relative to liver mean), a threshold of approximately 2.5 yields the highest conformality index and best approximates the CT-based GTV at the epicenter. These findings may ultimately aid radiation oncologists in the delineation of the entire GTV in esophageal cancer patients.

A Javascript library that uses Windows Script Host (WSH) to analyze prostate motion data fragmented across a multitude of Excel files by the Calypso 4D Localization System.

The Calypso 4D Localization System records prostate motion continuously during radiation treatment. It stores the data across thousands of Excel files. We developed Javascript (JScript) libraries for Windows Script Host (WSH) that use ActiveX Data Objects, OLE Automation and SQL to statistically analyze the data and display the results as a comprehensible Excel table. We then leveraged these libraries in other research to perform vector math on data spread across multiple access databases.