Photoacoustic Imaging in Detecting Ovarian or Fallopian Tube Cancer

Transvaginal Ultrasound and Photoacoustic Imaging of the Ovaries and the Fallopian Tubes: A Clinical Feasibility Study

This pilot clinical trial studies how well photoacoustic imaging works in detecting ovarian or fallopian tube cancer. Photoacoustic imaging is an imaging method that uses lasers to light up tissue, and then converts the light information into ultrasound images. Photoacoustic imaging can provide images of the structure of tissues, as well as their function and the levels of molecules, such as the flow of blood in blood vessels and the level of oxygen in the blood. Photoacoustic imaging may help doctors determine whether a mass is benign (non-cancerous) or cancerous based on the molecular differences between cancer and normal tissue. It may be more accurate and less expensive than other imaging methods, and does not expose patients to radiation.

PRIMARY OBJECTIVES: I. To assess the performance of photoacoustic imaging (PAI) in detection of ovarian cancer in a clinical setting and to help improve the design of the next generation hand held PAI probe. SECONDARY OBJECTIVES: I. To evaluate vasculature and oxygen saturation in lesions based on PAI-measurements. OUTLINE: Patients undergo PAI over 15-30 minutes prior to the ovarian excision.

Descriptive statistics (proportions, means) will be used to summarize depth of lesion. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Descriptive statistics (proportions, means) will be used to summarize lesion total hemoglobin. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Descriptive statistics (proportions, means) will be used to summarize PAI signal intensity. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Descriptive statistics (proportions, means) will be used to summarize percent SO2 in ROI. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Descriptive statistics (proportions, means) will be used to summarize size of lesion. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Descriptive statistics (proportions, means) will be used to summarize time span for PAI examination. The distribution of signal intensity on PAI, total hemoglobin concentration (HbT), and oxygen saturation (SO2) will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the receiver operating characteristic (ROC) curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Visibility/quality rating of PAI-image as measured by 5-level scale: not visible, barely visible, fair (or moderately) visible, visible, and clearly visible

Descriptive statistics (proportions, means) will be used to summarize visibility/quality rating of PAI. The distribution of signal intensity on PAI, HbT, and SO2 will be summarized separately by lesion depth, size and status using means and will be graphed as boxplots with a P value of the corresponding Kendall correlation to aid in interpretation. The area under the ROC curve will be computed along with a 95% confidence interval based on the .632 bootstrap estimated error rate.

Inclusion Criteria: Patients must be undergoing ovarian resection Ability to understand and the willingness to sign a written informed consent document Exclusion Criteria: Patients who have had primary surgical excision Pregnant or lactating women