Diffuse optical spectroscopic imaging reveals distinct early breast tumor hemodynamic responses to metronomic and maximum tolerated dose regimens.

BACKGROUND:Breast cancer patients with early-stage disease are increasingly administered neoadjuvant chemotherapy (NAC) to downstage their tumors prior to surgery. In this setting, approximately 31% of patients fail to respond to therapy. This demonstrates the need for techniques capable of providing personalized feedback about treatment response at the earliest stages of therapy to identify patients likely to benefit from changing treatment. Diffuse optical spectroscopic imaging (DOSI) has emerged as a promising functional imaging technique for NAC monitoring. DOSI uses non-ionizing near-infrared light to provide non-invasive measures of absolute concentrations of tissue chromophores such as oxyhemoglobin. In 2011, we reported a new DOSI prognostic marker, oxyhemoglobin flare: a transient increase in oxyhemoglobin capable of discriminating NAC responders within the first day of treatment. In this follow-up study, DOSI was used to confirm the presence of the flare as well as to investigate whether DOSI markers of NAC response are regimen dependent. METHODS:This dual-center study examined 54 breast tumors receiving NAC measured with DOSI before therapy and the first week following chemotherapy administration. Patients were treated with either a standard of care maximum tolerated dose (MTD) regimen or an investigational metronomic (MET) regimen. Changes in tumor chromophores were tracked throughout the first week and compared to pathologic response and treatment regimen at specific days utilizing generalized estimating equations (GEE). RESULTS:Within patients receiving MTD therapy, the oxyhemoglobin flare was confirmed as a prognostic DOSI marker for response appearing as soon as day 1 with post hoc GEE analysis demonstrating a difference of 48.77% between responders and non-responders (p < 0.0001). Flare was not observed in patients receiving MET therapy. Within all responding patients, the specific treatment was a significant predictor of day 1 changes in oxyhemoglobin, showing a difference of 39.45% (p = 0.0010) between patients receiving MTD and MET regimens. CONCLUSIONS:DOSI optical biomarkers are differentially sensitive to MTD and MET regimens at early timepoints suggesting the specific treatment regimen should be considered in future DOSI studies. Additionally, DOSI may help to identify regimen-specific responses in a more personalized manner, potentially providing critical feedback necessary to implement adaptive changes to the treatment strategy

Tissue Oxygen Saturation Predicts Response to Breast Cancer Neoadjuvant Chemotherapy within 10 Days of Treatment

Ideally, neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3- to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (StO2) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC  =  0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue StO2 to surrounding tissue StO2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer

Performance Assessment of Diffuse Optical Spectroscopic Imaging Instruments in a 2-Year Multicenter Breast Cancer Trial

We present a framework for characterizing the performance of an experimental imaging technology, diffuse optical spectroscopic imaging (DOSI), in a 2-year multicenter American College of Radiology Imaging Network (ACRIN) breast cancer study (ACRIN-6691). DOSI instruments combine broadband frequency-domain photon migration with time-independent near-infrared (650 to 1000 nm) spectroscopy to measure tissue absorption and reduced scattering spectra and tissue hemoglobin, water, and lipid composition. The goal of ACRIN-6691 was to test the effectiveness of optically derived imaging endpoints in predicting the final pathologic response of neoadjuvant chemotherapy (NAC). Sixty patients were enrolled over a 2-year period at participating sites and received multiple DOSI scans prior to and during 3- to 6-month NAC. The impact of three sources of error on accuracy and precision, including different operators, instruments, and calibration standards, was evaluated using a broadband reflectance standard and two different solid tissue-simulating optical phantoms. Instruments showed \u3c 0.0010 mm−1 (10.3%) and 0.06 mm−1 (4.7%) deviation in broadband absorption and reduced scattering, respectively, over the 2-year duration of ACRIN-6691. These variations establish a useful performance criterion for assessing instrument stability. The proposed procedures and tests are not limited to DOSI; rather, they are intended to provide methods to characterize performance of any instrument used in translational optical imaging

The NEWGEN European Union Research Project for a New Generation of HVDC Cable Systems

This paper illustrates the European Union NEWGEN research project, entitled 'New Generation of HVDC Insulation Materials, Cables and Systems', with 10 partners over 5 EU Countries. The objective of NEWGEN is to develop and proof new insulation materials, manufacturing solutions, online condition monitoring, and comprehensive life and reliability modelling tools for next-generation of extruded HVDC cables and cable systems, thus fostering the reliability and resilience of the European HVAC/-DC transmission grid.</p

Breast cancer differential diagnosis using diffuse optical spectroscopic imaging and regression with z-score normalized data.

Current imaging paradigms for differential diagnosis of suspicious breast lesions suffer from high false positive rates that force patients to undergo unnecessary biopsies. Diffuse optical spectroscopic imaging (DOSI) noninvasively probes functional hemodynamic and compositional parameters in deep tissue and has been shown to be sensitive to contrast between normal and malignant tissues. DOSI methods are under investigation as an adjunct to mammography and ultrasound that could reduce false positive rates and unnecessary biopsies, particularly in radiographically dense breasts. We performed a retrospective analysis of 212 subjects with suspicious breast lesions who underwent DOSI imaging. Physiological tissue parameters were z-score normalized to the patient's contralateral breast tissue and input to univariate logistic regression models to discriminate between malignant tumors and the surrounding normal tissue. The models were then used to differentiate malignant lesions from benign lesions. Models incorporating several individual hemodynamic parameters were able to accurately distinguish malignant tumors from both the surrounding background tissue and benign lesions with area under the curve (AUC) ≥0.85. Z-score normalization improved the discriminatory ability and calibration of these predictive models relative to unnormalized or ratio-normalized data. Findings from a large subject population study show how DOSI data normalization that accounts for normal tissue heterogeneity and quantitative statistical regression approaches can be combined to improve the ability of DOSI to diagnose malignant lesions. This improved diagnostic accuracy, combined with the modality's inherent logistical advantages of portability, low cost, and nonionizing radiation, could position DOSI as an effective adjunct modality that could be used to reduce the number of unnecessary invasive biopsies

Breast cancer differential diagnosis using diffuse optical spectroscopic imaging and regression with z-score normalized data.

SignificanceCurrent imaging paradigms for differential diagnosis of suspicious breast lesions suffer from high false positive rates that force patients to undergo unnecessary biopsies. Diffuse optical spectroscopic imaging (DOSI) noninvasively probes functional hemodynamic and compositional parameters in deep tissue and has been shown to be sensitive to contrast between normal and malignant tissues.AimDOSI methods are under investigation as an adjunct to mammography and ultrasound that could reduce false positive rates and unnecessary biopsies, particularly in radiographically dense breasts.MethodsWe performed a retrospective analysis of 212 subjects with suspicious breast lesions who underwent DOSI imaging. Physiological tissue parameters were z-score normalized to the patient's contralateral breast tissue and input to univariate logistic regression models to discriminate between malignant tumors and the surrounding normal tissue. The models were then used to differentiate malignant lesions from benign lesions.ResultsModels incorporating several individual hemodynamic parameters were able to accurately distinguish malignant tumors from both the surrounding background tissue and benign lesions with area under the curve (AUC) ≥0.85. Z-score normalization improved the discriminatory ability and calibration of these predictive models relative to unnormalized or ratio-normalized data.ConclusionsFindings from a large subject population study show how DOSI data normalization that accounts for normal tissue heterogeneity and quantitative statistical regression approaches can be combined to improve the ability of DOSI to diagnose malignant lesions. This improved diagnostic accuracy, combined with the modality's inherent logistical advantages of portability, low cost, and nonionizing radiation, could position DOSI as an effective adjunct modality that could be used to reduce the number of unnecessary invasive biopsies

Baseline tumor oxygen saturation correlates with a pathologic complete response in breast cancer patients undergoing neoadjuvant chemotherapy.

Tissue hemoglobin oxygen saturation (i.e., oxygenation) is a functional imaging endpoint that can reveal variations in tissue hypoxia, which may be predictive of pathologic response in subjects undergoing neoadjuvant chemotherapy. In this study, we used diffuse optical spectroscopic imaging (DOSI) to measure concentrations of oxyhemoglobin (ctO(2)Hb), deoxy-hemoglobin (ctHHb), total Hb (ctTHb = ctO(2)Hb + ctHHb), and oxygen saturation (stO(2) = ctO(2)Hb/ctTHb) in tumor and contralateral normal tissue from 41 patients with locally advanced primary breast cancer. Measurements were acquired before the start of neoadjuvant chemotherapy. Optically derived parameters were analyzed separately and in combination with clinical biomarkers to evaluate correlations with pathologic response. Discriminant analysis was conducted to determine the ability of optical and clinical biomarkers to classify subjects into response groups. Twelve (28.6%) of 42 tumors achieved pathologic complete response (pCR) and 30 (71.4%) were non-pCR. Tumor measurements in pCR subjects had higher stO(2) levels (median 77.8%) than those in non-pCR individuals (median 72.3%, P = 0.01). There were no significant differences in baseline ctO(2)Hb, ctHHb, and ctTHb between response groups. An optimal tumor oxygenation threshold of stO(2) = 76.7% was determined for pCR versus non-pCR (sensitivity = 75.0%, specificity = 73.3%). Multivariate discriminant analysis combining estrogen receptor staining and stO(2) further improved the classification of pCR versus non-pCR (sensitivity = 100%, specificity = 85.7%). These results show that elevated baseline tumor stO(2) are correlated with a pCR. Noninvasive DOSI scans combined with histopathology subtyping may aid in stratification of individual patients with breast cancer before neoadjuvant chemotherapy