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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.

BackgroundBreast 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.MethodsThis 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).ResultsWithin 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

Relatively few imaging and sensing technologies are employed to study human lactation physiology. In particular, human mammary development during pregnancy as well as mammary involution after lactation have been poorly described, despite their importance for breast cancer diagnosis and treatment during these phases. Our case study shows the potential of diffuse optical spectroscopic imaging (DOSI) to uniquely study the spatiotemporal changes in mammary tissue composition during the involution of the lactating breast toward its pre-pregnant state. At nine time intervals over a period of eight months after the cessation of breastfeeding, we reconstructed 2-D maps of mammary water content, lipid content, total hemoglobin (THb) concentration, oxygen saturation (StO2), and tissue optical scattering. Mammary lipid content in the nonareolar region showed a significant relative increase of 59%, whereas water content and THb concentration showed a significant relative decrease of 50% and 48%, respectively. Significant changes were also found in StO2 and tissue optical scattering. Our findings are consistent with the gradual replacement of fibroglandular tissue by adipose tissue and vascular regression during mammary involution. Moreover, our data provide unique insight into the dynamics of breast tissue composition and demonstrate the effectiveness of DOSI as a technique to study human lactation physiology.

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.

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

We measure tissue blood flow markers in breast tumors during neoadjuvant chemotherapy and investigate their correlation to pathologic complete response in a pilot longitudinal patient study (n  =  4). Tumor blood flow is quantified optically by diffuse correlation spectroscopy (DCS), and tissue optical properties, blood oxygen saturation, and total hemoglobin concentration are derived from concurrent diffuse optical spectroscopic imaging (DOSI). The study represents the first longitudinal DCS measurement of neoadjuvant chemotherapy in humans over the entire course of treatment; it therefore offers a first correlation between DCS flow indices and pathologic complete response. The use of absolute optical properties measured by DOSI facilitates significant improvement of DCS blood flow calculation, which typically assumes optical properties based on literature values. Additionally, the combination of the DCS blood flow index and the tissue oxygen saturation from DOSI permits investigation of tissue oxygen metabolism. Pilot results from four patients suggest that lower blood flow in the lesion-bearing breast is correlated with pathologic complete response. Both absolute lesion blood flow and lesion flow relative to the contralateral breast exhibit potential for characterization of pathological response. This initial demonstration of the combined optical approach for chemotherapy monitoring provides incentive for more comprehensive studies in the future and can help power those investigations.

Diffuse optical spectroscopic imaging (DOSI) and diffuse correlation spectroscopy (DCS) are model-based near-infrared (NIR) methods that measure tissue optical properties (broadband absorption, ? a , and reduced scattering, ? s ? ) and blood flow (blood flow index, BFI), respectively. DOSI-derived ? a values are used to determine composition by calculating the tissue concentration of oxy- and deoxyhemoglobin ( HbO 2 , HbR), water, and lipid. We developed and evaluated a combined, coregistered DOSI/DCS handheld probe for mapping and imaging these parameters. We show that uncertainties of 0.3 ?? mm ? 1 (37%) in ? s ? and 0.003 ?? mm ? 1 (33%) in ? a lead to ? 53 % and 9% errors in BFI, respectively. DOSI/DCS imaging of a solid tissue-simulating flow phantom and

The prospective multicenter ACRIN 6691 trial was designed to evaluate whether changes from baseline to mid-therapy in a diffuse optical spectroscopic imaging (DOSI)-derived imaging endpoint, the tissue optical index (TOI), predict pathologic complete response (pCR) in women undergoing breast cancer neoadjuvant chemotherapy (NAC). DOSI instruments were constructed at the University of California, Irvine (Irvine, CA), and delivered to six institutions where 60 subjects with newly diagnosed breast tumors (at least 2 cm in the longest dimension) were enrolled over a 2-year period. Bedside DOSI images of the tissue concentrations of deoxy-hemoglobin (ctHHb), oxy-hemoglobin (ctHbO2), water (ctH2O), lipid, and TOI (ctHHb × ctH2O/lipid) were acquired on both breasts up to four times during NAC treatment: baseline, 1-week, mid-point, and completion. Of the 34 subjects (mean age 48.4 ± 10.7 years) with complete, evaluable data from both normal and tumor-containing breast, 10 (29%) achieved pCR as determined by central pathology review. The percent change in tumor-to-normal TOI ratio (%TOITN) from baseline to mid-therapy ranged from -82% to 321%, with a median of -36%. Using pCR as the reference standard and ROC curve methodology, %TOITN AUC was 0.60 (95% CI, 0.39-0.81). In the cohort of 17 patients with baseline tumor oxygen saturation (%StO2) greater than the 77% population median, %TOITN AUC improved to 0.83 (95% CI, 0.63-1.00). We conclude that the combination of baseline functional properties and dynamic optical response shows promise for clinical outcome prediction. Cancer Res; 76(20); 5933-44. ©2016 AACR.

Changes in subcutaneous adipose tissue (AT) structure and metabolism have been shown to correlate with the development of obesity and related metabolic disorders. Measurements of AT physiology could provide new insight into metabolic disease progression and response to therapy. An emerging functional imaging technology, diffuse optical spectroscopic imaging (DOSI), was used to obtain quantitative measures of near infrared (NIR) AT optical and physiological properties.Ten overweight or obese adults were assessed during 3 months on calorie-restricted diets. DOSI-derived tissue concentrations of hemoglobin, water and lipid and the wavelength-dependent scattering amplitude (A) and slope (b) obtained from 30 abdominal locations and three time points (T0, T6, T12) were calculated and analyzed using linear mixed-effects models and were also used to form 3D surface images.Subjects lost a mean of 11.7±3.4% of starting weight, while significant changes in A (+0.23±0.04 mm(-1), adj. P

Young patients with dense breasts have a relatively low-positive biopsy rate for breast cancer (∼1 in 7). South Korean women have higher breast density than Westerners. We investigated the benefit of using a functional and metabolic imaging technique, diffuse optical spectroscopic imaging (DOSI), to help the standard of care imaging tools to distinguish benign from malignant lesions in premenopausal Korean women. DOSI uses near-infrared light to measure breast tissue composition by quantifying tissue concentrations of water (ctH2O), bulk lipid (ctLipid), deoxygenated (ctHHb), and oxygenated (ctHbO2) hemoglobin. DOSI spectral signatures specific to abnormal tissue and absent in healthy tissue were also used to form a malignancy index. This study included 19 premenopausal subjects (average age 41±9), corresponding to 11 benign and 10 malignant lesions. Elevated lesion to normal ratio of ctH2O, ctHHb, ctHbO2, total hemoglobin (THb=ctHHb+ctHbO2), and tissue optical index (ctHHb×ctH2O/ctLipid) were observed in the malignant lesions compared to the benign lesions (p90% sensitivity and specificity. Malignant lesions showed significantly higher metabolism and perfusion than benign lesions. DOSI spectral features showed high discriminatory power for distinguishing malignant and benign lesions in dense breasts of the Korean population.

Abstract: Background: In addition to being a strong risk factor for breast cancer, data from recent studies suggests that breast density changes correlate with response to preventative or adjuvant tamoxifen treatment for breast cancer. Breast density may be a surrogate biomarker for survival and indication of the need for additional treatments such as radiotherapy. However, quantitative methods to assess breast density in the clinic are limited. In this study, we assess how Diffuse Optical Spectroscopic Imaging (DOSI) may be used to evaluate and understand changes in breast density in patients undergoing neoadjuvant chemotherapy. Methods: DOSI was used to measure hemodynamic and metabolic information from the contralateral normal breast of 28 breast cancer patients undergoing neoadjuvant chemotherapy. DOSI uses near-infrared light to determine absolute tissue molar concentrations of oxyhemoglobin (ctO2Hb), deoxyhemoglobin (ctHHb), water, and lipid content without requirement of an exogenous contrast agent. DOSI measurements were compared to 3.0T MRI measured fibroglandular density before and during therapy. Results: Water (r = 0.843; P

Abstract Introduction Radiographic density adversely affects the performance of X-ray mammography and can be particularly problematic in younger and high-risk women. Because of this limitation, there is significant ongoing effort to develop alternative cancer screening and detection strategies for this population. This pilot study evaluates the potential of Diffuse Optical Spectroscopic Imaging (DOSI) to image known tumors in dense breast tissue. Methods We performed a retrospective analysis on 24 radiographically dense breast cancer subjects measured with DOSI over a four-year period (Breast Imaging Reporting and Data System - BI-RADS, category 3 and 4, average age = 39 ± 7.6, average maximum size 31 ± 17 mm). Two previously-described DOSI contrast functions, the tissue optical index (TOI) and the specific tumor component (STC), which are based upon the concentrations and spectral signatures of hemoglobin, water and lipids, respectively, were used to form 2D optical images of breast tumors. Results Using TOI and STC, 21 out of 24 breast tumors were found to be statistically different from the surrounding highly vascularized dense tissue and to be distinguishable from the areolar region. For these patients, the tumor to normal contrast was 2.6 ± 1.2 (range 1.3 to 5.5) and 10.0 ± 7.5 (range 3.3 to 26.4) for TOI and STC, respectively. STC images were particularly useful in eliminating metabolic background from the retroareolar region which led to identification of two out of four retroareolar tumors. Conclusions Using both the abundance and the disposition of the tissue chromophores recovered from the DOSI measurements, we were able to observe tumor contrast relative to dense breast tissue. These preliminary results suggest that DOSI spectral characterization strategies may provide new information content that could help imaging breast tumors in radiographically dense tissue and in particular in the areolar complex.

Instrument equivalence and quality control are critical elements of multi-center clinical trials. We currently have five identical Diffuse Optical Spectroscopic Imaging (DOSI) instruments enrolled in the American College of Radiology Imaging Network (ACRIN, #6691) trial located at five academic clinical research sites in the US. The goal of the study is to predict the response of breast tumors to neoadjuvant chemotherapy in 60 patients. In order to reliably compare DOSI measurements across different instruments, operators and sites, we must be confident that the data quality is comparable. We require objective and reliable methods for identifying, correcting, and rejecting low quality data. To achieve this goal, we developed and tested an automated quality control algorithm that rejects data points below the instrument noise floor, improves tissue optical property recovery, and outputs a detailed data quality report. Using a new protocol for obtaining dark-noise data, we applied the algorithm to ACRIN patient data and successfully improved the quality of recovered physiological data in some cases. © 2013 Copyright SPIE.

Instrument equivalence and quality control are critical elements of multi-center clinical trials. We currently have five identical Diffuse Optical Spectroscopic Imaging (DOSI) instruments enrolled in the American College of Radiology Imaging Network (ACRIN, #6691) trial located at five academic clinical research sites in the US. The goal of the study is to predict the response of breast tumors to neoadjuvant chemotherapy in 60 patients. In order to reliably compare DOSI measurements across different instruments, operators and sites, we must be confident that the data quality is comparable. We require objective and reliable methods for identifying, correcting, and rejecting low quality data. To achieve this goal, we developed and tested an automated quality control algorithm that rejects data points below the instrument noise floor, improves tissue optical property recovery, and outputs a detailed data quality report. Using a new protocol for obtaining dark-noise data, we applied the algorithm to ACRIN patient data and successfully improved the quality of recovered physiological data in some cases. © 2013 Copyright SPIE.

IntroductionIn addition to being a risk factor for breast cancer, breast density has beenhypothesized to be a surrogate biomarker for predicting response toendocrine-based chemotherapies. The purpose of this study was to evaluate whethera noninvasive bedside scanner based on diffuse optical spectroscopic imaging(DOSI) provides quantitative metrics to measure and track changes in breast tissuecomposition and density. To access a broad range of densities in a limited patientpopulation, we performed optical measurements on the contralateral normal breastof patients before and during neoadjuvant chemotherapy (NAC). In this work, DOSIparameters, including tissue hemoglobin, water, and lipid concentrations, wereobtained and correlated with magnetic resonance imaging (MRI)-measuredfibroglandular tissue density. We evaluated how DOSI could be used to assessbreast density while gaining new insight into the impact of chemotherapy on breasttissue.MethodsThis was a retrospective study of 28 volunteers undergoing NAC treatment forbreast cancer. Both 3.0-T MRI and broadband DOSI (650 to 1,000 nm) were obtainedfrom the contralateral normal breast before and during NAC. Longitudinal DOSImeasurements were used to calculate breast tissue concentrations of oxygenated anddeoxygenated hemoglobin, water, and lipid. These values were compared withMRI-measured fibroglandular density before and during therapy.ResultsWater (r = 0.843; P < 0.001), deoxyhemoglobin (r =0.785; P = 0.003), and lipid (r = -0.707; P = 0.010)concentration measured with DOSI correlated strongly with MRI-measured densitybefore therapy. Mean DOSI parameters differed significantly between pre- andpostmenopausal subjects at baseline (water, P < 0.001;deoxyhemoglobin, P = 0.024; lipid, P = 0.006). During NACtreatment measured at about 90 days, significant reductions were observed inoxyhemoglobin for pre- (-20.0%; 95% confidence interval (CI), -32.7 to -7.4) andpostmenopausal subjects (-20.1%; 95% CI, -31.4 to -8.8), and water concentrationfor premenopausal subjects (-11.9%; 95% CI, -17.1 to -6.7) compared with baseline.Lipid increased slightly in premenopausal subjects (3.8%; 95% CI, 1.1 to 6.5), andwater increased slightly in postmenopausal subjects (4.4%; 95% CI, 0.1 to 8.6).Percentage change in water at the end of therapy compared with baseline correlatedstrongly with percentage change in MRI-measured density (r = 0.864; P= 0.012).ConclusionsDOSI functional measurements correlate with MRI fibroglandular density, bothbefore therapy and during NAC. Although from a limited patient dataset, theseresults suggest that DOSI may provide new functional indices of density based onhemoglobin and water that could be used at the bedside to assess response totherapy and evaluate disease risk.

Abstract Introduction In addition to being a risk factor for breast cancer, breast density has been hypothesized to be a surrogate biomarker for predicting response to endocrine-based chemotherapies. The purpose of this study was to evaluate whether a noninvasive bedside scanner based on diffuse optical spectroscopic imaging (DOSI) provides quantitative metrics to measure and track changes in breast tissue composition and density. To access a broad range of densities in a limited patient population, we performed optical measurements on the contralateral normal breast of patients before and during neoadjuvant chemotherapy (NAC). In this work, DOSI parameters, including tissue hemoglobin, water, and lipid concentrations, were obtained and correlated with magnetic resonance imaging (MRI)-measured fibroglandular tissue density. We evaluated how DOSI could be used to assess breast density while gaining new insight into the impact of chemotherapy on breast tissue. Methods This was a retrospective study of 28 volunteers undergoing NAC treatment for breast cancer. Both 3.0-T MRI and broadband DOSI (650 to 1,000 nm) were obtained from the contralateral normal breast before and during NAC. Longitudinal DOSI measurements were used to calculate breast tissue concentrations of oxygenated and deoxygenated hemoglobin, water, and lipid. These values were compared with MRI-measured fibroglandular density before and during therapy. Results Water (r = 0.843; P < 0.001), deoxyhemoglobin (r = 0.785; P = 0.003), and lipid (r = -0.707; P = 0.010) concentration measured with DOSI correlated strongly with MRI-measured density before therapy. Mean DOSI parameters differed significantly between pre- and postmenopausal subjects at baseline (water, P < 0.001; deoxyhemoglobin, P = 0.024; lipid, P = 0.006). During NAC treatment measured at about 90 days, significant reductions were observed in oxyhemoglobin for pre- (-20.0%; 95% confidence interval (CI), -32.7 to -7.4) and postmenopausal subjects (-20.1%; 95% CI, -31.4 to -8.8), and water concentration for premenopausal subjects (-11.9%; 95% CI, -17.1 to -6.7) compared with baseline. Lipid increased slightly in premenopausal subjects (3.8%; 95% CI, 1.1 to 6.5), and water increased slightly in postmenopausal subjects (4.4%; 95% CI, 0.1 to 8.6). Percentage change in water at the end of therapy compared with baseline correlated strongly with percentage change in MRI-measured density (r = 0.864; P = 0.012). Conclusions DOSI functional measurements correlate with MRI fibroglandular density, both before therapy and during NAC. Although from a limited patient dataset, these results suggest that DOSI may provide new functional indices of density based on hemoglobin and water that could be used at the bedside to assess response to therapy and evaluate disease risk.

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.

Tissue simulating phantoms are an important part of instrumentation validation, standardization/training and clinical translation. Properly used, phantoms form the backbone of sound quality control procedures. We describe the development and testing of a series of optically turbid phantoms used in a multi-center American College of Radiology Imaging Network (ACRIN) clinical trial of Diffuse Optical Spectroscopic Imaging (DOSI). The ACRIN trial is designed to measure the response of breast tumors to neoadjuvant chemotherapy. Phantom measurements are used to determine absolute instrument response functions during each measurement session and assess both long and short-term operator and instrument reliability.

We previously developed a self-referencing differential spectroscopic (SRDS) method to detect lesions by identifying a spectroscopic biomarker of breast cancer, i.e., the specific tumor component (STC). The SRDS method is based on the assumption of the exclusive presence of this spectroscopic biomaker in malignant disease. Although clinical results using this method have already been published, the dependence of the STC spectra on the choice of reference tissue has not yet been addressed. In this study, we explore the impact of the selection of the reference region size and location on the STC spectrum in 10 subjects with malignant breast tumors. Referencing from both contralateral and ipsilateral sides was performed. Regardless of the referencing, we are able to obtain consistent high contrast images of malignant lesions using the STC with less than 13% deviation. These results suggest that the STC measurements are independent of any type, location, and amount of normal breast tissue used for referencing. This confirms the initial assumption of the SRDS analysis, that there are specific tumor components in cancer that do not exist in normal tissue. This also indicates that bilateral measurements are not required for lesion identification using the STC method.

We describe an algorithm to calculate an index that characterizes spatial differences in broadband near-infrared [(NIR), 650-1000 nm] absorption spectra of tumor-containing breast tissue. Patient-specific tumor spatial heterogeneities are visualized through a heterogeneity spectrum function (HS). HS is a biomarker that can be attributed to different molecular distributions within the tumor. To classify lesion heterogeneities, we built a heterogeneity index (HI) derived from the HS by weighing the HS in specific NIR absorption bands. It is shown that neoadjuvant chemotherapy (NAC) response is potentially related to the tumor heterogeneity. Therefore, we correlate the heterogeneity index obtained prior to treatment with the final response to NAC. From a pilot study of 15 cancer patients treated with NAC, pathological complete responders (pCR) were separated from non-pCR according to their HI (-44 ± 12 and 43 ± 17, p = 3 × 10(-8), respectively). We conclude that the HS function is a biomarker that can be used to visualize spatial heterogeneities in lesions, and the baseline HI prior to therapy correlates with chemotherapy pathological response.