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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.

Fluorescence-guided surgery (FGS) and other interventions are rapidly evolving as a class of technologically driven interventional approaches in which many surgical specialties visualize fluorescent molecular tracers or biomarkers through associated cameras or oculars to guide clinical decisions on pathological lesion detection and excision/ablation. The technology has been commercialized for some specific applications, but also presents technical challenges unique to optical imaging that could confound the utility of some interventional procedures where real-time decisions must be made. Accordingly, the AAPM has initiated the publication of this Blue Paper of The Emerging Technology Working Group (TETAWG) and the creation of a Task Group from the Therapy Physics Committee within the Treatment Delivery Subcommittee. In describing the relevant issues, this document outlines the key parameters, stakeholders, impacts, and outcomes of clinical FGS technology and its applications. The presentation is not intended to be conclusive, but rather to inform the field of medical physics and stimulate the discussions needed in the field with respect to a seemingly low-risk imaging technology that has high potential for significant therapeutic impact. This AAPM Task Group is working toward consensus around guidelines and standards for advancing the field safely and effectively.

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

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.

Navigation with fluorescence guidance has emerged in the last decade as a promising strategy to improve the efficacy of oncologic surgery. To achieve routine clinical use, the onus is on the surgical community to objectively assess the value of this technique. This assessment may facilitate both Food and Drug Administration approval of new optical imaging agents and reimbursement for the imaging procedures. It is critical to characterize fluorescence-guided procedural benefits over existing practices and to elucidate both the costs and the safety risks. This report is the result of a meeting of the International Society of Image Guided Surgery (www.isigs.org) on February 6, 2015, in Miami, Florida, and reflects a consensus of the participants' opinions. Our objective was to critically evaluate the imaging platform technology and optical imaging agents and to make recommendations for successful clinical trial development of this highly promising approach in oncologic surgery.

The last decade has seen a large growth in fluorescence‐guided surgery (FGS) imaging and interventions. With the increasing number of clinical specialties implementing FGS, the range of systems with radically different physical designs, image processing approaches, and performance requirements is expanding. This variety of systems makes it nearly impossible to specify uniform performance goals, yet at the same time, utilization of different devices in new clinical procedures and trials indicates some need for common knowledge bases and a quality assessment paradigm to ensure that effective translation and use occurs. It is feasible to identify key fundamental image quality characteristics and corresponding objective test methods that should be determined such that there are consistent conventions across a variety of FGS devices. This report outlines test methods, tissue simulating phantoms and suggested guidelines, as well as personnel needs and professional knowledge bases that can be established. This report frames the issues with guidance and feedback from related societies and agencies having vested interest in the outcome, coming from an independent scientific group formed from academics and international federal agencies for the establishment of these professional guidelines. [ABSTRACT FROM AUTHOR]

Abstract Introduction Nationally, 25% to 50% of patients undergoing lumpectomy for local management of breast cancer require a secondary excision because of the persistence of residual tumor. Intraoperative assessment of specimen margins by frozen-section analysis is not widely adopted in breast-conserving surgery. Here, a new approach to wide-field optical imaging of breast pathology in situ was tested to determine whether the system could accurately discriminate cancer from benign tissues before routine pathological processing. Methods Spatial frequency domain imaging (SFDI) was used to quantify near-infrared (NIR) optical parameters at the surface of 47 lumpectomy tissue specimens. Spatial frequency and wavelength-dependent reflectance spectra were parameterized with matched simulations of light transport. Spectral images were co-registered to histopathology in adjacent, stained sections of the tissue, cut in the geometry imaged in situ. A supervised classifier and feature-selection algorithm were implemented to automate discrimination of breast pathologies and to rank the contribution of each parameter to a diagnosis. Results Spectral parameters distinguished all pathology subtypes with 82% accuracy and benign (fibrocystic disease, fibroadenoma) from malignant (DCIS, invasive cancer, and partially treated invasive cancer after neoadjuvant chemotherapy) pathologies with 88% accuracy, high specificity (93%), and reasonable sensitivity (79%). Although spectral absorption and scattering features were essential components of the discriminant classifier, scattering exhibited lower variance and contributed most to tissue-type separation. The scattering slope was sensitive to stromal and epithelial distributions measured with quantitative immunohistochemistry. Conclusions SFDI is a new quantitative imaging technique that renders a specific tissue-type diagnosis. Its combination of planar sampling and frequency-dependent depth sensing is clinically pragmatic and appropriate for breast surgical-margin assessment. This study is the first to apply SFDI to pathology discrimination in surgical breast tissues. It represents an important step toward imaging surgical specimens immediately ex vivo to reduce the high rate of secondary excisions associated with breast lumpectomy procedures.

IntroductionNationally, 25% to 50% of patients undergoing lumpectomy for local management of breast cancer require a secondary excision because of the persistence of residual tumor. Intraoperative assessment of specimen margins by frozen-section analysis is not widely adopted in breast-conserving surgery. Here, a new approach to wide-field optical imaging of breast pathology in situ was tested to determine whether the system could accurately discriminate cancer from benign tissues before routine pathological processing.MethodsSpatial frequency domain imaging (SFDI) was used to quantify near-infrared (NIR) optical parameters at the surface of 47 lumpectomy tissue specimens. Spatial frequency and wavelength-dependent reflectance spectra were parameterized with matched simulations of light transport. Spectral images were co-registered to histopathology in adjacent, stained sections of the tissue, cut in the geometry imaged in situ. A supervised classifier and feature-selection algorithm were implemented to automate discrimination of breast pathologies and to rank the contribution of each parameter to a diagnosis.ResultsSpectral parameters distinguished all pathology subtypes with 82% accuracy and benign (fibrocystic disease, fibroadenoma) from malignant (DCIS, invasive cancer, and partially treated invasive cancer after neoadjuvant chemotherapy) pathologies with 88% accuracy, high specificity (93%), and reasonable sensitivity (79%). Although spectral absorption and scattering features were essential components of the discriminant classifier, scattering exhibited lower variance and contributed most to tissue-type separation. The scattering slope was sensitive to stromal and epithelial distributions measured with quantitative immunohistochemistry.ConclusionsSFDI is a new quantitative imaging technique that renders a specific tissue-type diagnosis. Its combination of planar sampling and frequency-dependent depth sensing is clinically pragmatic and appropriate for breast surgical-margin assessment. This study is the first to apply SFDI to pathology discrimination in surgical breast tissues. It represents an important step toward imaging surgical specimens immediately ex vivo to reduce the high rate of secondary excisions associated with breast lumpectomy procedures.

The feasibility of spatial frequency domain imaging (SFDI) for breast surgical margin assessment was evaluated in tissue-simulating phantoms and in fully intact lumpectomy specimens at the time of surgery. Phantom data was evaluated according to contrast-detail resolution, quantitative accuracy and model-data goodness of fit, where optical parameters were estimated by minimizing the residual sum of squares between the measured modulation amplitude and its solutions, modeled according to diffusion and scaled-Monte Carlo simulations. In contrast-detail phantoms, a 1.25-mm-diameter surface inclusion was detectable for scattering contrast >28%; a fraction of this scattering contrast (7%) was detectable for a 10 mm surface inclusion and at least 33% scattering contrast was detected up to 1.5 mm below the phantom surface, a probing depth relevant to breast surgical margin assessment. Recovered hemoglobin concentrations were insensitive to changes in scattering, except for overestimation at visible wavelengths for total hemoglobin concentrations

Abstract.Multifrequency (0 to 0.3  mm−1), multiwavelength (633, 680, 720, 800, and 820 nm) spatial frequency domain imaging (SFDI) of 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) was used to recover absorption, scattering, and fluorescence properties of glioblastoma multiforme spheroids in tissue-simulating phantoms and in vivo in a mouse model. Three-dimensional tomographic reconstructions of the frequency-dependent remitted light localized the depths of the spheroids within 500 μm, and the total amount of PpIX in the reconstructed images was constant to within 30% when spheroid depth was varied. In vivo tumor-to-normal contrast was greater than ∼1.5 in reduced scattering coefficient for all wavelengths and was ∼1.3 for the tissue concentration of deoxyhemoglobin (ctHb). The study demonstrates the feasibility of SFDI for providing enhanced image guidance during surgical resection of brain tumors.

Spatial frequency domain imaging of 5-aminolevulinic acid induced protoporphyrin IX was used to recover absorption, scattering, and fluorescence properties of glioblastoma multiforme in tissue-simulating phantoms and in vivo in a mouse model. © 2012.

Diffuse optical imaging (DOI) is a noninvasive optical technique that employs near-infrared (NIR) light to quantitatively characterize the optical properties of thick tissues. Although NIR methods were first applied to breast transillumination (also called diaphanography) nearly 80 years ago, quantitative DOI methods employing time- or frequency-domain photon migration technologies have only recently been used for breast imaging (i.e., since the mid-1990s). In this review, the state of the art in DOI for breast cancer is outlined and a multi-institutional Network for Translational Research in Optical Imaging (NTROI) is described, which has been formed by the National Cancer Institute to advance diffuse optical spectroscopy and imaging (DOSI) for the purpose of improving breast cancer detection and clinical management. DOSI employs broadband technology both in near-infrared spectral and temporal signal domains in order to separate absorption from scattering and quantify uptake of multiple molecular probes based on absorption or fluorescence contrast. Additional dimensionality in the data is provided by integrating and co-registering the functional information of DOSI with x-ray mammography and magnetic resonance imaging (MRI), which provide structural information or vascular flow information, respectively. Factors affecting DOSI performance, such as intrinsic and extrinsic contrast mechanisms, quantitation of biochemical components, image formation/visualization, and multimodality co-registration are under investigation in the ongoing research NTROI sites. One of the goals is to develop standardized DOSI platforms that can be used as stand-alone devices or in conjunction with MRI, mammography, or ultrasound. This broad-based, multidisciplinary effort is expected to provide new insight regarding the origins of breast disease and practical approaches for addressing several key challenges in breast cancer, including: Detecting disease in mammographically dense tissue, distinguishing between malignant and benign lesions, and understanding the impact of neoadjuvant chemotherapies.

Background: Accuracy of electrode placement for deep brain stimulation (DBS) is critical to achieving desired surgical outcomes and impacts the efficacy of treating neurodegenerative diseases. Intraoperative brain shift degrades the accuracy of surgical navigation based on preoperative images. Purpose: We extended a model‐based image updating scheme to address intraoperative brain shift in DBS surgery and improved its accuracy in deep brain. Methods: We evaluated 10 patients, retrospectively, who underwent bilateral DBS surgery and classified them into groups of large and small deformation based on a 2 mm subsurface movement threshold and brain shift index of 5%. In each case, sparse brain deformation data were used to estimate whole brain displacements and deform preoperative CT (preCT) to generate updated CT (uCT). Accuracy of uCT was assessed using target registration errors (TREs) at the Anterior Commissure (AC), Posterior Commissure (PC), and four calcification points in the sub‐ventricular area by comparing their locations in uCT with their ground truth counterparts in postoperative CT (postCT). Results: In the large deformation group, TREs were reduced from 2.5 mm in preCT to 1.2 mm in uCT (53% compensation); in the small deformation group, errors were reduced from 1.25 to 0.74 mm (41%). Average reduction of TREs at AC, PC and pineal gland were significant, statistically (p ⩽ 0.01). Conclusions: With more rigorous validation of model results, this study confirms the feasibility of improving the accuracy of model‐based image updating in compensating for intraoperative brain shift during DBS procedures by assimilating deep brain sparse data. [ABSTRACT FROM AUTHOR]