Linear signal combination T2 spectroscopy

A technique is presented for performing T2 spectroscopy in magnetic resonance imaging (MRI). It is based on a weighted linear combination of T2 decay data. The data is combined in a manner that acts like a filter on the T2 spectrum. The choice of weighting coefficients determines the filter specifications (e.g. passband/stopband locations, stopband suppression factors). To perform spectroscopy, a series of filters are designed with narrow passbands centered about consecutive regions of the T2 spectrum. This provides an estimate of every region of the spectrum. Taken together, an initial estimate of the full T2 spectrum is thus obtained. However, the filtering process causes a distortion of the estimate relative to the true spectrum. To reduce this distortion, deconvolution is performed. The characteristics of the technique are first evaluated through simulation. The technique is then applied to experimental MRI data to demonstrate practical feasibility. T2 spectroscopy falls into a class of problems requiring inverse transformation with a set of exponential basis functions (i.e. the Laplace Transform). It is demonstrated how the present technique may be applied to problems involving non-exponential basis functions as well.     

Breast cancer diagnostics by Raman spectroscopy

This paper presents new results for the normal, malignant and benign tissues by Raman spectroscopy. To the best of our knowledge, this is one of the most statistically reliable research (321 spectra from 44 patients) on Raman spectroscopy-based diagnosis of breast cancers among the world's women population. The paper demonstrates that Raman spectroscopy is a powerful medical diagnostic tool with the key advantage in breast cancer research.     

Transcutaneous in vivo Raman spectroscopy of breast tumors and pretumors

Breast cancer is the most common cancer amongst women worldwide. Early detection of this cancer results in better prognosis. Owing to the disadvantages of currently available screening tools for early detection of this cancer, rapid and sensitive alternatives such as optical spectroscopic techniques are being extensively explored. Detection of premalignant lesions using these techniques has been reported. However, premalignant lesions are risk indicators and may not be true predictors of tumor development. Therefore, the current study aims at correlation between spectral changes and tumor appearance. In this context, transcutaneous in vivo spectra were acquired from same carcinogen‐induced rats immediately before carcinogen treatment, 3, 8–10, and 12–14 weeks after carcinogen treatment and from frank tumors. These were analyzed using multivariate statistical tools principal component analysis and principal component linear discriminant analysis. Further, a complex test data set consisting of spectra from rats of varying ages, tumor appearance times, and tumor induction protocols was used to test the feasibility of correctly identifying controls and pretumors using Raman spectroscopy. Results suggest feasibility of distinguishing pretumor spectra from controls. Taking into consideration the heterogeneity of afflicted breast, rat‐wise analysis was performed wherein a rat was declared ‘will develop tumor’, even if one spectrum was found abnormal. Using this criterion, in vivo Raman spectroscopy could predict tumor appearance with 82% sensitivity and 95% specificity. Prospectively, combined with emerging technologies like deep Raman spectroscopy and fiber‐probe‐based whole sample imaging, Raman spectroscopy may prove as an invaluable adjunct to currently available breast cancer screening tools. Copyright © 2015 John Wiley & Sons, Ltd.     

High-resolution near-infrared tomographic imaging simulations of the rat cranium by use of a priori magnetic resonance imaging structural information

Near-infrared (NIR) optical image reconstruction that incorporates magnetic resonance image (MRI) structural data was tested in a series of simulated reconstructions. NIR diffuse tomography generally suffers from comparatively low spatial resolution. By using the fine structural detail that is available with MRI, combined with the functional information of NIR spectroscopy, it is possible to design a new image-reconstruction methodology that provides high-resolution images that are correlated with hemoglobin concentration and oxygen saturation. To test this concept a MRI spin-echo image of a rat cranium was used to obtain an outline of the bone, brain, and muscle tissues, and this information was incorporated into an iterative-based diffuse tomography reconstruction. These simulations represent what is believed to be the first attempt at evaluating a spatially constrained iterative-reconstruction MRI-NIR imaging modality for brain tissue.     

Raman spectroscopic analysis differentiates between breast cancer cell lines

Breast cancer incident rates are increasing in women worldwide with the highest incidence rates reported in developing countries. Major breast cancer screening approaches like mammography, ultrasound, clinical breast examination (CBE) and magnetic resonance imaging (MRI) are currently used but have their own limitations. Optical spectroscopy has attained great attention from biomedical researchers in recent years due to its non‐invasive and non‐destructive detection approach. Chemometrics is one of the powerful tools used in spectroscopic research to enhance its sensitivity. Raman spectroscopy, a vibrational spectroscopic approach, has been used to explore the chemical fingerprints of different biological tissues including normal and malignant types. This approach was used to characterize and differentiate two breast cancer and one normal breast cell lines (MDA‐MB‐436, MCF‐7 and MCF‐10A) using dispersive Raman spectroscopy. Raman spectra of the cell lines have revealed that basic differences in the concentration of biochemical compounds such as lipids, nucleic acids and protein Raman peaks were found to differ in intensity, and principal component analysis (PCA) was able to identify variations that lead to accurate and reliable separation of the three cell lines. Linear discriminant analysis (LDA) model of three cell lines was predicted with 100% sensitivity and 91% specificity. We have shown that a combination of Raman spectroscopy and chemometrics are capable of differentiation between breast cancer cell lines. These variations may be useful in identifying new spectral markers to differentiate different subtypes of breast cancer although this needs confirmation in a larger panel of cell lines as well as clinical material. Copyright © 2015 John Wiley & Sons, Ltd.     

Potential of magnetic resonance spectroscopy to detect metastasis in axillary lymph nodes in breast cancer

Focused pathological evaluation of axillary lymph nodes in breast cancer is gaining importance. Nuclear magnetic resonance (NMR) spectroscopy that assesses the whole of the specimen has the potential in evaluating micrometastases. The biochemical changes associated with breast cancer metastases in axillary nodes by in vitro NMR and its use in the detection of axillary metastases in a clinical setting in comparison with conventional histopathology is presented in this study. Eighty-eight lymph nodes obtained from 30 patients with breast cancer were investigated. Histopathology revealed metastases in 20 nodes from 11 patients, while in vitro NMR spectroscopy revealed metastases in 22 nodes. Out of these 22 nodes, 16 were the same, which showed metastases on histopathology, while 6 nodes have shown metastases only on in vitro magnetic resonance spectroscopy (MRS). These 6 nodes with suspicion of metastases on MRS were subjected to reevaluation with serial sectioning and immunohistochemistry, but no additional metastases were revealed. Forty metabolites could be identified from the MR spectrum of lymph nodes. The levels of the glycerophosphocholine-phosphocholine (GPC-PC), choline, lactate, alanine and uridine diphosphoglucose were elevated significantly in nodes with metastases. In addition, the intensity ratio of GPC-PC/threonine (Thr) was higher in nodes with metastases, and using this as marker, MRS detected the axillary metastases with a sensitivity, specificity and accuracy of 80%, 91% and 88%, respectively. Neoadjuvant chemotherapy (NACT) lowered the concentrations of GPC-PC and GPC-PC/Thr ratio. The accuracy of MRS in detecting metastases was 75% in patients who received NACT (n=9) as compared to 96% in those who did not (n=21). Our results demonstrate the potential of in vitro MRS in characterizing the metabolite profile of the axillary nodes with breast cancer metastases. It detected axillary metastases with reasonable accuracy and can be complementary to histopathological evaluation and immunohistochemistry.     

Magnetic resonance imaging for secondary assessment of breast density in a high-risk cohort

A quantitative measure of three-dimensional breast density derived from noncontrast magnetic resonance imaging (MRI) was investigated in 35 women at high-risk for breast cancer. A semiautomatic segmentation tool was used to quantify the total volume of the breast and to separate volumes of fibroglandular and adipose tissue in noncontrast MRI data. The MRI density measure was defined as the ratio of breast fibroglandular volume over total volume of the breast. The overall correlation between MRI and mammographic density measures was R²=.67. However the MRI/mammography density correlation was higher in patients with lower breast density (R²=.73) than in patients with higher breast density (R²=.26). Women with mammographic density higher than 25% exhibited very different magnetic resonance density measures spread over a broad range of values. These results suggest that MRI may provide a volumetric measure more representative of breast composition than mammography, particularly in groups of women with dense breasts. Magnetic resonance imaging density could potentially be quantified and used for a better assessment of breast cancer risk in these populations.     

Multiclass discrimination of cervical precancers using Raman spectroscopy

Raman spectroscopy has the potential to differentiate among the various stages leading to high‐grade cervical cancer such as normal, squamous metaplasia, and low‐grade cancer. For Raman spectroscopy to successfully differentiate among the stages, an applicable statistical method must be developed. Algorithms like linear discriminant analysis (LDA) are incapable of differentiating among three or more types of tissues. We developed a novel statistical method combining the method of maximum representation and discrimination feature (MRDF) to extract diagnostic information with sparse multinomial logistic regression (SMLR) to classify spectra based on nonlinear features for multiclass analysis of Raman spectra. We found that high‐grade spectra classified correctly 95% of the time; low‐grade data classified correctly 74% of the time, improving sensitivity from 92 to 98% and specificity from 81 to 96% suggesting that MRDF with SMLR is a more appropriate technique for categorizing Raman spectra. SMLR also outputs a posterior probability to evaluate the algorithm's accuracy. This combined method holds promise to diagnose subtle changes leading to cervical cancer. Copyright © 2008 John Wiley & Sons, Ltd.     

Magnetic resonance imaging of intraductal papilloma of the breast

To describe the appearance of isolated intraductal papilloma on contrast-enhanced water-specific, high spatial-resolution and rapid dynamic breast MRI, a retrospective review of unilateral breast images of 15 pathologically proven papilloma was performed. MRI revealed three patterns: Four papillomas were small, smooth, enhancing masses at the posterior end of an enlarged duct, corresponding to the "small lumenal mass" appearance of papilloma known from galactography. MRI detected two of these "small lumenal mass" papillomas in patients with abnormal nipple discharge even when galactography was unsuccessful. Seven papillomas were irregular enhancing masses detected in patients without nipple discharge. None of these papillomas had specifically benign findings. All seven demonstrated rapid enhancement and three showed rim enhancement or spiculation. These "tumor-like" papillomas mimicked invasive breast cancer on MRI. Four papillomas were occult on MRI, not revealed by either contrast-enhanced MRI or fat-suppressed T(2)-weighted MRI. Intraductal papillomas present with a variable appearance on MRI ranging from occult to "small lumenal mass" papillomas to irregular rapidly enhancing lesions that cannot be distinguished from invasive cancers.     

含NGR的多肽与肿瘤细胞作用的NMR研究

NGR为肿瘤血管特异导向肽,将其与功能肽KV7连接构建成一导向功能多肽NGR-KV7;为研究该多肽与人肿瘤乳癌细胞的相互作用,应用核磁共振技术来探讨该多肽与细胞的作用位点和亲和性;通过¹H NMR和T₂弛豫谱的分析,推断该多肽分子与人乳癌细胞结合紧密,亲和程度高.     

Comparison of in vitro breast cancer visibility in analyser‐based computed tomography with histopathology,mammography, computed tomography and magnetic resonance imaging

High‐resolution analyser‐based X‐ray imaging computed tomography (HR ABI‐CT) findings on in vitro human breast cancer are compared with histopathology, mammography, computed tomography (CT) and magnetic resonance imaging. The HR ABI‐CT images provided significantly better low‐contrast visibility compared with the standard radiological images. Fine cancer structures indistinguishable and superimposed in mammograms were seen, and could be matched with the histopathological results. The mean glandular dose was less than 1 mGy in mammography and 12–13 mGy in CT and ABI‐CT. The excellent visibility of in vitro breast cancer suggests that HR ABI‐CT may have a valuable role in the future as an adjunct or even alternative to current breast diagnostics, when radiation dose is further decreased, and compact synchrotron radiation sources become available.     

In Vitro Evaluation of Non‐Protein Adsorbing Breast Cancer Theranostics Based on 19F‐Polymer Containing Nanoparticles

Eight fluorinated nanoparticles (NPs) are synthesized, loaded with doxorubicin (DOX), and evaluated as theranostic delivery platforms to breast cancer cells. The multifunctional NPs are formed by self‐assembly of either linear or star‐shaped amphiphilic block copolymers, with fluorinated segments incorporated in the hydrophilic corona of the carrier. The sizes of the NPs confirm that small circular NPs are formed. The release kinetics data of the particles reveals clear hydrophobic core dependence, with longer sustained release from particles with larger hydrophobic cores, suggesting that the DOX release from these carriers can be tailored. Viability assays and flow cytometry evaluation of the ratios of apoptosis/necrosis indicate that the materials are non‐toxic to breast cancer cells before DOX loading; however, they are very efficient, similar to free DOX, at killing cancer cells after drug encapsulation. Both flow cytometry and confocal microscopy confirm the cellular uptake of NPs and DOX‐NPs into breast cancer cells, and in vitro ¹⁹F‐MRI measurement shows that the fluorinated NPs have strong imaging signals, qualifying them as a potential in vivo contrast agent for ¹⁹F‐MRI.     

In vivo proton magnetic resonance spectroscopy (MRS) and single photon emission computerized tomography (SPECT) in systemic lupus erythematosus (SLE)

Neuropsychiatric involvement in SLE (NP-SLE) may not be picked up by routine neuroimaging procedures like computerized tomography (CT) or magnetic resonance imaging (MRI). We prospectively studied the role of single photon emission computerized tomography (SPECT) and magnetic resonance spectroscopy (MRS) in detection of NP-SLE in 20 patients with lupus (10 with clinical NP involvement and 10 without) and 9 healthy controls. MRI abnormalities were seen in 5/10 patients with NP-SLE while the MRI was normal in all the lupus patients without clinical NP involvement. Perfusion defects on SPECT were seen in as many as 8/10 patients with NP-SLE while only 1/10 lupus patients without clinical NP involvement and none of the healthy controls demonstrated perfusion defects. MRS revealed abnormal metabolite ratios in all patients with NP-SLE and as many as 8 lupus patients without clinical NP features. Normal metabolite ratios were observed in healthy controls. SPECT and MRS can help detect changes not evident on MRI and may serve as useful supplements to existing neuroimaging techniques in the diagnosis of NP-SLE. The precise significance of alterations in regional cerebral blood flow on SPECT and neurometabolite ratios on MRS needs larger, longitudinal studies.     

High-resolution imaging without iteration: a fast and robust method for breast ultrasound tomography

Breast ultrasound tomography has the potential to improve the cost, safety, and reliability of breast cancer screening and diagnosis over the gold-standard of mammography. Vital to achieving this potential is the development of imaging algorithms to unravel the complex anatomy of the breast and its mechanical properties. The solution most commonly relied upon is time-of-flight tomography, but this exhibits low resolution due to the presence of diffraction effects. Iterative full-wave inversion methods present one solution to achieve higher resolution, but these are slow and are not guaranteed to converge to the correct solution. Presented here is HARBUT, the hybrid algorithm for robust breast ultrasound tomography, which utilizes the complementary strengths of time-of-flight and diffraction tomography resulting in a direct, fast, robust and accurate high resolution method of reconstructing the sound speed through the breast. The algorithm is shown to produce accurate reconstructions with realistic data from a complex three-dimensional simulation, with masses as small as 4 mm being clearly visible.     

Analyzing normal proliferating,hypoxic and necrotic regions of T-47D human breast cancer spheroids using Raman spectroscopy

Raman spectroscopy is an advanced chemical analytical technique that has gained significant interest in cancer research, in particular early detection and monitoring of cancer, with added advantages of non-invasive and real-time diagnosis. Recently, studies have shown its sensitivity to monitor chemical changes during cancer progression. This information will lead to identification of chemical markers (molecular fingerprints of chemical composition) that can be used as biological markers. In this study, we used a tumor spheroid model that mimics the characteristics of a non-vascular in vitro tumor model, we used a combination of Raman and multivariate approach to identify chemical changes associated with normal proliferating, hypoxic and necrotic regions of T-47D human breast cancer spheroid model. The results provide evidence that lipids, amide I, III and nucleic acid contents differ significantly in normal, hypoxic and necrotic regions. Principal component analysis loading plots has suggested that normal proliferating region separated with low amide I and high-tryptophan content compared to hypoxic and necrotic regions. These differences observed in three regions might be useful in identification of new spectral markers associated stress faced by each region progressing toward necrosis.     

Nonlinear phase dispersion spectroscopy

Nonlinear phase dispersion spectroscopy is introduced as a means to retrieve wideband, high spectral resolution profiles of the wavelength-dependent real part of the refractive index. The method is based on detecting dispersion effects imparted to a light field with low coherence transmitted through a thin sample and detected interferometrically in the spectral domain. The same sampled signal is also processed to yield quantitative phase maps and spectral information regarding the total attenuation coefficient using spectral-domain phase microscopy and spectroscopic optical coherence tomography (SOCT), respectively. Proof-of-concept experiments using fluorescent and nonfluorescent polystyrene beads and another using a red blood cell demonstrate the ability of the method to quantify various absorptive/dispersive features. The increased sensitivity of this method, novel to our knowledge, is compared to intensity-based spectroscopy (e.g., SOCT), and potential applications are discussed.     

Combined Raman spectroscopy and optical coherence tomography device for tissue characterization

We report a dual-modal device capable of sequential acquisition of Raman spectroscopy (RS) and optical coherence tomography (OCT) along a common optical axis. The device enhances application of both RS and OCT by precisely guiding RS acquisition with OCT images while also compensating for the lack of molecular specificity in OCT with the biochemical specificity of RS. We characterize the system performance and demonstrate the capability to identify structurally ambiguous features within an OCT image with RS in a scattering phantom, guide acquisition of RS from a localized malignancy in ex vivo breast tissue, and perform in vivo tissue analysis of a scab.     

Simultaneous acquisition of magnetic resonance spectroscopy (MRS) data and positron emission tomography (PET) images with a prototype MR-compatible, small animal PET imager

Multi-modality imaging (such as PET-CT) is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET, fused with anatomical images created by MRI, allow the correlation of form with function. Perhaps more exciting than the combination of anatomical MRI with PET, is the melding of PET with MR spectroscopy (MRS). Thus, two aspects of physiology could be combined in novel ways to produce new insights into the physiology of normal and pathological processes. Our team is developing a system to acquire MRI images and MRS spectra, and PET images contemporaneously. The prototype MR-compatible PET system consists of two opposed detector heads (appropriate in size for small animal imaging), operating in coincidence mode with an active field-of-view of approximately 14 cm in diameter. Each detector consists of an array of LSO detector elements coupled through a 2-m long fiber optic light guide to a single position-sensitive photomultiplier tube. The use of light guides allows these magnetic field-sensitive elements of the PET imager to be positioned outside the strong magnetic field of our 3T MRI scanner. The PET scanner imager was integrated with a 12-cm diameter, 12-leg custom, birdcage coil. Simultaneous MRS spectra and PET images were successfully acquired from a multi-modality phantom consisting of a sphere filled with 17 brain relevant substances and a positron-emitting radionuclide. There were no significant changes in MRI or PET scanner performance when both were present in the MRI magnet bore. This successful initial test demonstrates the potential for using such a multi-modality to obtain complementary MRS and PET data.     

Raman spectroscopy utilizing Fisher‐based feature selection combined with Support Vector Machines for the characterization of breast cell lines

Raman spectroscopy has the potential to significantly aid in the research and diagnosis of cancer. The information dense, complex spectra generate massive datasets in which subtle correlations may provide critical clues for biological analysis and pathological classification. Therefore, implementing advanced data mining techniques is imperative for complete, rapid and accurate spectral processing. Numerous recent studies have employed various data methods to Raman spectra for classification and biochemical analysis. Although, as Raman datasets from biological specimens are often characterized by high dimensionality and low sample numbers, many of these classification models are subject to overfitting. Furthermore, attempts to reduce dimensionality result in transformed feature spaces making the biological evaluation of significant and discriminative spectral features problematic. We have developed a novel data mining framework optimized for Raman datasets, called Fisher‐based Feature Selection Support Vector Machines (FFS‐SVM). This framework provides simultaneous supervised classification and user‐defined Fisher criterion‐based feature selection, reducing overfitting and directly yielding significant wavenumbers from the original feature space. Herein, we investigate five cancerous and non‐cancerous breast cell lines using Raman microspectroscopy and our unique FFS‐SVM framework. Our framework classification performance is then compared to several other frequently employed classification methods on four classification tasks. The four tasks were constructed by an unsupervised clustering method yielding the four different categories of cell line groupings (e.g. cancer vs non‐cancer) studied. FFS‐SVM achieves both high classification accuracies and the extraction of biologically significant features. The top ten most discriminative features are discussed in terms of cell‐type specific biological relevance. Our framework provides comprehensive cellular level characterization and could potentially lead to the discovery of cancer biomarker‐type information, which we have informally termed ‘Raman‐based spectral biomarkers’. The FFS‐SVM framework along with Raman spectroscopy will be used in future studies to investigate in‐situ dynamic biological phenomena. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic sequential 3D gadolinium-enhanced MRI of the whole breast

Dynamic contrast-enhanced 2D MR imaging of the breast has shown high sensitivity and specificity for the detection and characterization of breast lesions. We investigated the ability of a dynamic fast 3D MR imaging technique that repeatedly scans the whole breast in 44-s intervals without an interscan delay time to obtain similar sensitivity and specificity as 2D imaging. Fifty-six patients scheduled for breast biopsy were entered into the study, and 83 lesions detected by 3D dynamic scanning were biopsied. Dynamic 3D contrast-enhanced breast imaging with subtraction detected and correctly classified all 23 cancers, and 44 of the 60 benign lesions yielding a sensitivity of 100%, a specificity of 73%, and a 100% predictive negative value. The enhancement profiles of metastatic lymph nodes were similar to those of primary cancer. This technique allowed detection of multifocal and multicentric lesions and did not require a priori knowledge of lesion location. These results indicate that dynamic contrast-enhanced 3D MRI of the whole breast is a useful and economically feasible method for staging breast cancer, providing a comprehensive noninvasive method for total evaluation of the breast and axilla in patients considering breast conservation surgery or lumpectomy.