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Background: Positron emission tomography with computed tomography (PET-CT) using fluorine 18-fluorodeoxyglucose (F-18 FDG) is increasingly used to stage patients with locally advanced breast cancer and for assessing treatment response after neoadjuvant chemotherapy (NACT). Aims and Objectives: The aim of the study was to assess the correlation between PET-CT parameters and pathologic response of breast primary after NACT in breast cancer patients and to devise a grading system called NIMS grading system for response assessment using PET quantitative parameters. Materials and Methods: 55 patients who underwent F-18 FDG PET-CT before starting the therapy and again after completion of therapy were identified and included in the study. The clinical data and the histopathologic findings were recorded. All the patients received chemotherapy followed by surgery with axillary lymph node dissection. The PET-CT results were interpreted both qualitatively by visual analysis and quantitatively by estimating maximum Standardized uptake values(SUVmax) and other parameters - SUVmean, SUL, SUVBSA, Metabolic tumor volume (MTV) and Total lesion glycolysis (TLG). Results: The sensitivity and specificity of F-18 FDG PET-CT to detect the residual disease after neoadjuvant chemotherapy was 75.6% & 92.8% respectively. Differences between complete response and residual disease were significant for ΔSUVmax(p=0.005), ΔSUVmean(p=0.006), ΔSUL (0.005) and ΔSUVBSA(0.004), while ΔMTV and ΔTLG were not significantly different between the two groups. The new NIMS grading system included scoring of ΔSUVmax, ΔSUVBSA, ΔTLG and ΔMTV on scale of 1 to 4 and correlated well with PERCIST criteria. Conclusion: F-18 FDG PET-CT had a good accuracy in the detection of residual disease after completion of NACT. Pre chemotherapy PET-CT is not adequate to predict the response of primary tumour to chemotherapy. However, changes in the values of various PET-CT parameters are a sensitive tool to assess the response to chemotherapy. The new grading system is easy to use and showed good correlation to PERCIST.
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Objective Electrical status epilepticus in sleep (ESES) is defined by near-continuous epileptiform discharges during sleep along with cognitive, behavioral, and/or imaging abnormalities. We studied the neurocognitive profile and their correlation with 18 F fluorodeoxyglucose positron emission tomography (FDG PET) brain abnormalities in children with ESES. Methods Fourteen children with ESES with normal magnetic resonance imaging (MRI) from March to December 2019 were included. The intelligence quotient (IQ) and child behavior checklist (CBCL) scores were estimated using validated scales, and FDG PET brain was done at the same point of time to look for cerebral metabolic defects which was compared with a control group. Results Fourteen patients with a mean age of 8.2 ± 2.7 years were analyzed. The average duration of epilepsy was 6 ± 2.8 years. The mean IQ was 72.4 ± 18.2 and mean CBCL score was 37.3 ± 11.8. There was negative correlation between IQ and CBCL ( r = -0.55, p < 0.001). The duration of epilepsy also showed negative correlation with IQ ( r = -4.75, p < 0.001). FDG PET scan showed predominant thalamic hypometabolism in 12 of 14 patients (85.7%) on visual analysis with multiple other hypometabolic cortical and subcortical regions in the brain. The quantitative analysis showed significant difference in metabolism of basal ganglion when compared with control group. The total number of hypometabolic regions seen in the brain showed moderate positive correlation with CBCL score but no significant correlation with the IQ of cases. Conclusion This study demonstrates functional impairment of cerebral cortical, basal ganglia, and thalamic hypometabolism in a cohort of ESES patients with normal structural MRI brain study. There was a moderate correlation of extent and pattern of cerebral hypometabolism with the neuropsychological status of the child and duration of epilepsy.
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Two-dimensional electron spin resonance (2D ESR) spectroscopy is a unique experimental technique for probing protein structure and dynamics, including processes that occur at the microsecond time scale. While it provides significant resolution enhancement over the one-dimensional experimental setup, spectral broadening and noise make extraction of spectral information highly challenging. Traditionally, two-dimensional Fourier transform (2D FT) is applied for the analysis of 2D ESR signals, although its efficiency is limited to stationary signals. In addition, it often fails to resolve overlapping peaks in 2D ESR. In this work, we propose a time-frequency analysis of 2D time-domain signals, which identifies all frequency peaks by decoupling a signal into its distinct constituent components via projection on the time-frequency plane. The method utilizes 2D undecimated discrete wavelet transform (2D UDWT) as an intermediate step in the analysis, followed by signal reconstruction and 2D FT. We have applied the method to a simulated 2D double quantum coherence (DQC) signal for validation and a set of experimental 2D ESR signals, demonstrating its efficiency in resolving overlapping peaks in the frequency domain, while displaying frequency evolution with time in case of non-stationary data.
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Site directed spin labeling has enabled protein structure determination using electron spin resonance (ESR) pulsed dipolar spectroscopy (PDS). Small details in a distance distribution can be key to understanding important protein structure-function relationships. A major challenge has been to differentiate unimodal and overlapped multimodal distance distributions. They often yield similar distributions and dipolar signals. Current model-free distance reconstruction techniques such as Srivastava-Freed Singular Value Decomposition (SF-SVD) and Tikhonov regularization can suppress these small features in uncertainty and/or error bounds, despite being present. In this work, we demonstrate that continuous wavelet transform (CWT) can distinguish PDS signals from unimodal and multimodal distance distributions. We show that periodicity in CWT representation reflects unimodal distributions, which is masked for multimodal cases. This work is meant as a precursor to a cross-validation technique, which could indicate the modality of the distance distribution.
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The accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understanding their structure-function relationships and electrochemical properties. The current methods of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users' defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly/partially resolved and unresolved spectra, which is common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.
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Skeletal scintigraphy is one of the most widely performed investigations in any nuclear medicine department. However, there has been a paradigm shift in the indications for which bone scan was performed in the past 3 decades, mainly due to advancement in other imaging modalities, better disease understanding, and the development of newer disease-specific guidelines. The metastatic indications for bone scans accounted for 60.3% of cases in 1998 which reduced to 15.5% in 2021 and nonmetastatic indications rose from 39.7% in 1998 to 84.5% in 2021. Fewer bone scans are being performed for the metastatic survey, and more scans are being performed for nononcological orthopedic and rheumatological indications. This article captures the journey of skeletal scintigraphy in the past three decades.
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Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility, and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency, and/or the requirement of prior knowledge. Recently, we resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating the WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.
Subject(s)
Algorithms , Magnetic Resonance Imaging , Reproducibility of Results , Magnetic Resonance Spectroscopy/methods , Wavelet AnalysisABSTRACT
Objective: Low back pain (LBP) is a major cause of pain and disability. Identification of the pathology accurately or the pain generators is sometimes difficult with the conventional modalities such as magnetic resonance imaging (MRI), computed tomography (CT), or X-ray. Nuclear medicine investigations such as single-photon emission CT (SPECT/CT) or 18-fluorodeoxyglucose positron emission tomography-CT (18-FDG PET-CT) have emerged as an adjuvant tool in these cases. In this study, we evaluated and analyzed the role of 18-FDG PET-CT in identifying active pain generators and the outcomes of interventions based on that compared to MRI. Methodology: This study included all patients who fell under inclusion criteria presented with chronic LBP with or without radiculopathy. History and clinical examination were done as well as Visual Analog Scale (VAS) and Oswestry Disability Index (ODI) scores were calculated. All the patients underwent MRI lumbosacral spine with sacroiliac (SI) joint and 18-FDG PET-CT whole spine. Patients in whom PET-CT was positive and active pain generator was identified were managed for the specific level or pain generator responsible by appropriate modalities, i.e. surgery, interfacetal injections, transforaminal epidural injections, and SI joint injections. Patients in whom PET-CT was negative were managed according to the pain generator identified on the basis of MRI and clinical correlation. Patients were told to follow-up after 1 week and 1 month, and subsequent improvement was evaluated on the basis of VAS after 1 week and 1 month and ODI score after 1 month. Results: A total of 20 patients were included in the study, with a mean age of 41.9 ± 13.53 years. Twelve patients had multiple level pathology without the indication of significant pain generator and eight patients' symptoms did not correlate with the MRI findings. 18-FDG PET-CT was done in all patients. 10% (2/20) patients were identified with active pain generators on PET-CT which were not identified on MRI. Eleven out of twenty patients underwent intervention in the form of surgery or pain injections. The mean VAS and ODI score in the patients intervened on the basis of 18-FDG PET-CT improved by 70.59% and 50%, respectively, whereas in patients who underwent intervention on the basis of MRI had improvement in mean VAS and ODI score by 58.57% and 30.81%, respectively after 1 month. Conclusion: Inflammation and associated degenerative process in the spine is a continuous process and affects multiple levels and might not be easily picked up on MRI or other conventional modalities. Thus, 18-FDG PET-CT is useful in identifying these active inflammatory processes and thereby helping in the localization of active pain generators. Treating these active pain generators has a better outcome in patients after intervention in terms of better pain relief and quality of life and also reduces the levels being treated.
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Systemic cystic angiomatosis (SCA) is a rare disorder, usually involving the visceral organs with incidental detection during its insidious course. On radiography, it can present as multiple cystic lesions. In rare instances, it can present as mixed lesions (lytic, sclerotic) as was the case with our patient. The disease has a better prognosis than most vascular neoplasms involving the bones. We present a rare case of this disease, involving multiple organs, and presenting with an insidious onset.
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Analysis of small molecules is essential to metabolomics, natural products, drug discovery, food technology, and many other areas of interest. Current barriers preclude from identifying the constituent molecules in a mixture as overlapping clusters of NMR lines pose a major challenge in resolving signature frequencies for individual molecules. While homonuclear decoupling techniques produce much simplified pure shift spectra, they often affect sensitivity. Conversion of typical NMR spectra to pure shift spectra by signal processing without a priori knowledge about the coupling patterns is essential for accurate analysis. We developed a super-resolved wavelet packet transform based 1H NMR spectroscopy that can be used in high-throughput studies to reliably decouple individual constituents of small molecule mixtures. We demonstrate the efficacy of the method on the model mixtures of saccharides and amino acids in the presence of significant noise.
Subject(s)
Magnetic Resonance SpectroscopyABSTRACT
Background: Imaging of gliomas/glioblastomas has always been challenging. Many magnetic resonance imaging (MRI) techniques are available for imaging glioblastomas. MRI cannot always differentiate tumor from nonspecific changes and postoperative changes in brain tissue. Among the new positron emission tomography-computed tomography (PET-CT) tracers, gallium-68 prostate-specific membrane antigen (Ga-68 PSMA-11 PET-CT) appears to be the most promising one. The absence of uptake by normal brain parenchyma leads to high tumor-to-background ratio leading to better visualization of the tumor. Objective: The aim of this study was to assess the correlation of target volumes on MRI and PSMA brain scans in the treatment planning of glioblastomas. Materials and Methods: Twenty-four patients in the age group of 5-75 years with histologically proven glioblastoma were included in the study following maximum safe resection. Simulation for treatment planning was done with Ga-68 PSMA PET-CT brain with IV iodine-based contrast. The pre- and postoperative MRI images were fused with PSMA simulation images. Gross tumor volumes (GTVs) contoured on T1-contrast MRI and on PSMA scans were compared. Results: GTV contoured on MRI and PSMA brain scans showed complete overlap in 17 patients. In seven patients, the target volumes drawn on Ga-68 PSMA brain scans were slightly smaller than the target volumes drawn on MRI brain scans. This difference in volumes could be due to postoperative changes which showed enhancement on the MRI scan. Conclusion: Ga-68 PSMA PET-CT shows good correlation with MRI brain in the evaluation and RT planning in glioblastomas. Tumor necrosis and postoperative changes did not show PSMA uptake. Precise target delineation on PSMA PET-CT can potentially result in smaller and more accurate GTVs, which in turn would result in less RT-induced side effects.
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A fast and accurate time-frequency analysis is challenging for many applications, especially in the current big data era. A recent work introduces a fast continuous wavelet transform that effectively boosts the analysis speed without sacrificing the resolution of the result.
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The objective of spectral analysis is to resolve and extract relevant features from experimental data in an optimal fashion. In continuous-wave (cw) electron spin resonance (ESR) spectroscopy, both g values of a paramagnetic center and hyperfine splitting (A) caused by its interaction with neighboring magnetic nuclei in a molecule provide important structural and electronic information. However, in the presence of g - and/or A-anisotropy and/or large number of resonance lines, spectral analysis becomes highly challenging. Either high-resolution experimental techniques are employed to resolve the spectra in those cases or a range of suitable ESR frequencies are used in combination with simulations to identify the corresponding g and A values. In this work, we present a wavelet transform technique in resolving both simulated and experimental cW-ESR spectra by separating the hyperfine and super-hyperfine components. We exploit the multiresolution property of wavelet transforms that allow the separation of distinct features of a spectrum based on simultaneous analysis of spectrum and its varying frequency. We retain the wavelet components that stored the hyperfine and/or super-hyperfine features, while eliminating the wavelet components representing the remaining spectrum. We tested the method on simulated cases of metal-ligand adducts at L-, S-, and X-band frequencies, and showed that extracted g values, hyperfine and super-hyperfine coupling constants from simulated spectra, were in excellent agreement with the values of those parameters used in the simulations. For the experimental case of a copper(II) complex with distorted octahedral geometry, the method was able to extract g and hyperfine coupling constant values, and revealed features that were buried in the overlapped spectra.
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Myocardial perfusion imaging (MPI) is an important investigative tool in the diagnosis and management of coronary artery disease. This investigation has seen a manifold increase in number in past decades as compared to other investigations such as cardiac magnetic resonance imaging/positron emission tomography or computed tomography. In 2005, "Appropriate use criteria (AUC) in cardiac radionuclide imaging" was formulated by the American College of Cardiology Foundation and the American Society of Nuclear Cardiology for effective use of this investigation, later revised in 2009. We assessed the appropriateness of indications for MPI in patients presenting to the nuclear medicine department of a tertiary care hospital according to the latest AUC for cardiac radionuclide imaging. This is a retrospective analysis of all cardiac perfusion scans performed from June 2019 to January 2020 in a tertiary care teaching hospital in South India. All patients' indications for MPI were assessed for appropriateness using AUC 2009 as appropriate, inappropriate, and uncertain indications by two experienced nuclear medicine physicians blinded for results of the test and hospital stay of the patients. A total of 1015 cardiac scans were performed in the given period, which were analyzed. This included 613 males and 402 females, with most of the patients aged above 60 years (n = 640; males = 385, females = 255). Most of the patients had diabetes mellitus or hypertension or both except in 161 patients (15.8%) which did not have either of the comorbidities. Chest pain and/or shortness of breath were the most common presenting complaints. The appropriate indication for imaging was found in 784 patients (77.2%), inappropriate in 121 patients (12%), and uncertain in 110 patients (10.8%). Our results showed appropriate indication to be 77.2% and inappropriate indications as 12% for MPI referrals in a tertiary care teaching hospital, similar to Western literature but can be improved further by continued teaching and awareness campaigns.
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Noise impedes experimental studies by reducing signal resolution and/or suppressing weak signals. Signal averaging and filtering are the primary methods used to reduce noise, but they have limited effectiveness and lack capabilities to recover signals at low signal-to-noise ratios (SNRs). We utilize a wavelet transform-based approach to effectively remove noise from spectroscopic data. The wavelet denoising method we use is a significant improvement on standard wavelet denoising approaches. We demonstrate its power in extracting signals from noisy spectra on a variety of signal types ranging from hyperfine lines to overlapped peaks to weak peaks overlaid on strong ones, drawn from electron-spin-resonance spectroscopy. The results show that one can accurately extract details of complex spectra, including retrieval of very weak ones. It accurately recovers signals at an SNR of â¼1 and improves the SNR by about 3 orders of magnitude with high fidelity. Our examples show that one is now able to address weaker SNR signals much better than by previous methods. This new wavelet approach can be successfully applied to other spectroscopic signals.
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Insufficiency fractures (IFs) can be challenging to diagnose due to varied presentations, and sometimes, it changes the course of treatment, as in cancer patients in whom it has to be differentiated with metastatic disease. We present the role of Technetium 99m methylene diphosphonate (99mTc-MDP) bone scan, which is a low-cost, simple to perform, whole body diagnostic investigation in the diagnosis of IFs. This is a retrospective analysis of all patients who underwent a 99mTc-MDP bone scan in a tertiary care teaching hospital during 2013-2017 and were diagnosed as having an IF on bone scan. The bone scans were performed on a dual-head gamma camera using low-energy high-resolution collimators. Of all the bone scan performed during 2013-2017, a total of 138 patients with a mean age of 57.5 ± 14.7 years were diagnosed as having IFs based on bone scan and final clinical diagnosis. Among them, the most common complaint was regional bony pain in 62% of patients, while the most common cause was osteoporosis in 47% of patients, both postmenopausal and senile osteoporosis. In all, 265 sites of fractures were identified with a fracture average of 1.9/patient, the most common site being dorsolumbar vertebrae, followed by ribs and lower limb bones. Many unusual sites were also identified such as talus, sternum, clavicle, and scapula. 99mTc-MDP bone scan, being noninvasive whole-body imaging, is a useful investigation for evaluation of IFs and in correlation with biochemical analysis and other imaging can be used to determine the etiology of IF.
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Bacterial chemoreceptors, the histidine kinase CheA, and the coupling protein CheW form transmembrane molecular arrays with remarkable sensing properties. The receptors inhibit or stimulate CheA kinase activity depending on the presence of attractants or repellants, respectively. We engineered chemoreceptor cytoplasmic regions to assume a trimer of receptor dimers configuration that formed well-defined complexes with CheA and CheW and promoted a CheA kinase-off state. These mimics of core signaling units were assembled to homogeneity and investigated by site-directed spin-labeling with pulse-dipolar electron-spin resonance spectroscopy (PDS), small-angle x-ray scattering, targeted protein cross-linking, and cryo-electron microscopy. The kinase-off state was especially stable, had relatively low domain mobility, and associated the histidine substrate and docking domains with the kinase core, thus preventing catalytic activity. Together, these data provide an experimentally restrained model for the inhibited state of the core signaling unit and suggest that chemoreceptors indirectly sequester the kinase and substrate domains to limit histidine autophosphorylation.
Subject(s)
Chemotaxis , Escherichia coli Proteins/chemistry , Escherichia coli/chemistry , Histidine Kinase/chemistry , Methyl-Accepting Chemotaxis Proteins/chemistry , Multiprotein Complexes/chemistry , Signal Transduction , Escherichia coli/genetics , Escherichia coli Proteins/genetics , Histidine Kinase/genetics , Methyl-Accepting Chemotaxis Proteins/genetics , Multiprotein Complexes/genetics , Protein Structure, QuaternaryABSTRACT
Pelvic insufficiency fractures (IFs) are frequently diagnosed on technetium-99m methylene diphosphonate bone scan (BS), where it remains an important diagnostic imaging modality. Involvement of iliac bone in pelvic IFs is very rare. Differentiation from metastases is crucial where BS shows characteristic appearance obviating the need for further investigations for confirmation. There are many diagnostic appearances reported on BS for the diagnosis of IFs at various sites. We present a patient with cervical carcinoma who was previously treated with external beam radiotherapy to pelvis and now presented with pelvic pain. BS was performed to rule out skeletal metastases, however, the findings were diagnostic for iliac IF.
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Translation of environmental cues into cellular behavior is a necessary process in all forms of life. In bacteria, this process frequently involves two-component systems in which a sensor histidine kinase (HK) autophosphorylates in response to a stimulus before subsequently transferring the phosphoryl group to a response regulator that controls downstream effectors. Many details of the molecular mechanisms of HK activation are still unclear due to complications associated with the multiple signaling states of these large, multidomain proteins. To address these challenges, we combined complementary solution biophysical approaches to examine the conformational changes upon activation of a minimal, blue-light-sensing histidine kinase from Erythrobacter litoralis HTCC2594, EL346. Our data show that multiple conformations coexist in the dark state of EL346 in solution, which may explain the enzyme's residual dark-state activity. We also observe that activation involves destabilization of the helices in the dimerization and histidine phosphotransfer-like domain, where the phosphoacceptor histidine resides, and their interactions with the catalytic domain. Similar light-induced changes occur to some extent even in constitutively active or inactive mutants, showing that light sensing can be decoupled from activation of kinase activity. These structural changes mirror those inferred by comparing X-ray crystal structures of inactive and active HK fragments, suggesting that they are at the core of conformational changes leading to HK activation. More broadly, our findings uncover surprising complexity in this simple system and allow us to outline a mechanism of the multiple steps of HK activation.
Subject(s)
Histidine Kinase/metabolism , Light , Adenosine Diphosphate/metabolism , Darkness , Enzyme Activation/radiation effects , Histidine Kinase/chemistry , Models, Molecular , Mutation/genetics , Protein Domains , Protein Stability , Protein Structure, SecondaryABSTRACT
This paper is a continuation of the method introduced by Srivastava and Freed (2017) that is a new method based on truncated singular value decomposition (TSVD) for obtaining physical results from experimental signals without any need for Tikhonov regularization or other similar methods that require a regularization parameter. We show here how to estimate the uncertainty in the SVD-generated solutions. The uncertainty in the solution may be obtained by finding the minimum and maximum values over which the solution remains converged. These are obtained from the optimum range of singular value contributions, where the width of this region depends on the solution point location (e.g., distance) and the signal-to-noise ratio (SNR) of the signal. The uncertainty levels typically found are very small with substantial SNR of the (denoised) signal, emphasizing the reliability of the method. With poorer SNR, the method is still satisfactory but with greater uncertainty, as expected. Pulsed dipolar electron spin resonance spectroscopy experiments are used as an example, but this TSVD approach is general and thus applicable to any similar experimental method wherein singular matrix inversion is needed to obtain the physically relevant result. We show that the Srivastava-Freed TSVD method along with the estimate of uncertainty can be effectively applied to pulsed dipolar electron spin resonance signals with SNR > 30, and even for a weak signal (e.g., SNR ≈ 3) reliable results are obtained by this method, provided the signal is first denoised using wavelet transforms (WavPDS).