ABSTRACT
AIM: Whereas the prevalence of lymph node level (LNL) involvement in oral cavity squamous cell carcinomas (OCSCC) has been reported, the details of lymphatic progression patterns are insufficiently quantified. We investigate how the risk of metastases in each LNL depends on the involvement of adjacent LNLs, T-category, subsite, primary tumor lateralization, and other risk factors. METHODS: We retrospectively analyzed patients with newly diagnosed OCSCC from two institutions, totaling 348 patients. Involvement of LNLs I-V was recorded individually based on pathology after neck dissection with clinicopathological factors. The dataset is publicly available in a previously developed web-app, which allows querying patients with specific combinations of co-involved LNLs and tumor characteristics. RESULTS: Ipsilateral involvement prevalence of levels I-III was higher for advanced T-category (T3/T4) patients (32 %, 38 %, 14 %) compared to early (T1/T2) patients (14 %, 23 %, 11 %). Involvement of level I increased the involvement probability in levels II and III. Similarly, involvement of level II increased the involvement probability in levels I and III. However, there was significant isolated involvement of level I or II. Advanced nodal involvement (>1 LNL involved) was more frequent for patients with extracapsular extension. Overall contralateral involvement in levels I-III was 7 %, 4 %, 3 % and more frequent for more advanced ipsilateral involvement and for midline-crossing tumors. Involvement of levels IV and V was rare: 3 % ipsilateral and 1 % contralateral in both levels. CONCLUSIONS: Detailed quantification of LNL involvement in OCSCC depending on involvement of adjacent LNLs and clinicopathological factors may allow further personalizing guidelines on elective nodal treatment.
ABSTRACT
The elective clinical target volume (CTV-N) in oropharyngeal squamous cell carcinoma (OPSCC) is currently based mostly on the prevalence of lymph node metastases in different lymph node levels (LNLs) for a given primary tumor location. We present a probabilistic model for ipsilateral lymphatic spread that can quantify the microscopic nodal involvement risk based on an individual patient's T-category and clinical involvement of LNLs at diagnosis. We extend a previously published hidden Markov model (HMM), which models the LNLs (I, II, III, IV, V, and VII) as hidden binary random variables (RVs). Each represents a patient's true state of lymphatic involvement. Clinical involvement at diagnosis represents the observed binary RVs linked to the true state via sensitivity and specificity. The primary tumor and the hidden RVs are connected in a graph. Each edge represents the conditional probability of metastatic spread per abstract time-step, given disease at the edge's starting node. To learn these probabilities, we draw Markov chain Monte Carlo samples from the likelihood of a dataset (686 OPSCC patients) from three institutions. We compute the model evidence using thermodynamic integration for different graphs to determine which describes the data best.The graph maximizing the model evidence connects the tumor to each LNL and the LNLs I through V in order. It predicts the risk of occult disease in level IV is below 5% if level III is clinically negative, and that the risk of occult disease in level V is below 5% except for advanced T-category (T3 and T4) patients with clinical involvement of levels II, III, and IV. The provided statistical model of nodal involvement in OPSCC patients trained on multi-institutional data may guide the design of clinical trials on volume-deescalated treatment of OPSCC and contribute to more personal guidelines on elective nodal treatment.
Subject(s)
Disease Progression , Lymphatic Metastasis , Markov Chains , Oropharyngeal Neoplasms , Humans , Lymphatic Metastasis/pathology , Oropharyngeal Neoplasms/pathology , Lymph Nodes/pathology , Models, Statistical , Squamous Cell Carcinoma of Head and Neck/pathology , Monte Carlo MethodABSTRACT
Background and Purpose: The feasibility of acquiring diffusion-weighted imaging (DWI) images on an MR-Linac for quantitative response assessment during radiotherapy was explored. DWI data obtained with a Spin Echo Echo Planar Imaging sequence adapted for a 0.35 T MR-Linac were examined and compared with DWI data from a conventional 3 T scanner. Materials and Methods: Apparent diffusion coefficient (ADC) measurements and a distortion correction technique were investigated using DWI-calibrated phantoms and in the brains of seven volunteers. All DWI utilized two phase-encoding directions for distortion correction and off-resonance field estimation. ADC maps in the brain were analyzed for automatically segmented normal tissues. Results: Phantom ADC measurements on the MR-Linac were within a 3 % margin of those recorded by the 3 T scanner. The maximum distortion observed in the phantom was 2.0 mm prior to correction and 1.1 mm post-correction on the MR-Linac, compared to 6.0 mm before correction and 3.6 mm after correction at 3 T. In vivo, the average ADC values for gray and white matter exhibited variations of 14 % and 4 %, respectively, for different selections of b-values on the MR-Linac. Distortions in brain images before correction, estimated through the off-resonance field, reached 2.7 mm on the MR-Linac and 12 mm at 3 T. Conclusion: Accurate ADC measurements are achievable on a 0.35 T MR-Linac, both in phantom and in vivo. The selection of b-values significantly influences ADC values in vivo. DWI on the MR-Linac demonstrated lower distortion levels, with a maximum distortion reduced to 1.1 mm after correction.
ABSTRACT
Background and Purpose: Standard imaging protocols can guarantee the spatial integrity of magnetic resonance (MR) images utilized in radiotherapy. However, the presence of metallic implants can significantly compromise this integrity. Our proposed method aims at characterizing the geometric distortions induced by both passive and active implants commonly encountered in planning images obtained from a low-field 0.35 T MR-linear accelerator (LINAC). Materials and Methods: We designed a spatial integrity phantom defining 1276 control points and covering a field of view of 20x20x20 cm3. This phantom was scanned in a water tank with and without different implants used in hip and shoulder arthroplasty procedures as well as with active cardiac stimulators. The images were acquired with the clinical planning sequence (balanced steady-state free-precession, resolution 1.5x1.5x1.5 mm3). Spatial integrity was assessed by the Euclidian distance between the control point detected on the image and their theoretical locations. A first plane free of artefact (FPFA) was defined to evaluate the spatial integrity beyond the larger banding artefact. Results: In the region extending up to 20 mm from the largest banding artefacts, the tested passive and active implants could cause distortions up to 2 mm and 3 mm, respectively. Beyond this region the spatial integrity was recovered and the image could be considered as unaffected by the implants. Conclusions: We characterized the impact of common implants on a low field MR-LINAC planning sequence. These measurements could support the creation of extra margin while contouring organs at risk and target volumes in the vicinity of implants.
ABSTRACT
Dataset: We provide a dataset on lymph node metastases in 968 patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC). All patients received neck dissection and we report the number of metastatic versus investigated lymph nodes per lymph node level (LNL) for every individual patient. Additionally, clinicopathological factors including T-category, primary tumor subsite (ICD-O-3 code), age, and sex are reported for all patients. The data is provided as three datasets: Dataset 1 contains 373 HNSCC patients treated at Centre Léon Bérard (CLB), France, with primary tumor location in the oral cavity, oropharynx, hypopharynx, and larynx. Dataset 2 contains 332 HNSCC patients treated at the Inselspital, Bern University Hospital (ISB), Switzerland with primary tumor location in the oral cavity, oropharynx, hypopharynx, and larynx. For these patients, additional information is provided including lateralization of the primary tumor, size and location of the largest metastases, and clinical involvement based on computed tomography (CT), magnetic resonance imaging (MRI), and/or 18FDG-positron emission tomography (PET/CT) imaging. Dataset 3 consists of 263 oropharyngeal SCC patients underlying a previous publication by Bauwens et al. [1], which were treated at CLB. For these patients, additional information including HPV status, lateralization of the primary tumor and clinically diagnosed lymph node involvement is provided. Reuse Potential: The data may be used to quantify the probability of occult lymph node metastases in each LNL, depending on an individual patient's characteristics of the primary tumor and the location of clinically diagnosed lymph node metastases. As such, the data may contribute to further personalize the elective treatment of the neck for HNSCC patients, i.e. definition of the elective clinical target volume (CTV-N) in radiotherapy (RT) and the extent of neck dissection (ND) in surgery. There exists only one similar publicly available dataset that reports clinical involvement per LNL in 287 oropharyngeal SCC patients [2]. The data presented in this article substantially extends the available data, it additionally includes pathologically assessed involvement per LNL, and it provides data for multiple subsites in the head and neck region.
ABSTRACT
â¢Data on cardiac toxicity after SBRT for ultra-central lung tumors remains limited.â¢We analyzed the dose to 18 cardiac sub-structures and cardiovascular toxicity.â¢A SBRT regimen of 45 Gy in 8-10 fractions yields good local control and low toxicity.â¢The highest cardiac doses were observed in the pulmonary artery and left atrium.â¢Higher doses to the base of the heart seem to be associated with non-cancer deaths.
ABSTRACT
Background and purpose: Synthetic computed tomography (sCT) scans are necessary for dose calculation in magnetic resonance (MR)-only radiotherapy. While deep learning (DL) has shown remarkable performance in generating sCT scans from MR images, research has predominantly focused on high-field MR images. This study presents the first implementation of a DL model for sCT generation in head-and-neck (HN) cancer using low-field MR images. Specifically, the use of vision transformers (ViTs) was explored. Materials and methods: The dataset consisted of 31 patients, resulting in 196 pairs of deformably-registered computed tomography (dCT) and MR scans. The latter were obtained using a balanced steady-state precession sequence on a 0.35T scanner. Residual ViTs were trained on 2D axial, sagittal, and coronal slices, respectively, and the final sCTs were generated by averaging the models' outputs. Different image similarity metrics, dose volume histogram (DVH) deviations, and gamma analyses were computed on the test set (n = 6). The overlap between auto-contours on sCT scans and manual contours on MR images was evaluated for different organs-at-risk using the Dice score. Results: The median [range] value of the test mean absolute error was 57 [37-74] HU. DVH deviations were below 1% for all structures. The median gamma passing rates exceeded 94% in the 2%/2mm analysis (threshold = 90%). The median Dice scores were above 0.7 for all organs-at-risk. Conclusions: The clinical applicability of DL-based sCT generation from low-field MR images in HN cancer was proved. High sCT-dCT similarity and dose metric accuracy were achieved, and sCT suitability for organs-at-risk auto-delineation was shown.
ABSTRACT
Dataset: We provide a dataset on lymph node level (LNL) involvement in 287 patients with newly diagnosed oropharyngeal squamous cell carcinoma (OPSCC). For each patient, ipsilateral and contralateral LNL involvement for levels I to VII is reported together with clinicopathological factors including TNM-stage, primary tumor subsite, tumor lateralization, HPV status, sex, age, smoking status, and primary treatment. LNL involvement was assessed individually based on available diagnostic modalities (PET, MRI, CT, fine needle aspiration) by reviewing pathology and radiology reports together with the radiological images. The data is shared as a CSV-table with rows of patients and columns of patient/tumor-specific information and the involvement of individual LNL based on the respective diagnostic modalities. Reuse potential: Patterns of lymphatic progression have never been reported on a patient-individual basis in as much detail as provided in this dataset. The data can be used to build quantitative models for lymphatic tumor progression to estimate the probability of occult metastases in LNLs. This may in turn allow for further personalization of the elective clinical target volume definition in radiotherapy and the extent of neck dissection for surgically treated patients. The data can be pooled with other data to build large multi-institutional datasets on lymphatic metastatic progression in the future. Co-submission: This paper supports the original scientific article by Roman Ludwig, Jean-Marc Hoffmann, Bertrand Pouymayou, Grégoire Morand, Martina Broglie Däppen, Matthias Guckenberger, Vincent Grégoire, Panagiotis Balermpas, Jan Unkelbach, "Detailed patient-individual reporting of lymph node involvement in oropharyngeal squamous cell carcinoma with an online interface", Radiotherapy & Oncology [1].
ABSTRACT
PURPOSE/OBJECTIVE: Whereas the prevalence of lymph node level (LNL) involvement in head & neck squamous cell carcinomas (HNSCC) has been reported, the details of lymphatic progression patterns are insufficiently quantified. In this study, we investigate how the risk of metastases in each LNL depends on the involvement of upstream LNLs, T-category, HPV status and other risk factors. MATERIALS/METHODS: We retrospectively analyzed patients with newly diagnosed oropharyngeal squamous cell carcinoma (OPSCC) treated at a single institution, resulting in a dataset of 287 patients. For all patients, involvement of LNLs I-VII was recorded individually based on available diagnostic modalities (PET, MRI, CT, FNA) together with clinicopathological factors. To analyze the dataset, a web-based graphical user interface (GUI) was developed, which allows querying the number of patients with a certain combination of co-involved LNLs and tumor characteristics. RESULTS: The full dataset and GUI is part of the publication. Selected findings are: Ipsilateral level IV was involved in 27% of patients with level II and III involvement, but only in 2% of patients with level II but not III involvement. Prevalence of involvement of ipsilateral levels II, III, IV, V was 79%, 34%, 7%, 3% for early T-category patients (T1/T2) and 85%, 50%, 17%, 9% for late T-category (T3/T4), quantifying increasing involvement with T-category. Contralateral levels II, III, IV were involved in 41%, 19%, 4% and 12%, 3%, 2% for tumors with and without midline extension, respectively. T-stage dependence of LNL involvement was more pronounced in HPV negative than positive tumors, but overall involvement was similar. Ipsilateral level VII was involved in 14% and 6% of patients with primary tumors in the tonsil and the base of tongue, respectively. CONCLUSIONS: Detailed quantification of LNL involvement in HNSCC depending on involvement of upstream LNLs and clinicopathological factors may allow for further personalization of CTV-N definition in the future.
Subject(s)
Head and Neck Neoplasms , Oropharyngeal Neoplasms , Papillomavirus Infections , Head and Neck Neoplasms/pathology , Humans , Lymph Nodes/pathology , Lymphatic Metastasis/pathology , Neoplasm Staging , Oropharyngeal Neoplasms/pathology , Papillomavirus Infections/pathology , Retrospective Studies , Squamous Cell Carcinoma of Head and Neck/pathologyABSTRACT
Currently, elective clinical target volume (CTV-N) definition for head and neck squamous cell carcinoma (HNSCC) is mostly based on the prevalence of nodal involvement for a given tumor location. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement in lymph node levels (LNL) given the location of macroscopic metastases and T-category. This may allow for further personalized CTV-N definition based on an individual patient's state of disease. We model the patient's state of metastatic lymphatic progression as a collection of hidden binary random variables that indicate the involvement of LNLs. In addition, each LNL is associated with observed binary random variables that indicate whether macroscopic metastases are detected. A hidden Markov model (HMM) is used to compute the probabilities of transitions between states over time. The underlying graph of the HMM represents the anatomy of the lymphatic drainage system. Learning of the transition probabilities is done via Markov chain Monte Carlo sampling and is based on a dataset of HNSCC patients in whom involvement of individual LNLs was reported. The model is demonstrated for ipsilateral metastatic spread in oropharyngeal HNSCC patients. We demonstrate the model's capability to quantify the risk of microscopic involvement in levels III and IV, depending on whether macroscopic metastases are observed in the upstream levels II and III, and depending on T-category. In conclusion, the statistical model of lymphatic progression may inform future, more personalized, guidelines on which LNL to include in the elective CTV. However, larger multi-institutional datasets for model parameter learning are required for that.
Subject(s)
Head and Neck Neoplasms/diagnosis , Markov Chains , Models, Theoretical , Algorithms , Bayes Theorem , Disease Progression , Head and Neck Neoplasms/pathology , Head and Neck Neoplasms/therapy , Humans , Lymph Nodes/pathology , Lymphatic Metastasis , Neoplasm Staging , Risk Assessment , Squamous Cell Carcinoma of Head and Neck/diagnosis , Squamous Cell Carcinoma of Head and Neck/pathology , Squamous Cell Carcinoma of Head and Neck/therapyABSTRACT
Treatment planning in radiotherapy distinguishes three target volume concepts: the gross tumor volume (GTV), the clinical target volume (CTV), and the planning target volume (PTV). Over time, GTV definition and PTV margins have improved through the development of novel imaging techniques and better image guidance, respectively. CTV definition is sometimes considered the weakest element in the planning process. CTV definition is particularly complex since the extension of microscopic disease cannot be seen using currently available in-vivo imaging techniques. Instead, CTV definition has to incorporate knowledge of the patterns of tumor progression. While CTV delineation has largely been considered the domain of radiation oncologists, this paper, arising from a 2019 ESTRO Physics research workshop, discusses the contributions that medical physics and computer science can make by developing computational methods to support CTV definition. First, we overview the role of image segmentation algorithms, which may in part automate CTV delineation through segmentation of lymph node stations or normal tissues representing anatomical boundaries of microscopic tumor progression. The recent success of deep convolutional neural networks has also enabled learning entire CTV delineations from examples. Second, we discuss the use of mathematical models of tumor progression for CTV definition, using as example the application of glioma growth models to facilitate GTV-to-CTV expansion for glioblastoma that is consistent with neuroanatomy. We further consider statistical machine learning models to quantify lymphatic metastatic progression of tumors, which may eventually improve elective CTV definition. Lastly, we discuss approaches to incorporate uncertainty in CTV definition into treatment plan optimization as well as general limitations of the CTV concept in the case of infiltrating tumors without natural boundaries.
Subject(s)
Neoplasms , Radiotherapy Planning, Computer-Assisted , Humans , Neoplasms/diagnostic imaging , Neoplasms/radiotherapy , Neural Networks, ComputerABSTRACT
The introduction of real-time imaging by magnetic resonance guided linear accelerators (MR-Linacs) enabled adaptive treatments and gating on the tumor position. Different end-to-end tests monitored the accuracy of our MR-Linac during the first year of clinical operation. We report on the stability of these tests covering a static, adaptive and gating workflow. Film measurements showed gamma passing rates of 96.4% ± 3.4% for the static tests (five measurements) and for the two adaptive tests 98.9% and 99.99%, respectively (criterion 2%/2mm). The gated point dose measurements in the breathing phantom were 2.7% lower than in the static phantom.
ABSTRACT
Many tumors including head and neck squamous cell carcinoma (HNSCC) spread along the lymphatic network. Current imaging modalities can only detect sufficiently large metastases. Therefore, adjacent lymph node levels (LNL) are irradiated electively since they may harbor microscopic tumors. We apply Bayesian Networks (BN) to model lymphatic tumor progression. The model can subsequently be used to personalize the risk estimation of microscopic lymph node metastases in newly diagnosed patients based on their distribution of macroscopic metastases. A BN is a graphical representation of a joint probability distribution. We represent LNLs by binary random variables corresponding to the BN nodes. Each LNL is associated with a hidden microscopic state and an observed macroscopic state (e.g. 18F-FDG-PET/CT imaging). The primary tumor is represented by network input nodes. We demonstrate the concept for early T-stage oropharyngeal carcinomas and their spread to ipsilateral lymph node levels (LNL) Ib to IV. We show that the BN parameters can be efficiently learnt by merging pathology findings on microscopic tumor progression (which is limited to a few published studies) and imaging data on macroscopic tumor progression such as CT and 18F-FDG-PET (which are widely available in clinical practice). The trained network can be used to quantify how the distribution of macroscopic metastases impacts the probability of microscopic involvement of the remaining LNLs. The analysis suggests that the risk of microscopic involvement of level IV exceeds 5% only if level III harbors metastases. Excluding level IV from the elective CTV for other patients would reduce the integral dose delivered to the patient and potentially reduce acute and late side effects.
Subject(s)
Bayes Theorem , Head and Neck Neoplasms/pathology , Lymph Nodes/pathology , Positron Emission Tomography Computed Tomography/methods , Disease Progression , Fluorodeoxyglucose F18 , Head and Neck Neoplasms/diagnostic imaging , Humans , Lymph Nodes/diagnostic imaging , Lymphatic Metastasis , Neoplasm Staging , Tumor BurdenABSTRACT
Sucrose overfeeding increases intrahepatocellular (IHCL) and intramyocellular (IMCL) lipid concentrations in healthy subjects. We hypothesized that these effects would be modulated by diet protein/fat content. Twelve healthy men and women were studied on two occasions in a randomized, cross-over trial. On each occasion, they received a 3-day 12% protein weight maintenance diet (WM) followed by a 6-day hypercaloric high sucrose diet (150% energy requirements). On one occasion the hypercaloric diet contained 5% protein and 25% fat (low protein-high fat, LP-HF), on the other occasion it contained 20% protein and 10% fat (high protein-low fat, HP-LF). IHCL and IMCL concentrations (magnetic resonance spectroscopy) and energy expenditure (indirect calorimetry) were measured after WM, and again after HP-LF/LP-HF. IHCL increased from 25.0 ± 3.6 after WM to 147.1 ± 26.9 mmol/kg wet weight (ww) after LP-HF and from 30.3 ± 7.7 to 57.8 ± 14.8 after HP-LF (two-way ANOVA with interaction: p < 0.001 overfeeding x protein/fat content). IMCL increased from 7.1 ± 0.6 to 8.8 ± 0.7 mmol/kg ww after LP-HF and from 6.2 ± 0.6 to 6.9 ± 0.6 after HP-LF, (p < 0.002). These results indicate that liver and muscle fat deposition is enhanced when sucrose overfeeding is associated with a low protein, high fat diet compared to a high protein, low fat diet.
Subject(s)
Adipose Tissue/metabolism , Diet , Dietary Fats/administration & dosage , Dietary Proteins/administration & dosage , Dietary Sucrose/adverse effects , Liver/drug effects , Muscle, Skeletal/drug effects , Adiposity/drug effects , Adult , Cross-Over Studies , Diet, High-Fat/adverse effects , Diet, Protein-Restricted/adverse effects , Dietary Fats/metabolism , Dietary Fats/pharmacology , Dietary Proteins/pharmacology , Energy Intake , Feeding Behavior , Female , Healthy Volunteers , Humans , Lipid Metabolism/drug effects , Lipids , Liver/cytology , Liver/metabolism , Male , Muscle, Skeletal/cytology , Muscle, Skeletal/metabolism , Young AdultABSTRACT
Background: Overconsumption of energy-dense foods and sleep restriction are both associated with the development of metabolic and cardiovascular diseases, but their combined effects remain poorly evaluated. Objective: The aim of this study was to assess whether sleep restriction potentiates the effects of a short-term overfeeding on intrahepatocellular lipid (IHCL) concentrations and on glucose homeostasis. Design: Ten healthy subjects were exposed to a 6-d overfeeding period (130% daily energy needs, with 15% extra energy as sucrose and 15% as fat), with normal sleep (8 h sleep opportunity time) or sleep restriction (4 h sleep opportunity time), according to a randomized, crossover design. At baseline and after intervention, IHCL concentrations were measured by proton magnetic resonance spectroscopy, and a dual intravenous [6,6-2H2]-, oral 13C-labeled glucose tolerance test and a polysomnographic recording were performed. Results: Overfeeding significantly increased IHCL concentrations (Poverfeeding < 0.001; overfeeding + normal sleep: +53% ± 16%). During the oral glucose tolerance test, overfeeding significantly increased endogenous glucose production (Poverfeeding = 0.034) and the oxidation of 13C-labeled glucose load (Poverfeeding = 0.038). Sleep restriction significantly decreased total sleep time, and the duration of stages 1 and 2 and rapid eye movement sleep (all P < 0.001), whereas slow-wave sleep duration was preserved (Poverfeeding × sleep = 0.809). Compared with overfeeding, overfeeding + sleep restriction did not change IHCL concentrations (Poverfeeding × sleep = 0.541; +83% ± 33%), endogenous glucose production (Poverfeeding × sleep = 0.567), or exogenous glucose oxidation (Poverfeeding × sleep = 0.118). Sleep restriction did not significantly alter blood pressure, heart rate, or plasma cortisol concentrations (all Poverfeeding × sleep = NS). Conclusions: Six days of a high-sucrose, high-fat overfeeding diet significantly increased IHCL concentrations and increased endogenous glucose production, suggesting hepatic insulin resistance. These effects of overfeeding were not altered by sleep restriction. This trial was registered at clinicaltrials.gov as NCT02075723. Other study ID numbers: SleepDep 02/14.
Subject(s)
Overnutrition/metabolism , Sleep Deprivation/metabolism , Adult , Blood Glucose/metabolism , Cross-Over Studies , Diet, High-Fat/adverse effects , Dietary Sucrose/administration & dosage , Dietary Sucrose/adverse effects , Energy Intake , Female , Glucose Tolerance Test , Homeostasis , Humans , Insulin Resistance , Lipid Metabolism/drug effects , Lipids/analysis , Liver/chemistry , Liver/metabolism , Male , Overnutrition/complications , Proton Magnetic Resonance Spectroscopy , Weight Gain , Young AdultABSTRACT
PURPOSE: A 31 P-MR inversion transfer (IT) method with a short adiabatic inversion pulse is proposed and its test-retest reliability was evaluated for two spectral fitting strategies. METHODS: Assessment in a test-retest design (3 Tesla, vastus muscles, 12 healthy volunteers, 14 inversion times, 22 ms asymmetric adiabatic inversion pulse, adiabatic excitation); spectral fitting in Fitting Tool for Interrelated Arrays of Datasets (FitAID) and Java Magnetic Resonance User Interface (jMRUI); least squares solution of the Bloch-McConnell-Solomon matrix formalism including all 14 measured time-points with equal weighting. RESULTS: The cohort averages of k[PCrâγ-ATP] (phosphocreatine, PCr; adenosine triphosphate, ATP) are 0.246 ± 0.050s-1 versus 0.254 ± 0.050s-1 , and k[Piâγ-ATP] 0.086 ± 0.033s-1 versus 0.066 ± 0.034s-1 (average ± standard deviation, jMRUI versus FitAID). Coefficients of variation of the differences between test and retest are lowest (9.5%) for k[PCrâγ-ATP] fitted in FitAID, larger (15.2%) for the fit in jMRUI, and considerably larger for k[Piâγ-ATP] fitted in FitAID (43.4%) or jMRUI (47.9%). The beginning of the IT effect can be observed with magnetizations above 92% for noninverted lines while inversion of the ATP resonances is better than -72%. CONCLUSION: The performance of the asymmetric adiabatic pulse allows an accurate observation of IT effects even in the early phase; the least squares fit of the Bloch-McConnell-Solomon matrix formalism is robust; and the type of spectral fitting can influence the results significantly. Magn Reson Med 78:33-39, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Subject(s)
Algorithms , Magnetic Resonance Spectroscopy/methods , Molecular Imaging/methods , Muscle, Skeletal/metabolism , Phosphocreatine/analogs & derivatives , Phosphorus/pharmacokinetics , Signal Processing, Computer-Assisted , Adult , Female , Humans , Male , Observer Variation , Phosphocreatine/metabolism , Reproducibility of Results , Sensitivity and Specificity , Tissue DistributionABSTRACT
PURPOSE: To reliably determine the amplitude of the transmit radiofrequency ( B1+) field in moving organs like the liver and heart, where most current techniques are usually not feasible. METHODS: B1+ field measurement based on the Bloch-Siegert shift induced by a pair of Fermi pulses in a double-triggered modified Point RESolved Spectroscopy (PRESS) sequence with motion-compensated crusher gradients has been developed. Performance of the sequence was tested in moving phantoms and in muscle, liver, and heart of six healthy volunteers each, using different arrangements of transmit/receive coils. RESULTS: B1+ determination in a moving phantom was almost independent of type and amplitude of the motion and agreed well with theory. In vivo, repeated measurements led to very small coefficients of variance (CV) if the amplitude of the Fermi pulse was chosen above an appropriate level (CV in muscle 0.6%, liver 1.6%, heart 2.3% with moderate amplitude of the Fermi pulses and 1.2% with stronger Fermi pulses). CONCLUSION: The proposed sequence shows a very robust determination of B1+ in a single voxel even under challenging conditions (transmission with a surface coil or measurements in the heart without breath-hold).