PET measured hypoxia and MRI parameters in re-irradiated head and neck squamous cell carcinomas: findings of a prospective pilot study [version 2; peer review: 2 approved]
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ABSTRACT:
SUBMITTER: Rogasch J
PROVIDER: S-EPMC7970429 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description:PurposeTo investigate the correlation of parameters measured by dynamic-contrast-enhanced MRI (DCE-MRI) and 18F-FDG PET/CT in spinal tumors, and their role in differential diagnosis.MethodsA total of 49 patients with pathologically confirmed spinal tumors, including 38 malignant, six benign and five borderline tumors, were analyzed. The MRI and PET/CT were done within 3 days, before biopsy. On MRI, the ROI was manually placed on area showing the strongest enhancement to measure pharmacokinetic parameters Ktrans and kep. On PET, the maximum standardized uptake value SUVmax was measured. The parameters in different histological groups were compared. ROC was performed to differentiate between the two largest subtypes, metastases and plasmacytomas. Spearman rank correlation was performed to compare DCE-MRI and PET/CT parameters.ResultsThe Ktrans, kep and SUVmax were not statistically different among malignant, benign and borderline groups (P = 0.95, 0.50, 0.11). There was no significant correlation between Ktrans and SUVmax (r = - 0.20, P = 0.18), or between kep and SUVmax (r = - 0.16, P = 0.28). The kep was significantly higher in plasmacytoma than in metastasis (0.78 ± 0.17 vs. 0.61 ± 0.18, P = 0.02); in contrast, the SUVmax was significantly lower in plasmacytoma than in metastasis (5.58 ± 2.16 vs. 9.37 ± 4.26, P = 0.03). In differential diagnosis, the AUC of kep and SUVmax was 0.79 and 0.78, respectively.ConclusionsThe vascular parameters measured by DCE-MRI and glucose metabolism measured by PET/CT from the most aggressive tumor area did not show a significant correlation. The results suggest they provide complementary information reflecting different aspects of the tumor, which may aid in diagnosis of spinal lesions. These slides can be retrieved under Electronic Supplementary Material.
| S-EPMC7709817 | biostudies-literature
Project description:PurposeTumor hypoxia is a major cause of radiation resistance, often present in various solid tumors. Dynamic [18 F]-fluoromisonidazole (FMISO) PET imaging is able to reliably assess tumor hypoxia. Comprehensive characterization of tumor microenvironment through FMISO-PET and dynamic contrast enhanced (DCE) MR multimodality imaging might be a valuable alternative to the dynamic FMISO-PET acquisition. The aim of this work was to explore the correlation between the FMISO-PET and DCE-MRI kinetic parameters.MethodsThis study was done on head and neck cancer patients (N = 6), who were imaged dynamically with FMISO-PET and DCE-MRI on the same day. Images were registered and analyzed for kinetics on a voxel basis. FMISO-PET images were analyzed with the two-tissue compartment three rate-constant model. Additionally, tumor-to-muscle ratio (TMR) maps were evaluated. DCE-MRI was analyzed with the extended Tofts model. Voxel-wise Pearson's coefficients were calculated for each patient to assess pairwise parameter correlations.ResultsMedian correlations between FMISO uptake parameters and DCE-MRI kinetic parameters varied across the parameter pairs in the range from -0.05 to 0.71. The highest median correlation of r = 0.71 was observed for the pair Vb -vp , while the K1 -Ktrans median correlation was r = 0.45. Median correlation coefficients for the K1 -vp and the Ki -Ktrans pairs were r = 0.42 and r = 0.32, respectively. Correlations between FMISO uptake rate parameter Ki and DCE-MRI kinetic parameters varied substantially across the patients, whereas correlations between the FMISO and DCE-MRI vascular parameters were consistently high. Median TMR-K1 and TMR-Ktrans correlations were r = 0.52 and r = 0.46, respectively, but varied substantially across the patients.ConclusionsBased on this clinical evidence, we can conclude that the vascular fraction parameters obtained through DCE-MRI kinetic analysis or FMISO kinetic analysis measure the same biological property, while other kinetic parameters are unrelated. These results might be useful in the design of future clinical trials involving FMISO-PET/DCE-MR multimodality imaging for the assessment of tumor microenvironment.
| S-EPMC5485084 | biostudies-literature
Project description:ObjectiveSimultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems.MethodThe NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3-7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction.ResultsThe range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively.ConclusionsFor two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters.
| S-EPMC8571452 | biostudies-literature
Project description:Functional MRI (fMRI) studies reported disruption of resting-state networks (RSNs) in several neuropsychiatric disorders. PET with 18F-FDG captures neuronal activity that is in steady state at a longer time span and is less dependent on neurovascular coupling. Methods: In the present study, we aimed to identify RSNs in 18F-FDG PET data and compare their spatial pattern with those obtained from simultaneously acquired resting-state fMRI data in 22 middle-aged healthy subjects. Results: Thirteen and 17 meaningful RSNs could be identified in PET and fMRI data, respectively. Spatial overlap was fair to moderate for the default mode, left central executive, primary and secondary visual, sensorimotor, cerebellar, and auditory networks. Despite recording different aspects of neural activity, similar RSNs were detected by both imaging modalities. Conclusion: The results argue for the common neural substrate of RSNs and encourage testing of the clinical utility of resting-state connectivity in PET data.
| S-EPMC6944183 | biostudies-literature
Project description:BackgroundSystemic inflammation is predictive of the overall survival in cancer patients and is related to the density of immune cells in the tumor microenvironment of cancer, which in turn correlates with 18F -fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) metabolic parameters (MPs). The density of tumor-infiltrating lymphocytes (TILs) in the microenvironment has the potential to be a biomarker that can be used clinically to optimize patient selection in oropharyngeal head and neck squamous cell carcinoma (HNSCC). There is little to no data regarding the association of systemic inflammation with PET/CT-MPs, especially in HNSCC. This study aimed to evaluate the correlation between markers of host inflammation, namely blood neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), with the PET/CT-MPs standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor, derived from FDG-PET/CT in patients with nonmetastatic (cM0) HNSCC before treatment. We hypothesized that NLR and PLR at baseline are positively correlated with PET/CT-MPs.MethodsA retrospective review of consecutive patients with HNSCC with a pretreatment PET/CT was performed. NLR and PLR were computed using complete blood counts measured within 10 days before the start of any treatment. The correlation between NLR and PLR with PET/CT-MPs was evaluated with Spearman's rho test.ResultsSeventy-one patients were analyzed. Overall survival (OS) at 1, 2, and 3 years was 86%, 76%, and 68%. PLR was found to be correlated with MTV (rho = 0.26, P = .03) and TLG (rho = 0.28, P = .02) but not with maximum SUV or mean SUV. There was no correlation between NLR and the analyzed PET/CT-MPs. TLG was associated with worse survival in uni- and multivariable analysis, but no other PET/CT-MPs were associated with either OS or disease-specific survival (DSS). NLR and PLR were associated with OS and DSS on uni- and multivariable analysis.ConclusionsIn patients with HNSCC before any treatment such as definitive radio (chemo)therapy or oncologic surgery followed by adjuvant RT, baseline PLR correlated with MTV and TLG but not with SUV. NLR was not correlated with any PET/CT-MPs analyzed in our study. Confirmatory studies are needed, and a potential interaction between tumor microenvironment, host inflammation, and FDG-PET/CT measures warrants further investigation.
| S-EPMC9375277 | biostudies-literature
Project description:BackgroundHypoxia and large tumor volumes are negative prognostic factors for patients with head and neck squamous cell carcinoma (HNSCC) treated with radiation therapy (RT). PET-scanning with specific hypoxia-tracers (hypoxia-PET) can be used to non-invasively assess hypoxic tumor volume. Primary tumor volume is readily available for patients undergoing RT. However, the relationship between hypoxic volume and primary tumor volume is yet an open question. The current study investigates the hypotheses that larger tumors contain both a larger hypoxic volume and a higher hypoxic fraction.MethodsPubMed and Embase were systematically searched to identify articles fulfilling the predefined criteria. Individual tumor data (primary tumor volume and hypoxic volume/fraction) was extracted. Relationship between hypoxic volume and primary tumor volume was investigated by linear regression. The correlation between hypoxic fraction and log2(primary tumor volume) was determined for each cohort and in a pooled analysis individual regression slopes and coefficients of determination (R2) were weighted according to cohort size.Results21 relevant articles were identified and individual data from 367 patients was extracted, out of which 323 patients from 17 studies had quantifiable volumes of interest. A correlation between primary tumor volume and PET-determined hypoxic volume was found (P <.001, R2 = 0.46). Larger tumors had a significantly higher fraction of hypoxia compared with smaller tumors (P<.01). The weighted analysis of all studies revealed that for each doubling of the tumor volume, the hypoxic fraction increased by four percentage points.ConclusionThis study shows correlations between primary tumor volume and hypoxic volume as well as primary tumor volume and the hypoxic fraction in patients with HNSCC. The findings suggest that not only do large tumors contain more cancer cells, they also have a higher proportion of potentially radioresistant hypoxic cells. This knowledge can be important when individualizing RT.
| S-EPMC9234341 | biostudies-literature
Project description:BackgroundThe Centiloid scale was developed to standardise the results of beta-amyloid (Aβ) PET. We aimed to determine the Centiloid unit (CL) thresholds for CERAD sparse and moderate-density neuritic plaques, Alzheimer's disease neuropathologic change (ADNC) score of intermediate or high probability of Alzheimer's Disease (AD), final clinicopathological diagnosis of AD, and expert visual read of a positive Aβ PET scan.MethodsAβ PET results in CL for 49 subjects were compared with post-mortem findings, visual read, and final clinicopathological diagnosis. The Youden Index was used to determine the optimal CL thresholds from receiver operator characteristic (ROC) curves.ResultsA threshold of 20.1 CL (21.3 CL when corrected for time to death, AUC 0.97) yielded highest accuracy in detecting moderate or frequent plaque density while < 10 CL was optimal for excluding neuritic plaque. The threshold for ADNC intermediate or high likelihood AD was 49.4 CL (AUC 0.98). Those cases with a final clinicopathological diagnosis of AD yielded a median CL result of 87.7 (IQR ± 42.2) with 94% > 45 CL. Positive visual read agreed highly with results > 26 CL.ConclusionsCentiloid values < 10 accurately reflected the absence of any neuritic plaque and > 20 CL indicated the presence of at least moderate plaque density, but approximately 50 CL or more best confirmed both neuropathological and clinicopathological diagnosis of Alzheimer's disease.
| S-EPMC7057642 | biostudies-literature
Project description:ObjectiveIntratumoral heterogeneity is associated with poor outcomes in head and neck cancer (HNC) patients owing to chemoradiotherapy resistance. [18 F]-FDG positron emission tomography (PET) / Magnetic Resonance Imaging (MRI) provides spatial information about tumor mass, allowing intratumor heterogeneity assessment through histogram analysis. However, variability in quantitative PET/MRI parameter measurements could influence their reliability in assessing patient prognosis. Therefore, to use standardized uptake value (SUV) and apparent diffusion coefficient (ADC) parameters for assessing tumor response, this study aimed to measure SUV and ADC's variability and assess their relationship in HNC.MethodsFirst, ADC variability was measured in an in-house diffusion phantom and in five healthy volunteers. The SUV variability was only measured with the NEMA phantom using a clinical imaging protocol. Furthermore, simultaneous PET/MRI data of 11 HNC patients were retrospectively collected from the National Cyclotron and PET center in Chulabhorn Hospital. Tumor contours were manually drawn from PET images by an experienced nuclear medicine radiologist before tumor volume segmentation. Next, SUV and ADC's histogram were used to extract statistic variables of ADC and SUV: mean, median, min, max, skewness, kurtosis, and 5th , 10th , 25th , 50th , 75th , 90th , and 95th percentiles. Finally, the correlation between the statistic variables of ADC and SUV, as well as Metabolic Tumor volume and Total Lesion Glycolysis parameters was assessed using Pearson's correlation.ResultsThis pilot study showed that both parameters' maximum coefficient of variation was 13.9% and 9.8% in the phantom and in vivo, respectively. Furthermore, we found a strong and negative correlation between SUVmax and ADVmed (r = -0.75, P = 0.01).ConclusionThe SUV and ADC obtained by simultaneous PET/MRI can be potentially used as an imaging biomarker for assessing intratumoral heterogeneity in patients with HNC. The low variability and relationship between SUV and ADC could allow multimodal prediction of tumor response in future studies.
| S-EPMC10161023 | biostudies-literature
Project description:Background and purposeThe advantage of combined PET-MRI over sequential PET and MRI is the high spatial conformity and the absence of time delay between the examinations. The benefit of this technique for planning of re-irradiation (re-RT) treatment is unkown yet. Imaging data from a phase 1 trial of re-RT for recurrent glioma was analysed to assess whether planning target volumes and treatment margins in glioma re-RT can be adjusted by PET-MRI with rater independent PET based biological tumour volumes (BTVs).Patients and methodsCombined PET-MRI with the tracer O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) prior to re-RT was performed in recurrent glioma patients in a phase I trial. GTVs including all regions suspicious of tumour on contrast enhanced MRI were delineated by three experienced radiation oncologists and included into MRI based consensus GTVs (MRGTVs). BTVs were semi-automatically delineated with a fixed threshold of 1.6 x background activity. Corresponding BTVs and MRGTVs were fused into union volume PET-MRGTVs. The Sørensen-Dice coefficient and the conformity index were used to assess the geometric overlap of the BTVs with the MRGTVs. A recurrence pattern analysis was performed based on the original planning target volumes (PTVs = GTV + 10 mm margin or 5 mm in one case) and the PET-MRGTVs with margins of 10, 8, 5 and 3 mm.ResultsSeven recurrent glioma patients, who received PET-MRI prior to re-RT, were included into the present planning study. At the time of re-RT, patients were in median 54 years old and had a median Karnofsky Performance Status (KPS) score of 80. Median post-recurrence survival after the beginning of re-RT was 13 months. Concomitant bevacizumab therapy was applied in six patients and one patient received chemoradiation with temozolomide. Median GTV volumes of the three radiation oncologists were 35.0, 37.5 and 40.5 cubic centimeters (cc) and median MRGTV volume 41.8 cc. Median BTV volume was 36.6 cc and median PET-MRGTV volume 59.3 cc. The median Sørensen-Dice coefficient for the comparison between MRGTV and BTV was 0.61 and the median conformity index 0.44. Recurrence pattern analysis revealed two central, two in-field and one distant recurrence within both, the original PTV, as well as the PET-MRGTV with a reduced margin of 3 mm.ConclusionPET-MRI provides radiation treatment planning imaging with high spatial and timely conformity for high-grade glioma patients treated with re-RT with potential advancements for target volume delineation. Prospective randomised trials are warranted to further investigate the treatment benefits of PET-MRI based re-RT planning.
| S-EPMC6655559 | biostudies-literature
Project description:PurposeTo develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy.Material and methodsConsecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI).Results195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features.ConclusionWhole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation.
| S-EPMC10264289 | biostudies-literature