Dataset Information

Hybrid 18F-FDG-PET/MRI Measurement of Standardized Uptake Value Coupled with Yin Yang 1 Signature in Metastatic Breast Cancer. A Preliminary Study.

ABSTRACT: PURPOSE:Detection of breast cancer (BC) metastasis at the early stage is important for the assessment of BC progression status. Image analysis represents a valuable tool for the management of oncological patients. Our preliminary study combined imaging parameters from hybrid 18F-FDG-PET/MRI and the expression level of the transcriptional factor Yin Yang 1 (YY1) for the detection of early metastases. METHODS:The study enrolled suspected n = 217 BC patients that underwent 18F-FDG-PET/MRI scans. The analysis retrospectively included n = 55 subjects. n = 40 were BC patients and n = 15 imaging-negative female individuals were healthy subjects (HS). Standard radiomics parameters were extracted from PET/MRI image. RNA was obtained from peripheral blood mononuclear cells and YY1 expression level was evaluated by real time reverse transcription polymerase chain reactions (qRT-PCR). An enzyme-linked immuosorbent assay (ELISA) was used to determine the amount of YY1 serum protein. Statistical comparison between subgroups was evaluated by Mann-Whitney U and Spearman's tests. RESULTS:Radiomics showed a significant positive correlation between Greg-level co-occurrence matrix (GLCM) and standardized uptake value maximum (SUVmax) (r = 0.8 and r = 0.8 respectively) in BC patients. YY1 level was significant overexpressed in estrogen receptor (ER)-positive/progesteron receptor-positive/human epidermal growth factor receptor2-negative (ER+/PR+/HER2-) subtype of BC patients with synchronous metastasis (SM) at primary diagnosis compared to metachronous metastasis (MM) and HS (p < 0.001) and correlating significantly with 18F-FDG-uptake parameter (SUVmax) (r = 0.48). CONCLUSIONS:The combination of functional 18F-FDG-PET/MRI parameters and molecular determination of YY1 could represent a novel integrated approach to predict synchronous metastatic disease with more accuracy than 18F-FDG-PET/MRI alone.

SUBMITTER: Schiano C

PROVIDER: S-EPMC6827137 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Hybrid <sup>18</sup>F-FDG-PET/MRI Measurement of Standardized Uptake Value Coupled with Yin Yang 1 Signature in Metastatic Breast Cancer. A Preliminary Study.

Schiano Concetta C Franzese Monica M Pane Katia K Garbino Nunzia N Soricelli Andrea A Salvatore Marco M de Nigris Filomena F Napoli Claudio C

Cancers 20190926 10

<h4>Purpose</h4>Detection of breast cancer (BC) metastasis at the early stage is important for the assessment of BC progression status. Image analysis represents a valuable tool for the management of oncological patients. Our preliminary study combined imaging parameters from hybrid <sup>18</sup>F-FDG-PET/MRI and the expression level of the transcriptional factor Yin Yang 1 (YY1) for the detection of early metastases.<h4>Methods</h4>The study enrolled suspected n = 217 BC patients that underwent ...[more]

PMID: 31561604

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Project description:PET imaging is useful for evaluating locally advanced primary breast cancer. Expression of specific molecular markers in these cancers, such as estrogen receptor (ER), progesterone receptor (PR), and HER2 status, has direct prognostic and therapeutic implications in patient management. This study aimed to determine whether a relationship exists between tumor glucose use and important molecular markers in invasive breast cancer. For our purposes, tumor glucose use is quantified by the PET-derived parameter maximum standardized uptake value (SUV).Breast tumors from 36 patients were excised and examined histologically after PET. ER, PR, and HER2 status were determined for all lesions histopathologically. In addition, genomewide expression for a subset of 20 tumors was analyzed using the human genome U133A oligonucleotide microarray.A significant association was found between estrogen ER status and lesion SUV. ER-negative tumors (n = 17; median SUV, 8.5) demonstrated a significantly higher maximum SUV than did ER-positive tumors (n = 19; median SUV, 4.0) (P < 0.001). No significant association existed between SUV and PR status, HER2/neu status, lymph node involvement, or tumor size. Unsupervised hierarchic clustering of the 20 genetically profiled cancers segregated tumor samples into 2 primary groups of 10 patients each, largely corresponding to ER status.In locally invasive primary breast cancer, ER-negative tumors display higher (18)F-FDG uptake than ER-positive tumors. Microarray analysis confirms these data and identifies genes associated with increased glucose use as measured by PET. These genes significantly overlap those of a previously validated ER-status molecular phenotype. These preliminary data support a growing body of evidence that ER-positive and ER-negative breast cancers have distinct disease-specific patterns. Further validation prospectively and with larger numbers will be required to establish a robust molecular signature for metabolic uptake and patterns of aggressive behavior in advanced breast cancer.

Project description:BackgroundAssessment of dual time point (DTP) positron emission tomography was carried out with the aim of a quantitative determination of Km, the metabolic uptake rate of [18F]fluorodeoxyglucose as a measure of glucose consumption.MethodsStarting from the Patlak equation, it is shown that Km?mt/ca0+V?r/?a, where mt is the secant slope of the tissue response function between the dual time point measurements centered at t?=?t0. ca0=ca(t0) denotes arterial tracer concentration, V?r is an estimate of the Patlak intercept, and ?a is the time constant of the ca(t) decrease. We compared the theoretical predictions with the observed relation between Ks=mt/ca0 and Km in a group of nine patients with liver metastases of colorectal cancer for which dynamic scans were available, and Km was derived from conventional Patlak analysis. Twenty-two lesion regions of interest (ROIs) were evaluated. ca(t) was determined from a three-dimensional ROI in the aorta. Furthermore, the correlation between Km and late standard uptake value (SUV) as well as retention index was investigated. Additionally, feasibility of the approach was demonstrated in a whole-body investigation.ResultsPatlak analysis yielded a mean Vr of V?r=0.53±0.08 ml/ml. The patient averaged ?a was 99?±?23 min. Linear regression between Patlak-derived Km and DTP-derived Ks according to Ks?=?b?·?Km?+?a yielded b?=?0.98?±?0.05 and a?=?-0.0054?±?0.0013 ml/min/ml (r?=?0.98) in full accordance with the theoretical predictions b?=?1 and a?-V?r/?a. Ks exhibits better correlation with Km than late SUV and retention index, respectively. Ks(c)=Ks+V?r/?a is proposed as a quantitative estimator of Km which is independent of patient weight, scan time, and scanner calibration.ConclusionQuantification of Km from dual time point measurements compatible with clinical routine is feasible. The proposed approach eliminates the issues of static SUV and conventional DTP imaging regarding influence of chosen scanning times and inter-study variability of the input function. Ks and Ks(c) exhibit improved stability and better correlation with the true Km. These properties might prove especially relevant in the context of radiation treatment planning and therapy response control.

Project description:This study assessed whether preoperative maximum standardized uptake value (SUVmax) of metastatic lymph nodes (LNs) measured by F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT) could improve the prediction of prognosis in gastric cancer.One hundred fifty-one patients with gastric cancer and pathologically confirmed LN involvement who had undergone preoperative F-FDG PET/CT prior to curative surgical resection were retrospectively enrolled. To obtain nodal SUVmax, a transaxial image representing the highest F-FDG uptake was carefully selected, and a region of interest was manually drawn on the highest F-FDG accumulating LN. Conventional prognostic parameters and PET findings (primary tumor and nodal SUVmax) were analyzed for prediction of recurrence-free survival (RFS) and overall survival (OS). Furthermore, prognostic accuracy of survival models was assessed using c-statistics.Of the 151 patients, 38 (25%) experienced recurrence and 34 (23%) died during follow-up (median follow-up, 48 months; range, 5-74 months). Twenty-seven patients (18%) showed positive F-FDG nodal uptake (range, 2.0-22.6). In these 27 patients, a receiver-operating characteristic curve demonstrated a nodal SUVmax of 2.8 to be the optimal cutoff for predicting RFS and OS. The univariate and multivariate analyses showed that nodal SUVmax (hazard ratio [HR]?= 2.71, P < 0.0001), pathologic N (pN) stage (HR = 2.58, P = 0.0058), and pathologic T (pT) stage (HR = 1.77, P = 0.0191) were independent prognostic factors for RFS. Also, nodal SUVmax (HR = 2.80, P < 0.0001) and pN stage (HR = 2.28, P = 0.0222) were independent prognostic factors for OS. A predictive survival model incorporating conventional risk factors (pT/pN stage) gave a c-statistic of 0.833 for RFS and 0.827 for OS, whereas a model combination of nodal SUVmax with pT/pN stage gave a c-statistic of 0.871 for RFS (P = 0.0355) and 0.877 for OS (P = 0.0313).Nodal SUVmax measured by preoperative F-FDG PET/CT is an independent prognostic factor for RFS and OS. Combining nodal SUVmax with pT/pN staging can improve survival prediction precision in patients with gastric cancer.

Project description:We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).

Project description:PurposeTo evaluate and compare the prognostic value of Epstein-Barr virus (EBV) DNA and maximal standard uptake values (SUVmax ) of 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG-PET) in subgroups of nasopharyngeal carcinoma (NPC) patients with locoregional or distant recurrence.Patients and methodsA total of 194 patients with recurrent NPC (locoregional recurrence: 107, distant recurrence: 87) were enrolled. Patients took evidence of recurrence performed with 18F-FDG-PET and an EBV DNA test before salvage treatment. Clinical parameters, the status of EBV DNA and the value of SUVmax were used for survival analysis using the Kaplan-Meier method and the Cox proportional hazards regression model.ResultsIn the subgroup of patients with locoregional recurrence, patients with SUVmax<8.65 had significantly better overall survival (OS) (P=0.005) compared with the patients with SUVmax ≥8.65. However, both elevated EBV DNA load (≥21,100 copies/ml) and distant SUVmax (≥13.55) were significantly associated with worse OS compared with the patients with EBV DNA <21,100 copies/ml or distant SUVmax <13.55 for the subgroup with distant recurrence (P=0.015 and P=0.006, respectively). The predictive ability of EBV DNA was superior to that of SUVmax (P=0.062). Multivariate analysis showed that SUVmax was only an independent prognostic factor for OS in patients with locoregional recurrence (P=0.042), whereas EBV DNA independently predicted OS for the patients with distant recurrence (P=0.007). For those patients with undetectable EBV DNA, SUVmax<8.65 was still an independent favorable prognostic factor (P=0.038).ConclusionsSUVmax is a useful biomarker for predicting OS in nasopharyngeal carcinoma patients with locoregional recurrence or with undetectable EBV DNA. Both distant SUVmax and EBV DNA appear to be independent predictors of OS in patients with distant recurrence; however, the predictive ability of EBV DNA was superior to that of SUVmax.

Dataset Information

Hybrid 18F-FDG-PET/MRI Measurement of Standardized Uptake Value Coupled with Yin Yang 1 Signature in Metastatic Breast Cancer. A Preliminary Study.

Publications

Hybrid <sup>18</sup>F-FDG-PET/MRI Measurement of Standardized Uptake Value Coupled with Yin Yang 1 Signature in Metastatic Breast Cancer. A Preliminary Study.

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