Baseline 18F-fluorodeoxyglucose Positron Emission Research Articles

Retrosplenial hypometabolism precedes the conversion from mild cognitive impairment to Alzheimer's disease.

Not all individuals who experience mild cognitive impairment (MCI) transition through progressive stages of cognitive decline at the same rate, if at all. Previous observational studies have identified the retrosplenial cortex (RSC) as an early site of hypometabolism in MCI which seems to be predictive of later transition to Alzheimer's disease (AD). We examined N=399 MCI subjects with baseline 18F-fluorodeoxyglucose positron emission tomography. Subjects were classified based on whether their diagnosis converted from MCI to AD. Whole-brain metabolism was decreased in converters (MCI-AD). This effect was more prominent at the RSC, where MCI-AD subjects showed even greater hypometabolism. Observations of RSC hypometabolism and its utility in predicting transition from MCI-AD withstood statistical analyses in a large retrospective study. These results point to the utility of incorporating RSC hypometabolism into predictive models of AD progression risk and call for further examination of mechanisms underlying this relationship. Not all individuals who develop MCI will progress to AD. Individuals with MCI who progress to AD show early whole-brain hypometabolism. Early hypometabolism is particularly prominent at the RSC.

Baseline 18F-FDG PET Radiomics Predicting Therapeutic Efficacy of Diffuse Large B-Cell Lymphoma after R-CHOP (-Like) Therapy.

Objective: This study aimed to predict therapeutic efficacy among diffuse large B-cell lymphoma (DLBCL) after R-CHOP (-like) therapy using baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) radiomics. Methods: A total of 239 patients with DLBCL were enrolled in this study, with 82 patients having refractory/relapsed disease. The radiomics signatures were developed using a stacking ensemble approach. The efficacy of the radiomics signatures, the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI), conventional PET parameters model, and their combinations in assessing refractory/relapse risk were evaluated using receiver operating characteristic (ROC) curves, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and decision curve analysis. Results: The stacking model, along with the integrated model that combines stacking with the NCCN-IPI and SDmax (the distance between the two lesions farthest apart, normalized to the patient's body surface area), showed remarkable predictive capabilities with a high area under the curve (AUC), sensitivity, specificity, PPV, NPV, accuracy, and significant net benefit of the AUC (NB-AUC). Although no significant differences were observed between the combined and stacking models in terms of the AUC in either the training cohort (AUC: 0.992 vs. 0.985, p = 0.139) or the testing cohort (AUC: 0.768 vs. 0.781, p = 0.668), the integrated model exhibited higher values for sensitivity, PPV, NPV, accuracy, and NB-AUC than the stacking model. Conclusion: Baseline PET radiomics could predict therapeutic efficacy in DLBCL after R-CHOP (-like) therapy, with improved predictive performance when incorporating clinical features and SDmax.

Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation

Objective. Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and prone to inter- and intra-observer variability. Automatic contouring by convolutional neural networks (CNN) can be fast and consistent but may produce unrealistic contours or miss relevant structures. We evaluate approaches for increasing the quality and assessing the uncertainty of CNN-generated contours of head and neck cancers with PET/CT as input. Approach. Two patient cohorts with head and neck squamous cell carcinoma and baseline 18F-fluorodeoxyglucose positron emission tomography and computed tomography images (FDG-PET/CT) were collected retrospectively from two centers. The union of manual contours of the gross primary tumor and involved nodes was used to train CNN models for generating automatic contours. The impact of image preprocessing, image augmentation, transfer learning and CNN complexity, architecture, and dimension (2D or 3D) on model performance and generalizability across centers was evaluated. A Monte Carlo dropout technique was used to quantify and visualize the uncertainty of the automatic contours. Main results. CNN models provided contours with good overlap with the manually contoured ground truth (median Dice Similarity Coefficient: 0.75–0.77), consistent with reported inter-observer variations and previous auto-contouring studies. Image augmentation and model dimension, rather than model complexity, architecture, or advanced image preprocessing, had the largest impact on model performance and cross-center generalizability. Transfer learning on a limited number of patients from a separate center increased model generalizability without decreasing model performance on the original training cohort. High model uncertainty was associated with false positive and false negative voxels as well as low Dice coefficients. Significance. High quality automatic contours can be obtained using deep learning architectures that are not overly complex. Uncertainty estimation of the predicted contours shows potential for highlighting regions of the contour requiring manual revision or flagging segmentations requiring manual inspection and intervention.

Elevated splenic 18F-fluorodeoxyglucose positron emission tomography/computed tomography activity is associated with 5-year risk of recurrence in non-metastatic invasive ductal carcinoma of the breast.

To construct prediction models including baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters of tumoural lesions and non-tumour lymphoid tissue for recurrence-free survival within 5 years (5y-RFS) after imaging examination in patients with invasive ductal carcinomas (IDCs) of the breast. The study included 101 consecutive female patients. Univariable and multivariable Cox regression were used to identify clinicopathological and metabolic parameters associated with risk of recurrence. Four prediction models based on the results of multivariable analysis were constructed and visualized as nomograms. Performance of each nomogram was evaluated using the concordance index (C-index), integrated discrimination improvement, decision curve analysis (DCA), and calibration curve. N3 status, total metabolic tumour volume, the maximum standardized uptake value of spleen, and spleen-to-liver ratio were significant predictors of 5y-RFS. The nomogram including all significant predictors demonstrated superior predictive performance for 5y-RFS, with a C-index of 0.907 (95% CI, 0.833-0.981), greatest net benefit on DCA, good accuracy on calibration curves, and excellent risk stratification on Kaplan-Meier curves. The model that included metabolic parameters of the spleen had the best performance for predicting 5y-RFS in patients with IDCs of the breast. This model may guide personalized treatment decisions and inform patients and clinicians about prognosis. This research identifies 18F-FDG PET/CT metabolic parameters of non-tumour lymphoid tissue as predictors of recurrence in breast cancer.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma

BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL.ResultsA total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell’s concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403).ConclusionsRadiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

The baseline metabolism parameters of 18F‑FDG PET/CT as promising prognostic biomarkers in pediatric Langerhans cell histiocytosis.

Langerhans cell histiocytosis (LCH) is a rare myeloid precursor cell inflammatory neoplasia, which agonizes, maims, and even kills patients. Although clinical outcomes have steadily improved over the past decades, the progression/relapse rate of LCH remains high. The purpose of this study was to evaluate the prognostic value of the pre-treatment metabolism parameters of baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F‑FDG PET/CT) in children with LCH. This cross-sectional study retrospectively and consecutively included 37 children (24 males and 13 females; median age, 5.1 years; range, 2.4-7.8 years) with pre-treatment 18F-FDG PET/CT from September 2020 to September 2022 in Nuclear Medicine Department, Beijing friendship hospital, Capital Medical University, Beijing, China. These patients were then all admitted to the hospital and diagnosed with LCH by biopsy, in Hematology Center, Beijing Children's Hospital, Capital Medical University, Beijing, China. Five metabolism parameters of 18F-FDG PET/CT were analyzed, including maximum standardized uptake, tumor-to-normal liver standard uptake value ratio, tumor-to-normal bone marrow standard uptake value ratio, sum of metabolic tumor volume (sMTV), and sum of total lesion glycolysis (sTLG) of all lesions. Patients were followed up for at least 1 year or until disease progression/relapse. Univariate and multivariate analyses of progression-free survival was performed. During follow-up, 11 (29.7%) patients had disease progression/relapse. Univariate analysis revealed that the risk organ involvement, the treatment response at the 5th or 11th week, pre-treatment sMTV, and sTLG were significantly associated with progression-free survival (P=0.024, 0.018, 0.006, 0.006, and 0.042, respectively). Multivariate COX analysis revealed that non-response at the 11th week, pre-treatment sMTV >32.55 g/cm3, and sTLG >98.86 g (P=0.002, 0.020, 0.026, respectively) were risk factors for progression-free survival. The baseline metabolism parameters of 18F-FDG PET/CT could be promising imaging biomarkers for predicting prognosis in children with LCH.

Prediction of pathological response after neoadjuvant chemotherapy using baseline FDG PET heterogeneity features in breast cancer

Complete pathological response to neoadjuvant systemic treatment (NAST) in some subtypes of breast cancer (BC) has been used as a surrogate of long-term outcome. The possibility of predicting BC pathological response to NAST based on the baseline 18F-Fluorodeoxyglucose positron emission tomography (FDG PET), without the need of an interim study, is a focus of recent discussion. This review summarises the characteristics and results of the available studies regarding the potential impact of heterogeneity features of the primary tumour burden on baseline FDG PET in predicting pathological response to NAST in BC patients. Literature search was conducted on PubMed database and relevant data from each selected study were collected. A total of 13 studies were eligible for inclusion, all of them published over the last 5 years. Eight out of 13 analysed studies indicated an association between FDG PET-based tumour uptake heterogeneity features and prediction of response to NAST. When features associated with predicting response to NAST were derived, these varied between studies. Therefore, definitive reproducible findings across series were difficult to establish. This lack of consensus may reflect the heterogeneity and low number of included series. The clinical relevance of this topic justifies further investigation about the predictive role of baseline FDG PET.

Effect of steroid treatment on the diagnostic yield of baseline 18f-fluorodeoxyglucose positron emission tomography in aggressive B cell lymphoma

Aggressive B cell lymphoma often requires prompt steroid treatment, even before baseline 18f-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and definitive treatment, to alleviate symptoms or prevent organ damage. Since lymphoma is a steroid-sensitive malignancy, there are concerns that steroids might affect the results of FDG PET/CT and decrease its diagnostic yield. The aim of the current study was to evaluate the effect of steroids administered before baseline PET/CT on the maximum standardized uptake value (SUVmax) and additional PET/CT parameters. Retrospective review of the database in a tertiary medical center yielded 178 patients newly diagnosed with aggressive B cell lymphoma between January 2017 and May 2020 who had an available baseline FDG PET/CT scan. The cohort was divided into patients who received steroids before PET/CT (n = 47) and those who did not (n = 131), and the groups were compared for SUVmax and additional PET/CT parameters. The steroid-treated group had a higher disease stage and lactate dehydrogenase level compared to the steroid-naïve group, with a trend toward a higher international prognostic index. There was no significant between-group difference in SUVmax (P = 0.61). This finding remained consistent across steroid treatment durations and dosage regimens. Further evaluation revealed a significantly larger mean tumor volume and a trend toward a higher tumor metabolic burden in the steroid-treated group, yet no between-group difference in SUV mean or other PET/CT parameters. In this retrospective analysis of patients with aggressive B cell lymphoma, steroid prophase prior to baseline PET/CT did not decrease the diagnostic yield of the scan. However, further studies are required to fully appreciate the impact of steroids on PET CT parameters.

Predictive value of metabolic parameters of baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography for survival rates of children with lymphoma (a metaanalysis and literature review)

The five-year overall survival (OS) rate for pediatric Hodgkin's (HL) and non-Hodgkin's (NHL) lymphomas remains at 85–95% despite improvements in therapy regimens. The problem of establishing reliable prognostic factors that could help identify high- or ultra-high-risk patients is still unresolved. We performed a systematic literature review and meta-analysis of studies investigating the predictive value of baseline metabolic parameters of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in pediatric patients with lymphomas. We systematically searched the following databases: PubMed, Medline, Cochrane Library and Google Scholar. Six retrospective studies (309 patients) evaluating the effect of quantitative parameters derived from baseline PET/CT with 18F-FDG (maximum standardized uptake value (SUVmax), tumor metabolic volume (MTV), and total lesion glycolysis (TLG)) on OS and event-free survival (EFS) in children with HL and NHL were included in our analysis. We used the Cochrane ROBINS-I tool to assess the quality of studies; the relative risks (RR) for the studied outcomes were calculated with RevMan software, version 5.3. The overall analysis showed that high MTV was associated with a six-fold increase in the relative mortality risk (RR 6.18 (3.15–12.11), p < 0.001) and a more than 5-fold increase in the risk of relapse/progression (RR 5.68 (3.21–10.07), p < 0.001). High values of TLG were associated with an eight-fold increase in the risk of mortality (RR 8.06 (3.35–19.39), p < 0.001) and worse EFS (RR 5.75 (2.99–11.06), p < 0.001). Our results will enable oncologists to expand existing risk assessment systems and improve their predictive effectiveness by using MTV and TLG parameters.

Axillary lymph nodes on PET in Hodgkin lymphoma after COVID-19 vaccination.

A 21-year-old woman presented with nodular sclerosis Hodgkin lymphoma stage IIIA, IPS 2 with a baseline 18F-fluorodeoxyglucose positron emission tomography and computed tomography (FDG PET/CT) showing initial involved lymph nodes in both sides of the neck, left axilla, mediastinum, hili, para-aortic, left iliac, and involvement of the spleen. After one course of BrAVD (brentuximab-vedotin, adriamycine, vinblastine, dacarbazine), the interim FDG PET/CT scan was negative, classified as a complete metabolic response. A third FDG PET/CT scan was performed after completion of her chemotherapy consisting of six courses of BrAVD. This scan showed a reappearance of FDG avid lymph nodes, with a Deauville score of 5, in the original sites in the left axilla and neck. The most FDG avid lymph node was excised and revealed florid follicular hyperplasia instead of recurrence of Hodgkin lymphoma. In hindsight, she received a COVID-19 vaccination in her left arm several weeks prior to the last FDG PET/CT scan. In the meantime, various articles were published that relate the occurrence of FDG avid ipsilateral axillary and neck lymph nodes to COVID-19 vaccination of several manufacturers. We, therefore, concluded all FDG avid lymph nodes to be triggered by the vaccination. FDG PET/CT scan is valuable in steering therapy in Hodgkin lymphoma patients. However, enhanced FDG uptake only indicates that enhanced glucose metabolism and false positive results are possible, necessitating good clinical correlation. Documentation of the vaccination status including date(s), side, and manufacturer is of importance. In cancer patients, the side and timing of the vaccination should be discussed with the patient to prevent concern of recurrence and avoid unnecessary diagnostics and as in our case.

Assessing immune organs on 18F-FDG PET/CT imaging for therapy monitoring of immune checkpoint inhibitors: inter-observer variability, prognostic value and evolution during the treatment course of melanoma patients.

Immune checkpoint inhibitors (ICIs) have significantly improved survival in advanced melanoma. There is a need for robust biomarkers to identify patients who do not respond. We analysed 14 baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metrics and their evolution to assess their correlation with patient outcome, compared with 7 established biological markers and 7 clinical variables. We conducted a retrospective monocentric observational study of 29 patients with advanced melanoma who underwent baseline 18F-FDG PET/CT, followed by an early monitoring PET/CT (iPET) scan after 1 month of treatment and follow-up studies at 3rd (M3PET) and 6th month (M6PET). 18F-FDG uptake in immune organs (spleen, bone marrow, ileocecal valve) and derived spleen-to-liver (SLR) and bone-to-liver (BLR) ratios were reviewed by two PET readers for reproducibility analysis purposes including 14 PET variables. The most reproducible indexes were used for evaluation as predictors of overall survival (OS) in comparison with PET response using imPERCIST5, whole-body metabolic active tumour volume (WB-MATV) and biological parameters (lactate dehydrogenases (LDH), reactive protein c (CRP), white blood count (WBC), absolute lymphocyte count (ALC), neutrophil to lymphocyte ratio (NLR) and derived neutrophils to lymphocyte ratio). Strong reproducibility's (intraclass coefficients of correlation (ICC) > 0.90) were observed for spleen anterior SUVpeak, spleen MV, spleen TLG, spleen length and BLRmean. ICC for SLRmean and ileocecal SUVmean were 0.86 and 0.65, respectively. In the 1-year OS 1 group, SLRmean tended to increase at each time point to reach a significant difference at M6-PET (p = 0.019). The same trends were observed with spleen SUVpeak anterior and spleen length. In the 1-year OS 0 group, a significative increase of spleen length was found at iPET, as compared with baseline PET (p = 0.014) and M3-PET (p = 0.0239). Univariable Kaplan-Meier survival analysis found that i%var spleen length, M3%var SLRmean, baseline LDH, i%var NLR and response at M6PET were all predictors of 1-year OS. SLRmean is recommended as a prognosticator in melanoma patients under immunotherapy: its increase greater than 25% at 3 months, compared with baseline, was associated with poor outcome after ICIs.

Prognostic Values of Baseline 18F-FDG PET/CT in Patients with Peripheral T-Cell Lymphoma.

Purpose In the present study, we aimed to investigate whether the metabolic parameters on baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) could be used to predict prognosis in peripheral T-cell lymphomas (PTCL). Methods A total of 51 nodal PTCL patients who underwent baseline 18F-FDG PET/CT were retrospectively evaluated in the present study. Total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) were also assessed. Besides, the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) was also included. Log-rank test and Cox regression analysis were used to evaluate progression-free survival (PFS) and overall survival (OS). Results The median follow-up was 18 months. Patients with low TLG, TMTV, and SUVmax levels had a significantly better clinical outcome than those with high TLG, TMTV, and SUVmax levels. The 2-year PFS rates of the high- and low-TMTV groups were 34.62% and 80%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, Conclusions Baseline TMTV and TLG were independent predictors of PFS and OS in PTCL patients, and SUVmax and NCCN-IPI scores were also independent predictors of OS. Moreover, the combination of TMTV and NCCN-IPI scores improved patient risk-stratification at the initial stage and might contribute to the adjustment of the therapeutic regime. This trial is registered with ChiCTR1900025526.

Maximum standardized uptake value at pre-treatment PET in estimating lung cancer progression after stereotactic body radiotherapy.

PurposeThis study aimed to identify the feasibility of the maximum standardized uptake value (SUVmax) on baseline 18F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) as a predictive factor for prognosis in early stage primary lung cancer treated with stereotactic body radiotherapy (SBRT).Materials and MethodsTwenty-seven T1-3N0M0 primary lung cancer patients treated with curative SBRT between 2010 and 2018 were retrospectively evaluated. Four patients (14.8%) treated with SBRT to address residual tumor after wedge resection and one patient (3.7%) with local recurrence after resection were included. The SUVmax at baseline PET/CT was assessed to determine its relationship with prognosis after SBRT. Patients were divided into two groups based on maximum SUVmax on pre-treatment FDG PET/CT, estimated by receiver operating characteristic curve.ResultsThe median follow-up period was 17.7 months (range, 2.3 to 60.0 months). The actuarial 2-year local control, progressionfree survival (PFS), and overall survival were 80.4%, 66.0%, and 78.2%, respectively. With regard to failure patterns, 5 patients exhibited local failure (in-field failure, 18.5%), 1 (3.7%) experienced regional nodal relapse, and other 2 (7.4%) developed distant failure. SUVmax was significantly correlated with progression (p = 0.08, optimal cut-off point SUVmax > 5.1). PFS was significantly influenced by pretreatment SUVmax (SUVmax > 5.1 vs. SUVmax ≤ 5.1; p = 0.012) and T stage (T1 vs. T2-3; p = 0.012).ConclusionSUVmax at pre-treatment FDG PET/CT demonstrated a predictive value for PFS after SBRT for lung cancer.

Total metabolic tumor volume, circulating tumor cells, cell-free DNA: distinct prognostic value in follicular lymphoma

AbstractOutcomes for follicular lymphoma (FL) have greatly improved, but most patients will ultimately relapse. High total metabolic tumor volume (TMTV), computed from baseline 18F-fluorodeoxyglucose–positron emission tomography (PET), is associated with shorter progression-free survival (PFS), but circulating tumor cells (CTCs) and cell-free DNA (cfDNA) may also reflect tumor burden and be of prognostic value. The aim of our study was to correlate CTCs and cfDNA with TMTV in FL at diagnosis and to determine their prognostic values. We retrospectively analyzed 133 patients (with previously untreated FL and a baseline PET) from 2 cohorts with either a baseline plasma sample (n = 61) or a bcl2-JH-informative peripheral blood (PB) sample (n = 68). Quantification of circulating bcl2-JH+ cells and cfDNA was performed by droplet digital polymerase chain reaction. A significant correlation was found between TMTV and both CTCs (P < .0001) and cfDNA (P < .0001). With a median 48-month follow-up, 4-year PFS was lower in patients with TMTV > 510 cm3 (P = .0004), CTCs >0.0018 PB cells (P = .03), or cfDNA >2550 equivalent-genome/mL (P = .04). In comparison with TMTV alone, no additional prognostic information was obtained by measuring CTCs. In contrast, Cox multivariate analysis, including cfDNA and TMTV, showed that both cfDNA and TMTV remained predictive of outcome. In conclusion, CTCs and cfDNA correlate with TMTV in FL, and all 3 influence patient outcome. PFS was shorter for patients with high cfDNA and TMTV, suggesting that these parameters provide relevant information for tumor-tailored therapy.

Metabolic correlates of reserve and resilience in MCI due to Alzheimer's Disease (AD)

BackgroundWe explored the presence of both reserve and resilience in late-converter mild cognitive impairment due to Alzheimer’s disease (MCI-AD) and in patients with slowly progressing amyloid-positive MCI by assessing the topography and extent of neurodegeneration with respect to both “aggressive” and typically progressing phenotypes and in the whole group of patients with MCI, grounding the stratification on education level.MethodsWe analyzed 94 patients with MCI-AD followed until conversion to dementia and 39 patients with MCI who had brain amyloidosis (AMY+ MCI), all with available baseline 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) results. Using a data-driven approach based on conversion time, patients with MCI-AD were divided into typical AD and late-converter subgroups. Similarly, on the basis of annual rate of Mini Mental State Examination score reduction, AMY+ MCI group was divided, obtaining smoldering (first tertile) and aggressive (third tertile) subgroups. Finally, we divided the whole group (MCI-AD and AMY+ MCI) according to years of schooling, obtaining four subgroups: poorly educated (Low-EDUC; first quartile), patients with average education (Average-EDUC; second quartile), highly educated (High-EDUC; third quartile), and exceptionally educated (Except-EDUC; fourth quartile). FDG-PET of typical AD, late converters, and aggressive and smoldering AMY+ MCI subgroups, as well as education level-based subgroups, were compared with healthy volunteer control subjects (CTR) and within each group using a two-samples t test design (SPM8; p < 0.05 family-wise error-corrected).ResultsLate converters were characterized by relatively preserved metabolism in the right middle temporal gyrus (Brodmann area [BA] 21) and in the left orbitofrontal cortex (BA 47) with respect to typical AD. When compared with CTR, the High-EDUC subgroup demonstrated a more extended bilateral hypometabolism in the posterior parietal cortex, posterior cingulate cortex, and precuneus than the Low- and Average-EDUC subgroups expressing the same level of cognitive impairment. The Except-EDUC subgroup showed a cluster of significant hypometabolism including only the left posterior parietal cortex (larger than the Low- and Average-EDUC subgroups but not further extended with respect to the High-EDUC subgroup).ConclusionsMiddle and inferior temporal gyri may represent sites of resilience rather than a hallmark of a more aggressive pattern (when hypometabolic). These findings thus support the existence of a relatively homogeneous AD progression pattern of hypometabolism despite AD heterogeneity and interference of cognitive reserve. In fact, cortical regions whose “metabolic resistance” was associated with slower clinical progression had different localization with respect to the regions affected by education-related reserve.

Development of a radiomic signature for prediction of pathological complete response following neoadjuvant chemoradiotherapy in esophageal cancer.

106 Background: Pivotal to personalized therapy is accurate pre-treatment patient selection based on predictive biomarkers. We developed a radiomic signature model to predict pathological complete response (pCR) following neoadjuvant chemo-radiotherapy (NACRT) in esophageal cancers. Methods: We retrospectively identified 68 patients with esophageal cancer, treated with NACRT followed by esophagectomy, with baseline 18F-fluorodeoxyglucose Positron Emission Tomography (PET) and computed tomography (CT) scans performed at our institution. In-house data-characterization algorithm was used to extract 3D radiomics features from the segmented primary disease. Prediction models were constructed and internally validated (2/3rd training, 1/3rd validation) using machine learning software. Cox regression hazard used to assess association with relapse free survival (RFS). Results: pCR was observed in 34 (50%) patients. A total of 126 features were extracted individually from PET and CT scans. On univariate analysis, 16 PET and 14 CT features were found to independently predict pCR. Three separate predictive models were built for CT, PET and combined CT+PET. Individually, both CT and PET had a good predictive power with AUC 0.74 and 0.730, respectively. Combined CT+PET radiomic features resulted in a significant improvement of predicting power, with AUC 0.856. Good discrimination (82.6%) was observed in validation dataset. Final model was: 13.439-34.632(CT-eccentricity)-2.469(CT-LRLGE)+10.626(CT-Gnorm_HIE)-2.094(CT-SD_Lac2)-19.337(CT-FD_SD)-0.344(PET-Contrast), where eccentricity is shape feature, LRLGE a gray level run length feature, Gnorm_HIE gray-level size zone feature, SD_Lac2 a fractal dimension feature. Stratifying patients with low vs. high radiomic signature score predicted RFS: median RFS 80.1 vs. 40.1 months; and 2-year RFS 77.4% vs. 52.6% [Hazard Ratio: 2.24, 95% CI 1.01-5.58], respectively. Conclusions: The developed radiomics signature models were highly predictive of pCR following NACRT. Further validation in larger data sets is needed to determine whether the model can predict clinical outcomes.

Reclassifying patients with early-stage Hodgkin lymphoma based on functional radiographic markers at presentation

The presence of bulky disease in Hodgkin lymphoma (HL), traditionally defined with a 1-dimensional measurement, can change a patient's risk grouping and thus the treatment approach. We hypothesized that 3-dimensional measurements of disease burden obtained from baseline 18F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) scans, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), would more accurately risk-stratify patients. To test this hypothesis, we reviewed pretreatment PET-CT scans of patients with stage I-II HL treated at our institution between 2003 and 2013. Disease was delineated on prechemotherapy PET-CT scans by 2 methods: (1) manual contouring and (2) subthresholding of these contours to give the tumor volume with standardized uptake value ≥2.5. MTV and TLG were extracted from the threshold volumes (MTVt, TLGt) and from the manually contoured soft-tissue volumes. At a median follow-up of 4.96 years for the 267 patients evaluated, 27 patients were diagnosed with relapsed or refractory disease and 12 died. Both MTVt and TLGt were highly correlated with freedom from progression and were dichotomized with 80th percentile cutoff values of 268 and 1703, respectively. Consideration of MTV and TLG enabled restratification of early unfavorable HL patients as having low- and high-risk disease. We conclude that MTV and TLG provide a potential measure of tumor burden to aid in risk stratification of early unfavorable HL patients.

Prognostic value of total lesion glycolysis of baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography in diffuse large B-cell lymphoma.

PurposeWe evaluated the prognostic value of total lesion glycolysis (TLG) measured in baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in diffuse large B-cell lymphoma (DLBCL) treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP).MethodsA total of 91 patients with newly diagnosed DLBCL underwent 18F-FDG PET/CT scans before R-CHOP therapy. Metabolic tumor volume (MTV) was measured with the marginal threshold of normal liver mean standard uptake value (SUVmean) plus 3 standard deviations (SD). TLG was the sum of the products of MTV and SUVmean in all measured lesions. The predictive value was estimated by Log-rank test and Cox-regression analysis.ResultsMedian follow-up was 30 months (range, 5-124 months). The 5-year estimated progression-free survival (PFS) of the low and high TLG group were 83% and 34%, respectively (p<0.001). The 5-year overall survival (OS) of the same groups were 92% and 67%, respectively (p<0.001). Patients with high TLG level were more likely to relapse than those with low TLG level even though they had got complete or partial remission in R-CHOP therapy (40% versus 9%, p=0.012). Multivariate analysis revealed TLG was the only independent predictor for PFS (Hazard ratio=5.211, 95% confidence interval=2.210-12.288, p<0.001) and OS (Hazard ratio=9.136, 95% confidence interval=1.829-45.644, p=0.002). Other factors including MTV, National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) and Ann Arbor Stage were not independently predictive for survivals.ConclusionBaseline TLG is the only independent predictor for PFS and OS in DLBCL patients treated with R-CHOP therapy.

Residual vectors for Alzheimer disease diagnosis and prognostication

Alzheimer disease (AD) is an increasingly prevalent neurodegenerative condition and a looming socioeconomic threat. A biomarker for the disease could make the process of diagnosis easier and more accurate, and accelerate drug discovery. The current work describes a method for scoring brain images that is inspired by fundamental principles from information retrieval (IR), a branch of computer science that includes the development of Internet search engines. For this research, a dataset of 254 baseline 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) scans was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For a given contrast, a subset of scans (nine of every 10) was used to compute a residual vector that typified the difference, at each voxel, between the two groups being contrasted. Scans that were not used for computing the residual vector (the remaining one of 10 scans) were then compared to the residual vector using a cosine similarity metric. This process was repeated sequentially, each time generating cosine similarity scores on 10% of the FDG-PET scans for each contrast. Statistical analysis revealed that the scores were significant predictors of functional decline as measured by the Functional Activities Questionnaire (FAQ). When logistic regression models that incorporated these scores were evaluated with leave-one-out cross-validation, cognitively normal controls were discerned from AD with sensitivity and specificity of 94.4% and 84.8%, respectively. Patients who converted from mild cognitive impairment (MCI) to AD were discerned from MCI nonconverters with sensitivity and specificity of 89.7% and 62.9%, respectively, when FAQ scores were brought into the model. Residual vectors are easy to compute and provide a simple method for scoring the similarity between an FDG-PET scan and sets of examples from a given diagnostic group. The method is readily generalizable to any imaging modality. Further interdisciplinary work between IR and clinical neuroscience is warranted.