PET Parameters Research Articles

Relationship Between Metabolic Activity, Cellularity, Histopathological Features of Primary Tumors and Distant Metastatic Potential in Breast Cancer.

The aim of this study was to evaluate the relationship between the types of distant metastatic spread, histopathological features, and imaging features of primary tumor on positron emission tomography/magnetic resonance imaging (PET/MRI) for primary staging in newly diagnosed breast invasive ductal carcinoma (IDC) patients. Data from 289 female patients were retrospectively evaluated. Maximum standardized uptake value, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and minimum apparent diffusion coefficient (ADCmin) values of primary tumors were obtained from PET/MRI. The patients were grouped as non-metastatic, oligometastatic (1-5 metastatic lesions) and multimetastatic (>5 metastatic lesions) disease according to the number of distant metastases, and divided into two groups as isolated bone metastasis (IBM) and mixed/soft tissue metastasis (M-SM) groups according to the sites of metastatic spread. Metabolic parameters had higher values and ADCmin had lower values in the multimetastatic and oligometastatic groups than in the non-metastatic group. MTV was the only parameter that showed significant difference between the multimetastatic and oligometastatic groups. MTV and TLG were significantly higher in the M-SM group than in the IBM group. 18F-fluorodeoxyglucose PET parameters had significantly higher values in grade 3, hormone receptor negative, human epidermal growth factor receptor 2 positive, triple negative, and highly proliferative (Ki-67 ≥14%) tumors. The prediction models that included imaging parameters to predict the presence of distant metastasis had higher discriminatory powers than the prediction models that included only histopathological parameters. Primary tumors with higher metabolic-glycolytic activity and higher cellularity were more aggressive and had higher metastatic potential in breast IDC. Compared with histopathological parameters alone, the combination of imaging parameters and histopathological features of primary tumors may help to better understand tumor biology and behavior.

Prospective Trial of Using Imaging to Predict Pathologic Response and Clinical Outcomes in Locally Advanced Esophageal Cancer

Trimodality therapy with chemoradiation (CRT) followed by esophagectomy is the standard of care for locally advanced esophageal cancer. An unresolved question is whether pathologic complete response (pCR) can be assessed non-invasively for patients post-CRT. In this study, we assessed whether diffusion-weighted imaging (DWI) with MRI or PET can be used as predictors of pCR and other clinical outcomes after CRT. Patients were enrolled on a single-arm institutional trial (PA13-0380) assessing the role of imaging in predicting outcomes in potentially resectable esophageal patients undergoing trimodality therapy. All patients received neoadjuvant CRT, and 29 patients had subsequent surgery. DWI MRI and PET scans were obtained at baseline, 2 weeks after the start of CRT (interim) and 4 to 6 weeks after completion of CRT (follow up). Apparent diffusion coefficients (ADCs) were calculated based on DWI images. Circulating tumor DNA was obtained for 27 patients post-radiation using CAPP-Seq. Mann-Whitney tests compared imaging changes associated with pCR. Discrimination of pCR by imaging changes was quantified by received operating characteristics. Youden's index was applied to select optimal thresholds. Kaplan-Meier analysis was performed to assess differences in overall survival (OS) and progression-free survival (PFS) by changes in DWI, PET, and ctDNA parameters. Our cohort of 60 patients had a median follow up of 42.7 months, age of 65.4 yrs, and ECOG of 1 at completion of CRT. 90% were male, 58% had a history of smoking, and 85% were white. 83% had adenocarcinoma with the rest squamous cell carcinoma. Stages of the patients ranged from IIA to IIIB. All had moderately (47%) or poorly (53%) differentiated disease. All received 41.4-50.4 Gy in 1.8 Gy fractions with the majority receiving 50.4 Gy (95%). 29 patients underwent surgery after CRT of which 8 (27.6%) had pCR. Mean ΔADC from baseline to mid-treatment was most associated with pCR (AUC = 0.98, p<0.001) for patients undergoing surgery. Max ΔADC from baseline to first follow-up was most associated with OS (p = 0.002) and PFS (p<0.001) for the whole cohort. 27 patients had ctDNA analyzed after RT with the presence of ctDNA significantly associated with worse OS (HR = 0.12, p = 0.05) and PFS (HR = 0.10, p = 0.002). Combining ctDNA and max ΔADC generated a model that was more predictive of OS and PFS than either alone. We found that neither the PET parameters of TLG or SUV max at baseline or changes in these parameters from baseline to mid-treatment or first follow-up were as predictive as DWI. We show that changes in DWI is associated with pCR, OS, and PFS in resectable esophageal cancer patients undergoing CRT. DWI was more predictive than PET and a model combining DWI and ctDNA was the most predictive of clinical outcomes. This study shows the significant promise of using DWI in potentially guiding treatment decisions in esophageal cancer patients and will require validation in a larger cohort.

A Novel FDG PET and Mean Lung Dose Model to Identify Stage III NSCLC Patients at High Risk of Developing Early Radiation Pneumonitis

Early radiation pneumonitis (RPEarly) is a primary reason for the premature discontinuation of durvalumab consolidation and can lead to poor survival in patients with stage III non-small cell lung cancer (NSCLC). Currently, there are no RP risk models specifically tested for RPEarly. Here, we tested the applicability of published RP models for predicting RPEarly and explored the value of integrating pretreatment FDG-PET parameters. The cohort consisted of all 178 LA-NSCLC patients treated with concurrent chemoradiation (cCRT) and durvalumab between May 2017 and December 2021. RPEarly was defined as RP occurring within three months of cCRT completion; late RP (RPLate) was defined as any later occurring RP. The three published RP models analyzed included: 1) Mean lung dose (MLD), 2) MLD, age, pulmonary comorbidity, smoking status, and tumor location, and 3) MLD, age and pulmonary comorbidity. In addition, pretreatment FDG PET-CT scans were used to calculate SUV parameters from auto-segmented normal lung contours: 10th- and 90th percentile (SUVP10, SUVP90), maximum, mean (SUVmean), minimum, and standard deviation. The RP models were fit to RPEarly, RPLate, and RPEarly+Late in the 178 patients. To assess the association between FDG PET parameters and RP unbiasedly, the cohort was then randomly split, but enforcing similar RP rates, into a two-thirds derivation and a one-third validation subset. Model performance was assessed by AUC, p-values and the Hosmer-Lemeshow test (pHL; ideally ∼0.50). The rates of RPEarly, RPLate, and RPEarly+Late were 12%, 11%, and 23%, respectively (corresponding to 21, 20, and 41 events). Only the MLD model significantly predicted RPEarly (AUC = 0.70; p = 0.04; pHL = 0.84); none of the three models predicted RPLate or RPEarly+Late. Among the FDG PET parameters, SUVP10, SUVP90 and SUVmean predicted RPEarly with similar performance (AUC = 0.69-0.73; p = 0.005-0.01; pHL = 0.68-0.72), and, therefore, bivariate models were built between MLD and each of SUVP10, SUVP90 and SUVmean. Only the MLD + SUVP90 model generalized in the validation subset (AUC = 0.63; p = 0.03; pHL = 0.89) and was thus deemed the final model for RPEarly. A final re-fitting of all model coefficients to the whole cohort indicated improvement over using the published MLD alone model (AUC = 0.75 vs. 0.70; p-value = 0.0006 vs. 0.04; pHL = 0.67 vs. 0.84). Risk of RPEarly is thus estimated as: RPEarly = 1/(1 = e-x); x = -5.79 + (1.57*MLD) + (0.14* SUVP90). Patients at risk for RPEarly can be accurately identified prior to treatment by combining a re-fitted version of the published Mean Lung Dose model and pre-treatment FDG PET SUVP90 of the normal lung. This refined model can be used to identify patients with an exacerbated risk for premature durvalumab discontinuation due to RPEarly and could allow for interventions and/or the generation of "RPEarly sparing" treatment plans to improve overall treatment outcomes.

Multicentric 68Ga-PSMA PET radiomics for treatment response assessment of 177Lu-PSMA-617 radioligand therapy in patients with metastatic castration-resistant prostate cancer.

The treatment with 177Lutetium PSMA (177Lu-PSMA) in patients with metastatic castration-resistant prostate cancer (mCRPC) has recently been approved by the FDA and EMA. Since treatment success is highly variable between patients, the prediction of treatment response and identification of short- and long-term survivors after treatment could help tailor mCRPC diagnosis and treatment accordingly. The aim of this study is to investigate the value of radiomic parameters extracted from pretreatment 68Ga-PSMA PET images for the prediction of treatment response. A total of 45 mCRPC patients treated with 177Lu-PSMA-617 from two university hospital centers were retrospectively reviewed for this study. Radiomic features were extracted from the volumetric segmentations of metastases in the bone. A random forest model was trained and validated to predict treatment response based on age and conventionally used PET parameters, radiomic features and combinations thereof. Further, overall survival was predicted by using the identified radiomic signature and compared to a Cox regression model based on age and PET parameters. The machine learning model based on a combined radiomic signature of three features and patient age achieved an AUC of 0.82 in 5-fold cross-validation and outperformed models based on age and PET parameters or radiomic features (AUC, 0.75 and 0.76, respectively). A Cox regression model based on this radiomic signature showed the best performance to predict overall survival (C-index, 0.67). Our results demonstrate that a machine learning model to predict response to 177Lu-PSMA treatment based on a combination of radiomics and patient age outperforms a model based on age and PET parameters. Moreover, the identified radiomic signature based on pretreatment 68Ga-PSMA PET images might be able to identify patients with an improved outcome and serve as a supportive tool in clinical decision making.

The feasibility of quantitative assessment of dynamic 18F-fluorodeoxyglucose PET in Takayasu's arteritis: a pilot study.

PET has been demonstrated to be sensitive for detecting active inflammation in Takayasu's arteritis (TAK) patients, but semi-quantitative-based assessment may be susceptible to various biological and technical factors. Absolute quantification via dynamic PET (dPET) may provide a more reliable and quantitative assessment of TAK-active arteries. The purpose of this study was to investigate the feasibility and efficacy of dPET in quantifying TAK-active arteries compared to static PET. This prospective study enrolled 10 TAK-active patients (fulfilled the NIH criteria) and 5 control participants from March to October 2022. One-hour dPET scan (all TAK and control participants) and delayed static PET scan at 2-h (all TAK patients) were acquired. For 1-h static PET, summed images from 50 to 60min of the dPET were extracted. PET parameters derived from 1- and 2-h static PET including SUV (SUV1H and SUV2H), target-to-background ratio (TBR) (TBR1H and TBR2H), net influx rate (Ki), and TBRKi extracted from dPET were obtained. The detectability of TAK-active arteries was compared among different scanning methods using the generalized estimating equation (GEE) with a logistic regression with repeated measures, and the GEE with gamma distribution and log link function was used to evaluate the different study groups or scanning methods. Based on the disease states, 5 cases of TAK were classified as untreated and relapsed, respectively. The SUVmax on 2-h PET was higher than that on 1-h PET in the untreated patients (P < 0.05). However, no significant differences were observed in the median SUVmax between 1-h PET and 2-h PET in the relapsed patients (P > 0.05). The TBRKi was significantly higher than both TBR1H and TBR2H (all P < 0.001). Moreover, the detectability of TAK-active arteries by dPET-derived Ki was significantly higher than 1-h and 2-h PET (all P < 0.001). Significant differences were observed in Kimax, SUVmax-1H, TBR1H, and TBRKi among untreated, relapsed, and control groups (all P < 0.05). Absolute quantitative assessment by dPET provides an improved sensitivity and detectability in both visualization and quantification of TAK-active arteries. This elucidates the clinical significance of dPET in the early detection of active inflammation and monitoring recurrence.

JS09.6.A ASSESSMENT OF RESPONSE TO REGORAFENIB IN RECURRENT GLIOMA PATIENTS USING FET PET AND MRI INCLUDING ADC VALUES

Abstract BACKGROUND The phase 2 REGOMA trial suggested that glioblastoma patients treated with the multikinase inhibitor regorafenib at first progression have significantly longer overall survival than patients treated with lomustine. Here, we evaluated the value of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET and MRI for the evaluation of response to regorafenib in recurrent glioma patients. MATERIAL AND METHODS Twenty patients (age range, 30-72 years) with CNS WHO grade 3 or 4 gliomas (glioblastoma, 85%) at recurrence were treated according to the REGOMA trial with regorafenib at 160 mg/d for the first three weeks of each 4-week cycle, with individual dose adjustment according to toxicity. FET PET and MRI were performed at baseline and follow-up after the second cycle. Static FET PET parameters comprised tumor-to-brain ratios (TBR) and metabolic tumor volumes (MTV). Parameters derived from dynamic FET PET acquisition were time-to-peak and slope. MRI response assessment was based on RANO criteria. Additionally, mean and minimum apparent diffusion coefficients (ADC) were obtained from diffusion-weighted MRI. FET PET parameters and ADC thresholds were defined using ROC analyses to predict an overall survival of ≥ 6 months. The predictive values of FET PET parameters, ADC values, and RANO criteria were subsequently evaluated using univariate and multivariate survival estimates. RESULTS Patients received a median of three regorafenib cycles (range, 2-10 cycles). After treatment initiation, the median follow-up was 8.6 months (range, 3.2-27.3 months). The median number of previous treatment lines was two (range, 1-4 lines). At the time of data analysis, 17 patients (85%) had died. After two cycles of regorafenib, a regorafenib-induced reduction of mean TBR values by ≥ 10% predicted a longer overall survival (9.9 vs. 5.3 months; P=0.023). Interestingly, absolute mean TBR values ≤ 2.0 at follow-up were prognostic and associated with longer OS (10.6 vs. 4.5 months; P=0.007). In contrast, MTV, dynamic PET parameters, RANO criteria, and ADC values were not predictive for response or prognostic (all P&amp;gt;0.05). Multivariate survival analyses revealed that relative mean TBR changes were most potent in predicting response to regorafenib (P=0.038; HR, 0.246) and absolute mean TBR values for prognostication (P&amp;lt;0.001; HR, 0.005). CONCLUSION Data suggest that FET PET parameters are clinically valuable for identifying responders to regorafenib early after treatment initiation and helpful for prognostication. MRI parameters, including ADC values, do not appear to add valuable information in this context.

Direct Patlak Reconstruction of [68Ga]Ga-PSMA PET for the Evaluation of Primary Prostate Cancer Prior Total Prostatectomy: Results of a Pilot Study.

To investigate the use of kinetic parameters derived from direct Patlak reconstructions of [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) to predict the histological grade of malignancy of the primary tumor of patients with prostate cancer (PCa). Thirteen patients (mean age 66 ± 10 years) with a primary, therapy-naïve PCa (median PSA 9.3 [range: 6.3-130 µg/L]) prior radical prostatectomy, were recruited in this exploratory prospective study. A dynamic whole-body [68Ga]Ga-PSMA-11 PET/CT scan was performed for all patients. Measured quantification parameters included Patlak slope (Ki: absolute rate of tracer consumption) and Patlak intercept (Vb: degree of tracer perfusion in the tumor). Additionally, the mean and maximum standardized uptake values (SUVmean and SUVmax) of the tumor were determined from a static PET 60 min post tracer injection. In every patient, initial PSA (iPSA) values that were also the PSA level at the time of the examination and final histology results with Gleason score (GS) grading were correlated with the quantitative readouts. Collectively, 20 individual malignant prostate lesions were ascertained and histologically graded for GS with ISUP classification. Six lesions were classified as ISUP 5, two as ISUP 4, eight as ISUP 3, and four as ISUP 2. In both static and dynamic PET/CT imaging, the prostate lesions could be visually distinguished from the background. The average values of the SUVmean, slope, and intercept of the background were 2.4 (±0.4), 0.015 1/min (±0.006), and 52% (±12), respectively. These were significantly lower than the corresponding parameters extracted from the prostate lesions (all p < 0.01). No significant differences were found between these values and the various GS and ISUP (all p > 0.05). Spearman correlation coefficient analysis demonstrated a strong correlation between static and dynamic PET/CT parameters (all r ≥ 0.70, p < 0.01). Both GS and ISUP grading revealed only weak correlations with the mean and maximum SUV and tumor-to-background ratio derived from static images and dynamic Patlak slope. The iPSA demonstrated no significant correlation with GS and ISUP grading or with dynamic and static PET parameter values. In this cohort of mainly high-risk PCa, no significant correlation between [68Ga]Ga-PSMA-11 perfusion and consumption and the aggressiveness of the primary tumor was observed. This suggests that the association between SUV values and GS may be more distinctive when distinguishing clinically relevant from clinically non-relevant PCa.

Multiparameter diagnostic model based on 18F-FDG positron emission tomography and serological examination for differentiating focal autoimmune pancreatitis from pancreatic ductal adenocarcinoma.

18F-fluorodeoxyglucose positron emission tomography-computerized tomography (18F-FDG PET-CT) has demonstrated high sensitivity in the diagnosis of autoimmune pancreatitis (AIP) and pancreatic ductal adenocarcinoma (PDAC), while also exhibiting the ability to distinguish AIP from PDAC lesions. The objective of this investigation was to assess the efficacy of multiparametric 18F-FDG PET with serological examination for distinguishing focal AIP (f-AIP) from PDAC. A total of 127 patients (43 with f-AIP and 84 with PDAC) who received 18F-FDG PET-CT before treatment were retrospectively included in the cohort study conducted at two centers, Beijing Friendship Hospital and Chinese PLA General Hospital, from January 2015 to December 2021. The baseline characteristics and clinical data were collected. The metabolism parameters of 18F-FDG PET, including maximum standardized uptake value (SUVmax), tumor-to-normal liver SUV ratio (SUVR), mean SUV (SUVmean), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were evaluated. The area under the receiver operating characteristic (ROC) curve was used to evaluate the differential diagnostic efficacy. The diagnostic efficacy improvement was assessed through the integrated discriminatory improvement (IDI), net reclassification improvement (NRI), and DeLong test. Serum immunoglobulin G4 (IgG4) >280 mg/dL, carbohydrate antigen 19-9 (CA19-9) <85 U/mL, and metabolic parameters differed significantly between patients with f-AID and PDAC. The ROC curve analysis of MTV showed the highest differentiating diagnostic value [sensitivity =0.814, 95% confidence interval (CI): 0.661-0.911; specificity =0.893, 95% CI: 0.802-0.947; area under the curve (AUC) =0.890, 95% CI: 0.820-0.957]. The combined diagnostics model of serum IgG4 >280 mg/dL, CA19-9 <85 U/mL, and MTV resulted in the highest AUC of 0.991 (95% CI: 0.978-1.000; sensitivity =0.953, 95% CI: 0.829-0.992; specificity =0.964, 95% CI: 0.892-0.991). The multiparameter diagnostic model based on 18F-FDG PET and serological examination has excellent clinical value in the differential diagnosis of f-AID and PDAC.

The Prognostic Value of Sequential 18 F-FDG PET/CT Metabolic Parameters in Outcomes of Upper-Third Esophageal Squamous Cell Carcinoma Patients Treated with Definitive Chemoradiotherapy.

Objective The aim of this study is to determine prognostic values of sequential 18 F-FDG PET/CT metabolic parameters in locally advanced esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy. Materials and Methods Forty locally advanced ESCC patients treated with definitive chemoradiotherapy (dCRT) who received pre-treatment 18 F-FDG PET/CT (PET1) and 3-months post-treatment 18 F-FDG PET/CT (PET2) were enrolled in the prospective study. 18 F-FDG PET parameters of the primary tumor including maximum and mean standardized uptake values (SUVmax, SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated on PET delineated primary tumor. Using Kaplan-Meier curves to estimated overall survival (OS), progression-free survival (PFS), and local-regional control (LRC). Cox regression analysis was performed to find significant prognostic factors for survival. Results With a median follow-up of 13.5 months, the 4-year OS, PFS, and LRC rates were 67.3%, 52.6%, and 53.4% respectively. Patients with MTV 2 > 5.7 had lower OS, PFS, and LRC rates than the lower MTV 2 group (p < 0.05). Univariate Cox regression analysis showed that MTV2 was a significant prognostic factor for OS, PFS, and LRC (p < 0.05). Conclusion MTV parameter of sequential 18 F-FDG PET/CT could be used as a prognostic factor for OS, PFS, and LRC in locally advanced ESCC patients treated with dCRT.

1254 Examining the Role of PET-CT in the Management of Oesophageal Cancer: A Single Institution Experience

Abstract Aim The role of PET-CT in oesophageal cancer is controversial. The aim of this study was to evaluate the utility of PET-CT in staging and response evaluation in oesophageal squamous cell carcinoma (SCC) and adenocarcinoma (AC). Method Patients undergoing curative-intent treatment were studied prospectively. PET1 was carried out at diagnosis and repeat scanning (PET2) was performed 2-4 weeks post-completion of neoadjuvant chemotherapy (nCT) or chemoradiation (nCRT). The association between PET parameters, histopathologic response and survival was determined using univariable and multivariable regression models. Results 730 consecutive patients were studied. PET identified CT-occult M1 disease in 2.9% and synchronous neoplasm in 1.4%. Similar PET1 SUVmax values were observed in AC and SCC. The reduction in SUVmax was greater post-nCRT versus nCT (P = 0.021). SUVmax correlated with pT stage among patients treated with primary surgery (P&amp;lt;0.001), however 32.3% with AC and 15.8% with SCC who were predicted node negative were pN+. Post neoadjuvant therapy, PET parameters showed modest associations with major pathologic response, but no parameter accurately predicted complete pathologic response. Among patients with a metabolic complete response (mCR), 90.9% with AC post-nCT, 84.1% with AC post-nCRT and 54.8% with SCC post-nCRT had residual disease. Lower preoperative SUVmax was independently associated with improved survival outcomes in AC, but not SCC. Conclusions PET-CT identified CT-occult M1 disease or synchronous neoplasms in 4.3% at initial staging. After neoadjuvant therapy, PET is poorly predictive of histopathologic response – most patients with an mCR have residual disease. Nonetheless, improvements in SUVmax may reflect a more favourable long-term outcome in AC.

327. ANALYSING THE ROLE OF PET-CT IN ESOPHAGEAL CANCER: A SINGLE CENTRE COHORT STUDY

Abstract Background While PET-CT is considered the gold standard imaging investigation in diagnosing esophageal cancer, its role in determining management is controversial. It demonstrates increased sensitivity for detection of occult M1 disease in comparison with endosonography or CT alone, however its accuracy in assessment of histopathologic response to neoadjuvant therapy is unclear. The aim of this study was to evaluate the clinical utility of PET-CT in staging, response evaluation and prognostication in esophageal squamous cell carcinoma (SCC) and adenocarcinoma (AC). Methods Patients with esophageal cancer undergoing treatment with curative intent were studied prospectively. Baseline imaging (PET1) was carried out at diagnosis. Repeat scanning (PET2) was performed at 4 weeks post-completion of neoadjuvant chemotherapy (nCT) or chemoradiation (nCRT). Pathological complete response (pCR) was defined as TRG1, ypN0. Major pathologic response was defined as TRG1–2, ypN0. Metabolic complete response (mCR) was defined as absence of abnormal FDG uptake at the primary site, nodal sites or suspected metastatic sites. The association between 18F-FDG-uptake (SUVmax) and PET-predicted nodal status, histopathologic parameters and survival were determined using univariable and multivariable regression models. Results 730 patients were studied. PET identified CT-occult M1 disease in 2.9% and synchronous neoplasms in 1.4%. The relative reduction in SUVmax was greater among patients treated with nCRT compared with nCT (P = 0.021). SUVmax correlated with pT stage among patients treated with primary surgery (P &amp;lt; 0.001), however 32.3% with AC and 15.8% with SCC who were predicted node negative were pN+. Post neoadjuvant therapy, PET parameters showed modest associations with mCR, but no parameter accurately predicted pCR. Among patients with mCR, 90.9% with AC post-nCT, 84.1% with AC post-nCRT and 54.8% with SCC post-nCRT had residual disease. Lower preoperative SUVmax was independently associated with improved survival in AC, but not SCC. Conclusion PET-CT identifies CT-occult M1 disease or synchronous neoplasms in 4.3% at initial staging. PET-CT poorly predicts ypN status, particularly in AC. After neoadjuvant therapy, PET-CT is poorly predictive of histopathologic response—the majority of patients with an mCR have residual disease. Nonetheless, improvements in SUVmax may reflect a greater chance of achieving major pathologic response and more favourable long-term outcomes in AC.

Predictive value of radiomic signature based on 2-[18F]FDG PET/CT in HER2 status determination for primary breast cancer with equivocal IHC results

PurposeTo evaluate the predictive power of 2-[18F]FDG PET/CT-derived radiomic signature in human epidermal growth factor receptor 2 (HER2) status determination for primary breast cancer (BC) with equivocal immunohistochemistry (IHC) results for HER2. MethodsA total of 154 primary BC with equivocal IHC results for HER2 were retrospectively enrolled in the study. First, the following five conventional PET parameters (SUVmax, SUVmean, SUVpeak, MTV, TLG) were measured and compared between HER2-positive and HER2-negative cohorts. After quantitative radiomic features extraction and reduction, the least absolute shrinkage and selection operator (LASSO) algorithm was used to establish a radiomic signature model. Then, the area under the curve (AUCs) after a receiver operator characteristic (ROC) analysis, accuracy, sensitivity and specificity were calculated and used as the main outcomes. Finally, a total of 37 BC patients from an external institution were included to perform an external validation. ResultsAll the five conventional PET parameters were unable to discriminate between HER2-positive and HER2-negative cohorts for BC (P = 0.104–0.544). Whereas, the developed radiomic signature model was potentially predictive of HER2 status with an of AUC 0.887 (95% confidence interval [CI], 0.824–0.950) in the training cohort and 0.766 (95% CI, 0.616–0.916) in the validation cohort, respectively. For external validation, the AUC for the external test cohort was 0.788 (95% CI, 0.633–0.944). ConclusionsRadiomic signature based on 2-[18F]FDG PET/CT images was capable of non-invasively predicting the HER2 status with a comparable ability to FISH assay, especially for those with equivocal IHC results for HER2.

Valor pronóstico de los parámetros metabólicos volumétricos del tumor primario y ganglios linfáticos en el PET/TC pretratamiento en el carcinoma nasofaríngeo

BackgroundThe aim of this study was to evaluate the prognostic significance of volumetric metabolic parameters of pre-treatment PET/CT along with clinical characteristics in patients with non-metastatic nasopharyngeal carcinoma. Material and methodsSeventy-nine patients with nasopharyngeal carcinoma underwent F18-FDG PET/CT for pretreatment evaluation and included in this study. The patient features (patient age, tumor histopathology, T and N stage, size of primary tumor and the largest cervical lymph node) and PET parameters were analyzed: maximum, mean and peak standardized uptake values (SUVmax, SUVmean, SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumor and largest cervical lymph node. After treatment, patients were evaluated for disease progression and mortality. Survival analysis for progression-free survival (PFS) and over-all survival (OS) was performed with Kaplan–Meier method using PET findings and clinical characteristics. ResultsThe median follow-up duration was 29.7 months (range 3–125 months). Among clinical characteristics, no parameters had significance association for PFS. Primary tumor-MTV and cervical lymphnode-MTV were independent prognostic factors for PFS (p = 0.025 and p = 0.004, respectively). Patients with primary tumor-MTV > 19.4 and patients with lymph node-MTV > 3.4 had shorter PFS. For OS, age and the size of the lymph node were independent prognostic factor (p = 0.031 and p = 0.029). Patients with age over 54 years and patients with lymph node size > 1 cm were associated with decreased OS. ConclusionPrimary tumor-MTV and lymph node-MTV on pre-treatment PET/CT are significant prognostic factors for long-term PFS in non-metastatic nasopharyngeal carcinoma. We consider that measuring MTV as volume-based metabolic parameter on pretreatment PET/CT may contribute decision of treatment intensity and individualized risk stratification and may improve long-term PFS. Additionally, age and the size of lymph node are independent prognostic factors for mortality.

Can physiologic colonic [18F]FDG uptake in PET/CT imaging predict response to immunotherapy in metastatic melanoma?

AimThe development of biomarkers that can reliably and early predict response to immune checkpoint inhibitors (ICIs) is crucial in melanoma. In recent years, the gut microbiome has emerged as an important regulator of immunotherapy response, which may, moreover, serve as a surrogate marker and prognosticator in oncological patients under immunotherapy. Aim of the present study is to investigate if physiologic colonic [18F]FDG uptake in PET/CT before start of ICIs correlates with clinical outcome of metastatic melanoma patients. The relation between [18F]FDG uptake in lymphoid cell-rich organs and long-term patient outcome is also assessed.MethodologyOne hundred nineteen stage IV melanoma patients scheduled for immunotherapy with ipilimumab, applied either as monotherapy or in combination with nivolumab, underwent baseline [18F]FDG PET/CT. PET/CT data analysis consisted of standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) calculations in the colon as well as measurements of the colon-to-liver SUV ratios (CLRmean, CLRmax). Visual grading of colon uptake based on a four-point scale was also performed. Moreover, the spleen-to-liver SUV ratios (SLRmean, SLRmax) and the bone marrow-to-liver SUV ratios (BLRmean, BLRmax) were calculated. We also measured serum lipopolysaccharide (LPS) levels as a marker for bacterial translocation and surrogate for mucosal defense homeostasis. The results were correlated with patients’ best clinical response, progression-free survival (PFS), and overall survival (OS) as well as clinical signs of colitis.ResultsMedian follow-up [95%CI] from the beginning of immunotherapy was 64.6 months [61.0–68.6 months]. Best response to treatment was progressive disease (PD) for 60 patients, stable disease (SD) for 37 patients, partial response (PR) for 18 patients, and complete response (CR) for 4 patients. Kaplan–Meier curves demonstrated a trend for longer PFS and OS in patients with lower colonic SUV and CLR values; however, no statistical significance for these parameters as prognostic factors was demonstrated. On the other hand, patients showing disease control as best response to treatment (SD, PR, CR) had significantly lower colonic MTV and TLG than those showing PD. With regard to lymphoid cell-rich organs, significantly lower baseline SLRmax and BLRmax were observed in patients responding with disease control than progression to treatment. Furthermore, patients with lower SLRmax and BLRmax values had a significantly longer OS when dichotomized at their median. In multivariate analysis, PET parameters that were found to significantly adversely correlate with patient survival were colonic MTV for PFS, colonic TLG for PFS, and BLRmax for PFS and OS.ConclusionsPhysiologic colonic [18F]FDG uptake in PET/CT, as assessed by means of SUV, before start of ipilimumab-based treatment does not seem to independently predict patient survival of metastatic melanoma. On the other hand, volumetric PET parameters, such as MTV and TLG, derived from the normal gut may identify patients showing disease control to immunotherapy and significantly correlate with PFS. Moreover, the investigation of glucose metabolism in the spleen and the bone marrow may offer prognostic information.

Changes in serial multiparametric MRI and FDG-PET/CT functional imaging during radiation therapy can predict treatment response in patients with head and neck cancer

ObjectivesTo test if tumour changes measured using combination of diffusion-weighted imaging (DWI) MRI and FDG-PET/CT performed serially during radiotherapy (RT) in mucosal head and neck carcinoma can predict treatment response.MethodsFifty-five patients from two prospective imaging biomarker studies were analysed. FDG-PET/CT was performed at baseline, during RT (week 3), and post RT (3 months). DWI was performed at baseline, during RT (weeks 2, 3, 5, 6), and post RT (1 and 3 months). The ADCmean from DWI and FDG-PET parameters SUVmax, SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. Absolute and relative change (%∆) in DWI and PET parameters were correlated to 1-year local recurrence. Patients were categorised into favourable, mixed, and unfavourable imaging response using optimal cut-off (OC) values of DWI and FDG-PET parameters and correlated to local control.ResultsThe 1-year local, regional, and distant recurrence rates were 18.2% (10/55), 7.3% (4/55), and 12.7% (7/55), respectively. ∆Week 3 ADCmean (AUC 0.825, p = 0.003; OC ∆ > 24.4%) and ∆MTV (AUC 0.833, p = 0.001; OC ∆ > 50.4%) were the best predictors of local recurrence. Week 3 was the optimal time point for assessing DWI imaging response. Using a combination of ∆ADCmean and ∆MTV improved the strength of correlation to local recurrence (p ≤ 0.001). In patients who underwent both week 3 MRI and FDG-PET/CT, significant differences in local recurrence rates were seen between patients with favourable (0%), mixed (17%), and unfavourable (78%) combined imaging response.ConclusionsChanges in mid-treatment DWI and FDG-PET/CT imaging can predict treatment response and could be utilised in the design of future adaptive clinical trials.Clinical relevance statementOur study shows the complementary information provided by two functional imaging modalities for mid-treatment response prediction in patients with head and neck cancer.Key Points•FDG-PET/CT and DWI MRI changes in tumour during radiotherapy in head and neck cancer can predict treatment response.•Combination of FDG-PET/CT and DWI parameters improved correlation to clinical outcome.•Week 3 was the optimal time point for DWI MRI imaging response assessment.

An Optimal Radiomics Nomogram Based on 18F-FDG PET/CT for Identifying Event-Free Survival in Pediatric Neuroblastoma

To investigate whether the 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics features that combine tumor and bone marrow can more accurately identify event-free survival (EFS) in pediatric neuroblastoma. A total of 126patients with neuroblastoma were retrospectively included and randomly divided into the training and validation cohorts (7:3 ratio). Radiomics features were extracted to develop a tumor- and bone marrow-based radiomics risk score (RRS). The Kaplan-Meier method was used to evaluate the effectiveness of RRS in EFS risk stratification. Univariate and multivariate Cox regression analyses were used to determine independent clinical risk factors and construct the clinical models. The conventional PET model was constructed based on conventional PET parameters, and the noninvasive combined model integrated the RRS and the noninvasive independent clinical risk factors. The performance of the models was evaluated using C-index, calibration curves, and decision curve analysis (DCA). A total of 15 radiomics features were selected to build the RRS. According to Kaplan-Meier analysis, there was a significant difference in EFS between the low-risk and high-risk groups as defined by the value of RRS (P<.05). The noninvasive combined model combining RRS and the International Neuroblastoma Risk Group stage achieved the best prognostic prediction of EFS, with a C-index of 0.810 and 0.783 in the training and validation cohorts, respectively. The calibration curves and DCA indicated that the noninvasive combined model had good consistency and clinical utility. The 18F-FDG PET/CT-based radiomics of neuroblastoma allows a reliable evaluation of EFS. The performance of the noninvasive combined model was superior to the clinical and conventional PET models.

Prognostic value of primary tumor and lymph node volumetric metabolic parameters at pre-treatment F-18 FDG PET/CT in nasopharyngeal carcinoma

BackgroundThe aim of this study was to evaluate the prognostic significance of volumetric metabolic parameters of pre-treatment PET/CT along with clinical characteristics in patients with non-metastatic nasopharyngeal carcinoma. Material and methodsSeventy-nine patients with nasopharyngeal carcinoma underwent F18- FDG PET/CT for pretreatment evaluation and included in this study. The patient features (patient age, tumor histopathology, T and N stage, size of primary tumor and the largest cervical lymph node) and PET parameters were analyzed: maximum, mean and peak standardized uptake values (SUVmax, SUVmean, SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumor and largest cervical lymph node. After treatment, patients were evaluated for disease progression and mortality. Survival analysis for progression-free survival (PFS) and over-all survival (OS) was performed with Kaplan–Meier method using PET findings and clinical characteristics. ResultsThe median follow-up duration was 29.7 months (range 3–125 months). Among clinical characteristics, no parameters had significance association for PFS. Primary tumor-MTV and cervical lymph node-MTV were independent prognostic factors for PFS (p = 0.025 and p = 0.004, respectively).Patients with primary tumor-MTV >19.4 and patients with lymph node-MTV>3.4 had shorter PFS. For OS, age and the size of the lymph node were independent prognostic factor (p = 0.031 and p = 0.029).Patients with age over 54 years and patients with lymph node size >1 cm were associated with decreased OS. ConclusionPrimary tumor-MTV and lymph node-MTV on pre-treatment PET/CT are significant prognostic factors for long-term PFS in non-metastatic nasopharyngeal carcinoma.We consider that measuring MTV as volume-based metabolic parameter on pretreatment PET/CT may contribute decision of treatment intensity and individualized risk stratification and may improve long-term PFS. Additionally, age and the size of lymph node are independent prognostic factors for mortality.

Restaging of rectal cancer with hybrid positron emission tomography magnetic resonance imaging after preoperative chemoradiotherapy.

This study determines the sensitivity and specificity of positron emission tomography/magnetic resonance imaging (PET/MRI) parameters in predicting treatment response in patients with localised rectal cancer who have undergone preoperative chemoradiotherapy (CRT). Patients with stage I-III adenocarcinoma of the rectum planned for preoperative CRT followed by surgery were recruited. Patients had PET/MRI scans at baseline and 6-8 weeks post-CRT. Functional MRI and PET parameters were assessed for their diagnostic accuracy for tumour regression grade (TRG). Nonparametric receiver operating characteristic analysis was employed to determine the area under the ROC curve (AUC), and the sensitivity and specificity of each quantile cut-off. A total of 31 patients were recruited, of whom 20 completed study protocol. All patients included had mid or lower rectal tumours. There were 16 patients (80%) with node-positive disease at presentation. The median time to surgery was 75.5 days (range 52-106 days). Histopathological assessment revealed 20% good responders (TRG 1/2), and the remaining 80% of patients had a poor response (TRG 3/4). When predicting good responders, the AUC values for percent maximum thickness reduction and percent apparent diffusion coefficient (ADC) change were 0.82 and 0.73, respectively. A maximum thickness reduction cut-off of >47% and a percent ADC change of >20% yielded a sensitivity and specificity of 75%/95% and 75%/73%, respectively. Parameters such as percent maximum thickness reduction and percent ADC change may be useful for predicting good responders in patients undergoing preoperative CRT for rectal cancer. Larger studies are warranted to establish the utility of PET/MRI in rectal cancer staging.

18F-FDG and 18F-NaF PET/CT Global Assessment of Large Joint Inflammation and Bone Turnover in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) involves chronic inflammation of synovial joints, causing pain, stiffness, and limited mobility. 18F-sodium fluoride (NaF) is a PET tracer whose uptake reflects bone turnover, while 18F-fludeoxyglucose (FDG) shows glucose metabolism and can serve as a marker for inflammation. The aim of this study is to determine the feasibility of calculating the FDG and NaF mean standardized uptake value (SUVmean) in the knee joint, hip joint, and sacroiliac (SI) joint of RA patients and to determine their association with patient characteristics. Prospective FDG-PET/CT as well as NaF-PET/CT imaging was performed on 18 RA patients. The global SUVmean was calculated on FDG-PET/CT and NaF-PET/CT images using a semiautomated CT-based method of segmentation. FDG and NaF uptake were found to be significantly correlated in the knee (r = 0.77, p < 0.001), but not in the hip and SI joints. In the knee, both NaF SUVmean and FDG SUVmean were significantly correlated with body weight, BMI, leptin, and sclerostin levels (p < 0.05). NaF SUVmean was significantly positively correlated with BMI and leptin for both the hip and SI joints (p < 0.05). No significant correlation was observed between either PET parameter and age, height, erythrocyte sedimentation rate (ESR), and interleukins 1 and 6 (IL-1 and IL-6); however, FDG was correlated with inflammatory markers such as C-reactive protein (CRP) and patient global visual analogue scale (VAS-PtGlobal) in some joints. In this study, both FDG and NaF uptake were quantified in large joints of patients with RA using CT segmentation. NaF and FDG SUVmean were correlated with clinical variables related to body weight and adiposity, suggesting that degenerative joint disease may play a larger role in influencing the uptake of these tracers in large joints than RA disease activity. FDG and its correlation with markers of inflammation such as CRP and VAS-PtGlobal suggests that this tracer may serve as a more specific marker for RA disease activity than NaF. Larger prospective and longitudinal data are necessary to gain a better understanding of the roles of FDG and NaF in evaluating RA joint activity in these joints.

Development of a Model Based on Delta-Radiomic Features for the Optimization of Head and Neck Squamous Cell Carcinoma Patient Treatment.

Background and Objectives: To our knowledge, this is the first study that investigated the prognostic value of radiomics features extracted from not only staging 18F-fluorodeoxyglucose positron emission tomography (FDG PET/CT) images, but also post-induction chemotherapy (ICT) PET/CT images. This study aimed to construct a training model based on radiomics features obtained from PET/CT in a cohort of patients with locally advanced head and neck squamous cell carcinoma treated with ICT, to predict locoregional recurrence, development of distant metastases, and the overall survival, and to extract the most significant radiomics features, which were included in the final model. Materials and Methods: This retrospective study analyzed data of 55 patients. All patients underwent PET/CT at the initial staging and after ICT. Along the classical set of 13 parameters, the original 52 parameters were extracted from each PET/CT study and an additional 52 parameters were generated as a difference between radiomics parameters before and after the ICT. Five machine learning algorithms were tested. Results: The Random Forest algorithm demonstrated the best performance (R2 0.963-0.998) in the majority of datasets. The strongest correlation in the classical dataset was between the time to disease progression and time to death (r = 0.89). Another strong correlation (r ≥ 0.8) was between higher-order texture indices GLRLM_GLNU, GLRLM_SZLGE, and GLRLM_ZLNU and standard PET parameters MTV, TLG, and SUVmax. Patients with a higher numerical expression of GLCM_ContrastVariance, extracted from the delta dataset, had a longer survival and longer time until progression (p = 0.001). Good correlations were observed between Discretized_SUVstd or Discretized_SUVSkewness and time until progression (p = 0.007). Conclusions: Radiomics features extracted from the delta dataset produced the most robust data. Most of the parameters had a positive impact on the prediction of the overall survival and the time until progression. The strongest single parameter was GLCM_ContrastVariance. Discretized_SUVstd or Discretized_SUVSkewness demonstrated a strong correlation with the time until progression.