PET tumor metabolism in locally advanced breast cancer patients undergoing neoadjuvant chemotherapy: value of static versus kinetic measures of fluorodeoxyglucose uptake

Dynamic total-body PET/CT imaging with reduced acquisition time shows acceptable performance in quantification of [18F]FDG tumor kinetic metrics

PURPOSE

To investigate the feasibility of reducing the acquisition time for continuous dynamic positron emission tomography (PET) while retaining acceptable performance in quantifying kinetic metrics of 2-[18F]-fluoro-2-deoxy-D-glucose ([18F]FDG) in tumors.

METHODS

In total, 78 oncological patients underwent total-body dynamic PET imaging for ≥ 60 min, with 8, 20, and 50 patients receiving full activity (3.7 MBq/kg), half activity (1.85 MBq/kg), and ultra-low activity (0.37 MBq/kg) of [18F]FDG, respectively. The dynamic data were divided into 21-, 30-, 45- and ≥ 60-min groups. The kinetic analysis involved model fitting to derive constant rates (VB, K1 to k3, and Ki) for both tumors and normal tissues, using both reversible and irreversible two-tissue-compartment models. One-way ANOVA with repeated measures or the Freidman test compared the kinetic metrics among groups, while the Deming regression assessed the correlation of kinetic metrics among groups.

RESULTS

All kinetic metrics in the 30-min and 45-min groups were statistically comparable to those in the ≥ 60-min group. The relative differences between the 30-min and ≥ 60-min groups ranged from 12.3% ± 15.1% for K1 to 29.8% ± 30.0% for VB, and those between the 45-min and ≥ 60-min groups ranged from 7.5% ± 8.7% for Ki to 24.0% ± 24.3% for VB. However, this comparability was not observed between the 21-min and ≥ 60-min groups. The significance trend of these comparisons remained consistent across different models (reversible or irreversible), administrated activity levels, and partial volume corrections for lesions. Significant correlations in tumor kinetic metrics were identified between the 30-/45-min and ≥ 60-min groups, with Deming regression slopes > 0.813. In addition, the comparability of kinetic metrics between the 30-min and ≥ 60-min groups were established for normal tissues.

CONCLUSION

The acquisition time for dynamic PET imaging can be reduced to 30 min without compromising the ability to reveal tumor kinetic metrics of [18F]FDG, using the total-body PET/CT system.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.

METHODS

For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and - 16.3% for SUVmax, and 21.2% and - 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak.

CONCLUSION

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Increased lesion detectability in patients with locally advanced breast cancer-A pilot study using dynamic whole-body [18F]FDG PET/CT

BACKGROUND

Accurate diagnosis of axillary lymph node (ALN) metastases is essential for prognosis and treatment planning in breast cancer. Evaluation of ALN is done by ultrasound, which is limited by inter-operator variability, and by sentinel lymph node biopsy and/or ALN dissection, none of which are without risks and/or long-term complications. It is known that conventional 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) has limited sensitivity for ALN metastases. However, a recently developed dynamic whole-body (D-WB) [18F]FDG PET/CT scanning protocol, allowing for imaging of tissue [18F]FDG metabolic rate (MRFDG), has been shown to have the potential to increase lesion detectability. The study purpose was to examine detectability of malignant lesions in D-WB [18F]FDG PET/CT compared to conventional [18F]FDG PET/CT.

RESULTS

This study prospectively included ten women with locally advanced breast cancer who were referred for an [18F]FDG PET/CT as part of their diagnostic work-up. They all underwent D-WB [18F]FDG PET/CT, consisting of a 6 min single bed dynamic scan over the chest region started at the time of tracer injection, a 64 min dynamic WB PET scan consisting of 16 continuous bed motion passes, and finally a contrast-enhanced CT scan, with generation of MRFDG parametric images. Lesion visibility was assessed by tumor-to-background and contrast-to-noise ratios using volumes of interest isocontouring tumors with a set limit of 50% of SUVmax and background volumes placed in the vicinity of tumors. Lesion visibility was best in the MRFDG images, with target-to-background values 2.28 (95% CI: 2.04-2.54) times higher than target-to-background values in SUV images, and contrast-to-noise values 1.23 (95% CI: 1.12-1.35) times higher than contrast-to-noise values in SUV images. Furthermore, five imaging experts visually assessed the images and three additional suspicious lesions were found in the MRFDG images compared to SUV images; one suspicious ALN, one suspicious parasternal lymph node, and one suspicious lesion located in the pelvic bone.

CONCLUSIONS

D-WB [18F]FDG PET/CT with MRFDG images show potential for improved lesion detectability compared to conventional SUV images in locally advanced breast cancer. Further validation in larger cohorts is needed.

CLINICAL TRIAL REGISTRATION

The trial is registered in clinicaltrials.gov, NCT05110443, https://www.

CLINICALTRIALS

gov/study/NCT05110443?term=NCT05110443&rank=1 .

The Current and Future Roles of Precision Oncology in Advanced Breast Cancer

Breast cancer is a common but heterogeneous disease characterized by several biologic features, including tumor grade, hormone receptor status, human epidermal growth factor receptor 2 status, and gene expression assays. These biologic and genomic features drive treatment decisions. In the advanced disease setting, inter- and intrapatient tumor heterogeneity is increasingly recognized as a challenge for optimizing treatment. Recent evidence and the recent approval of novel radiopharmaceuticals have increased recognition and acceptance of the potential of molecular imaging as a biomarker to impact and guide management decisions for advanced breast cancer.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients with bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.In this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified as the maximum tumor voxel normalized by dose and body weight (SUVmax) and the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals of SUVmax and SULpeak were used to determine limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax in 38 bone tumors of the first cohort was 4.3%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and -16.3%, respectively. The 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria changed the status of 3 patients compared to standard the standard Positron Emission Tomography Response Criteria in Solid Tumors of ±30% SULpeak.

CONCLUSIONS

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG uptake, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions from these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

The role of dynamic, static, and delayed total-body PET imaging in the detection and differential diagnosis of oncological lesions

OBJECTIVES

Commercialized total-body PET scanners can provide high-quality images due to its ultra-high sensitivity. We compared the dynamic, regular static, and delayed 18F-fluorodeoxyglucose (FDG) scans to detect lesions in oncologic patients on a total-body PET/CT scanner.

MATERIALS & METHODS

In all, 45 patients were scanned continuously for the first 60 min, followed by a delayed acquisition. FDG metabolic rate was calculated from dynamic data using full compartmental modeling, whereas regular static and delayed SUV images were obtained approximately 60- and 145-min post-injection, respectively. The retention index was computed from static and delayed measures for all lesions. Pearson's correlation and Kruskal-Wallis tests were used to compare parameters.

RESULTS

The number of lesions was largely identical between the three protocols, except MRFDG and delayed images on total-body PET only detected 4 and 2 more lesions, respectively (85 total). FDG metabolic rate (MRFDG) image-derived contrast-to-noise ratio and target-to-background ratio were significantly higher than those from static standardized uptake value (SUV) images (P < 0.01), but this is not the case for the delayed images (P > 0.05). Dynamic protocol did not significantly differentiate between benign and malignant lesions just like regular SUV, delayed SUV, and retention index.

CONCLUSION

The potential quantitative advantages of dynamic imaging may not improve lesion detection and differential diagnosis significantly on a total-body PET/CT scanner. The same conclusion applied to delayed imaging. This suggested the added benefits of complex imaging protocols must be weighed against the complex implementation in the future.

CLINICAL RELEVANCE

Total-body PET/CT was known to significantly improve the PET image quality due to its ultra-high sensitivity. However, whether the dynamic and delay imaging on total-body scanner could show additional clinical benefits is largely unknown. Head-to-head comparison between two protocols is relevant to oncological management.

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[18F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, displaying similar pKa and binding affinity to nicotine. Time-activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Patlak-Ki derived from ultra-high sensitivity dynamic total body [18F]FDG PET/CT correlates with the response to induction immuno-chemotherapy in locally advanced non-small cell lung cancer patients

PURPOSE

This study aimed to investigate the predictive value of metabolic features in response to induction immuno-chemotherapy in patients with locally advanced non-small cell cancer (LA-NSCLC), using ultra-high sensitivity dynamic total body [18F]FDG PET/CT.

METHODS

The study analyzed LA-NSCLC patients who received two cycles of induction immuno-chemotherapy and underwent a 60-min dynamic total body [18F]FDG PET/CT scan before treatment. The primary tumors (PTs) were manually delineated, and their metabolic features, including the Patlak-Ki, Patlak-Intercept, maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were evaluated. The overall response rate (ORR) to induction immuno-chemotherapy was evaluated according to RECIST 1.1 criteria. The Patlak-Ki of PTs was calculated from the 20-60 min frames using the Patlak graphical analysis. The best feature was selected using Laplacian feature importance scores, and an unsupervised K-Means method was applied to cluster patients. ROC curve was used to examine the effect of selected metabolic feature in predicting tumor response to treatment. The targeted next generation sequencing on 1021 genes was conducted. The expressions of CD68, CD86, CD163, CD206, CD33, CD34, Ki67 and VEGFA were assayed through immunohistochemistry. The independent samples t test and the Mann-Whitney U test were applied in the intergroup comparison. Statistical significance was considered at P < 0.05.

RESULTS

Thirty-seven LA-NSCLC patients were analyzed between September 2020 and November 2021. All patients received two cycles of induction chemotherapy combined with Nivolumab/ Camrelizumab. The Laplacian scores showed that the Patlak-Ki of PTs had the highest importance for patient clustering, and the unsupervised K-Means derived decision boundary of Patlak-Ki was 2.779 ml/min/100 g. Patients were categorized into two groups based on their Patlak-Ki values: high FDG Patlak-Ki (H-FDG-Ki, Patlak-Ki > 2.779 ml/min/100 g) group (n = 23) and low FDG Patlak-Ki (L-FDG-Ki, Patlak-Ki ≤ 2.779 ml/min/100 g) group (n = 14). The ORR to induction immuno-chemotherapy was 67.6% (25/37) in the whole cohort, with 87% (20/23) in H-FDG-Ki group and 35.7% (5/14) in L-FDG-Ki group (P = 0.001). The sensitivity and specificity of Patlak-Ki in predicting the treatment response were 80% and 75%, respectively [AUC = 0.775 (95%CI 0.605-0.945)]. The expression of CD3+/CD8+ T cells and CD86+/CD163+/CD206+ macrophages were higher in the H-FDG-Ki group, while Ki67, CD33+ myeloid cells, CD34+ micro-vessel density (MVD) and tumor mutation burden (TMB) were comparable between the two groups.

CONCLUSIONS

The total body [18F]FDG PET/CT scanner performed a dynamic acquisition of the entire body and clustered LA-NSCLC patients into H-FDG-Ki and L-FDG-Ki groups based on the Patlak-Ki. Patients with H-FDG-Ki demonstrated better response to induction immuno-chemotherapy and higher levels of immune cell infiltration in the PTs compared to those with L-FDG-Ki. Further studies with a larger patient cohort are required to validate these findings.

Quantitative parameters of static imaging and fast kinetics imaging in 18F-FDG total-body PET/CT for the assessment of histological feature of pulmonary lesions

Background

To investigate the value of quantitative parameters related to static imaging and fast kinetics imaging of total-body (TB) 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in differentiating benign from malignant pulmonary lesions and squamous cell carcinoma (SCC) from adenocarcinoma (AC) and to analyze the correlation of each parameter with the Ki-67 index.

Methods

A total of 108 patients with pulmonary lesions from July 2021 to May 2022 in the Henan Provincial People's Hospital, China, were consecutively recruited for TB 18F-FDG PET/CT in this prospective study. Static imaging parameters maximum standardized uptake value (SUVmax) and fast kinetics imaging parameters transport constant (K1), rate constants (k2), time delay (td), and fractional blood volume (vb) were calculated and compared. The area under the receiver operating characteristic (ROC) curve (AUC), Delong test, Logistic regression analyses, and Pearson correlation were used to assess diagnostic efficacy, find independent predictors and analyse correlations respectively.

Results

Malignant lesions had higher SUVmax and K1 and lower vb than benign lesions, and SCC had higher SUVmax and K1 and lower td and vb than AC (all P<0.05). For the differentiation of benign and malignant lesions, SUVmax, K1, and vb were independent predictors, and AUC (SUVmax + K1+ vb) =0.909 (95% CI: 0.839-0.956), AUC (SUVmax) =0.883 (95% CI: 0.807-0.937), AUC (K1) =0.810 (95% CI: 0.723-0.879), and AUC (vb) =0.746 (95% CI: 0.653-0.825), where AUC (SUVmax + K1+ vb) was significantly different from AUC (K1), AUC (vb) (Z=3.006, 3.965, all P<0.05). For the differentiation of SCC and AC, SUVmax, K1, td, and vb were independent predictors, and AUC (SUVmax + K1+ td + vb) =0.946 (95% CI: 0.840-0.991), AUC (SUVmax) =0.818 (95% CI: 0.680-0.914), AUC (K1) =0.770 (95% CI: 0.626-0.879), AUC (vb) =0.737 (95% CI: 0.590-0.853), and AUC (td) =0.669 (95% CI: 0.510-0.791), where AUC (SUVmax + K1+ td + vb) was significantly different from AUC (SUVmax), AUC (K1), AUC (vb), and AUC (td) (Z=2.269, 2.821, 2.848, and 3.276, all P<0.05). SUVmax and K1 were moderately and mildly positively correlated with the Ki-67 index (r=0.541, 0.452, all P<0.05), respectively.

Conclusions

Quantitative parameters of static imaging and fast kinetics imaging in 18F-FDG total-body PET/CT can be used to differentiate benign from malignant pulmonary lesions and SCC from AC and to assess Ki-67 expression.

Value of Dynamic 18F-FDG PET/CT in Predicting the Success of Neoadjuvant Chemotherapy in Patients with Locally Advanced Breast Cancer: A Prospective Study

Objectives

This prospective study was planned to compare the predictive value of dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in locally advanced breast cancer patients (LABC) receiving neoadjuvant chemotherapy (NAC).

Methods

Twenty seven patients with LABC [median age: 47, (26-66)] underwent a dynamic 18F-FDG PET study at baseline, and after 2-3 cycles of (NAC) were included (interim). Maximum standardized uptake value (SUVmax) values and SUV ratios for the 2nd, 5th, 10th, and 30th minutes and dynamic curve slope (SL) values and SL ratios were measured using 18F-FDG dynamic data. In addition, the values of SUVmean (2minSUVmean), SULpeak (2minSULpeak), metabolic volume (2minVol), and total lesion glycolysis (2minTLG) were measured for the first 2 min. Percent changes between baseline and interim studies were calculated and compared with the pathological results as the pathological complete response (PCR) or the pathological non-complete response (non-PCR). Receiver operating characteristic curves were obtained to calculate the area under the curve to predict PCR. Optimal threshold values were calculated to discriminate between PCR and non-PCR groups.

Results

Baseline study SUV 30 (p=0.044), SUV 30/2 (p=0.041), SUV 30/5 (p=0.049), SUV 30/10 (p=0.021), SL 30/2 (p=0.029) and SL 30/5 (p=0.027) values were statistically significant different between PCR and non-PCR groups. The percentage changes of 2minVol between PCR and non-PCR groups were statistically significant. For the threshold value of -67.6% change in 2minVol, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 87.2%, 77.8%, 63.6%, 93.3%, and 80.7%, respectively (area under the curve: 0.826, p=0.009).

Conclusion

Semiquantitative parameters for dynamic 18F-FDG PET can predict PCR. % changes in 2minVol can identify non-responding patients better than other parameters.

The valuable role of dynamic 18F FDG PET/CT-derived kinetic parameter Ki in patients with nasopharyngeal carcinoma prior to radiotherapy: A prospective study

BACKGROUND AND PURPOSE

Dynamic positron emission tomography/computed tomography (PET/CT) served the potential role of characterizing malignant foci. The main objective of this prospective study was to explore the advantage of dynamic PET/CT imaging in characterizing nasopharyngeal carcinoma (NPC).

METHODS AND MATERIALS

Patients with probable head and neck disease underwent a local dynamic PET/CT scan followed by a whole-body static scan. Patlak analysis was used to generate parametric influx rate constant (K_i) images from 48 frames obtained from a dynamic PET/CT scan. By delineating the volumes-of-interest (VOIs) of: primary tumor (PT), lymph node (LN), and normal nasopharyngeal tissues (N), we acquired the corresponding K_i mean and SUVmean of each site respectively to perform the quantitative statistical analysis.

RESULTS

Qualified images of 71 patients with newly diagnosed NPC and 8 without nasopharyngeal malignant lesions were finally included. We found the correlations between K_i mean-PT and critical clinical features, including clinical stage (r = 0.368), T category (r = 0.643) and EBV-DNA copy status (r = 0.351), and K_i mean-PT differed within the group. SUVmean-PT showed correlations with clinical stage (r = 0.280) and T category (r = 0.472), but could hardly differ systematically within group of clinical features except T category. K_i mean-LN offered the positive correlations with N category (r = 0.294), M category (r = 0.238) and EBV-DNA copy status (r = 0.446), and differed within the group. In addition, K_i mean represented a sensitivity of 94.4 % and a specificity of 100 %, in distinguishing NPC from the non-NPC, when the cut-off was defined as 0.0106. When the cut-off of SUV being defined as 2.03, the sensitivity and specificity were both 100 %.

CONCLUSION

Our research confirmed K_i compared favorably to SUV in characterizing NPC and found that K_i can serve as an effective imaging marker of NPC.

Dynamic FDG-PET imaging for differentiating metastatic from non-metastatic lymph nodes of lung cancer

OBJECTIVES

18F-fluorodeoxyglucose (FDG) PET/CT has been widely used in tumor diagnosis, staging, and response evaluation. To determine an optimal therapeutic strategy for lung cancer patients, accurate staging is essential. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may fail to differentiate between benign and malignant lesions. Lymph nodes (LNs) in the mediastinal and pulmonary hilar regions with high FDG uptake due to granulomatous lesions such as tuberculosis, which has a high prevalence in China, pose a diagnostic challenge. This study aims to evaluate the diagnostic value of the quantitative metabolic parameters derived from dynamic 18F-FDG PET/CT in differentiating metastatic and non-metastatic LNs in lung cancer.

METHODS

One hundred and eight patients with pulmonary nodules were enrolled to perform 18F-FDG PET/CT dynamic + static imaging with informed consent. One hundred and thirty-five LNs in 29 lung cancer patients were confirmed by pathology. Static image analysis parameters including LN-SUVmax, LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax), mediastinal blood pool SUVmax (MBP-SUVmax), LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter. Quantitative parameters including K1, k2, k3 and Ki and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was computed subsequently as a separate marker. We further divided the LNs into mediastinal LNs (N=82) and pulmonary hilar LNs (N=53). Wilcoxon rank-sum test or Independent-samples T-test and receiver-operating characteristic (ROC) analysis was performed on each parameter to compare the diagnostic efficacy in differentiating lymph node metastases from inflammatory uptake. P<0.05 were considered statistically significant.

RESULTS

Among the 135 FDG-avid LNs confirmed by pathology, 49 LNs were non-metastatic, and 86 LNs were metastatic. LN-SUVmax, MBP-SUVmax, LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter couldn't well differentiate metastatic from non-metastatic LNs (P>0.05). However, LN-SUVmax/PT-SUVmax have good performance in the differential diagnosis of non-metastatic and metastatic LNs (P=0.039). Dynamic metabolic parameters in addition to k3, the parameters including K1, k2, Ki, and Ki/K1, on the other hand, have good performance in the differential diagnosis of metastatic and non-metastatic LNs (P=0.045, P=0.001, P=0.001, P=0.001, respectively). For ROC analysis, the metabolic parameters Ki (AUC of 0.672 [0.579-0.765], sensitivity 0.395, specificity 0.918) and Ki/K1 (AUC of 0.673 [0.580-0.767], sensitivity 0.570, specificity 0.776) have good performance in the differential diagnosis of metastatic from non-metastatic LNs than SUVmax (AUC of 0.596 [0.498-0.696], sensitivity 0.826, specificity 0.388), included the mediastinal region and pulmonary hilar region.

CONCLUSION

Compared with SUVmax, quantitative parameters such as K1, k2, Ki and Ki/K1 showed promising results for differentiation of metastatic and non-metastatic LNs with high uptake. The Ki and Ki/K1 had a high differential diagnostic value both in the mediastinal region and pulmonary hilar region.

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Purpose

Efforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body ¹⁸F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup.

Methods

The research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate K_i.

Results

K_i and K₁ derived from the DTW protocol showed overall good consistency (P < 0.01) with the reference from the 60-min dynamic scan with 10-min early scan and 5-min late scan (K_i correlation: 0.971, 0.990, and 0.990; K₁ correlation: 0.820, 0.940, and 0.975 in the cerebral cortex, muscle, and tumor lesion, respectively). Similar correlationss were found for other micro-parameters. The DTW protocol had the lowest bias relative to standard K_i than any of the quantification methods, followed by FUR and Patlak. SUV had the weakest correlation with K_i. The whole-body K_i and K₁ images generated by the DTW protocol were consistent with the reference parametric images.

Conclusions

Using the DTW protocol, the dynamic total-body FDG scan time can be reduced to 15 min while obtaining accurate K_i and K₁ quantification and acceptable visual performance in parametric images. However, the trade-off between quantification accuracy and protocol implementation feasibility must be considered in practice. We recommend that the DTW protocol be used when the clinical task requires reliable visual assessment or quantifying multiple micro-parameters; FUR with a hybrid input function may be a more feasible approach to quantifying regional metabolic rate with a known lesion position or organs of interest.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00492-w.

Role of dynamic and parametric whole-body FDG PET/CT imaging in molecular characterization of primary breast cancer: a single institution experience

AIM

The aim of this pilot study was to assess the role of dynamic whole-body PET and parametric imaging in the biological characterization of primary breast cancer.

MATERIALS AND METHOD

In total 24 histologically proven primary breast cancer lesions in 21 consecutive patients were retrospectively analyzed. Each patient underwent 18F-fluoro-deoxyglucose whole-body dynamic PET-CT before any treatment. Dynamic PET images were acquired in the list mode for a total duration of 70 min. The reconstructed parametric imaging generated Patlak plot-based 'Slope' and 'Intercept' images, from which parametric indices ki and DV were obtained. The standard uptake value (SUV) metric was also obtained by summing the last few frames of the dynamic study. ki, distribution volume (DV) and SUV were correlated with the histological tumor grade, biomarkers [hormone receptors and human epidermal growth factor receptor 2 (HER-2) neu expression] and molecular subtypes (A, B and C) as well as with tumor size, regional nodal metastases and distant metastases.

RESULTS

The mean ki was found to be significantly higher in grade III than II lesions (P = 0.005), HER-2 neu positive status (P = 0.04) and molecular subtype B (P = 0.04) as well as in greater than T1 lesions(P = 0.0003 and P = 0.04, respectively) and node-positive lesions (P = 0.009). Though mean ki was not found to be significant for the hormone receptors status (P = 0.08), it showed the best correlation compared to the other parameters (P = 0.8 for DV and P = 0.1 for SUV). Spearman's correlation test, area under the curve (AUC) and mismatch percentage also revealed ki to predict tumor grade (AUC, 0.95; r = 0.7; P = 0.0001), HER-2 neu status and molecular subtypes (AUC, 0.81; r = 0.49 and P = 0.01) along with the hormone receptors status (AUC, 0.83; r = 0.32; P = 0.1). The mean DV failed to show any association with any of the biological or anatomical staging parameters. Though ki was found to be comparable to that of SUV in almost all the assessed parameters, it appeared to be better for predicting hormone receptors status even though both parameters were not statistically significant.

CONCLUSION

Our initial observation in a small cohort of breast cancer patients suggests that ki is promising in stratifying primary breast cancer lesions according to the tumor grade and biological characteristics.

Short-time total-body dynamic PET imaging performance in quantifying the kinetic metrics of 18F-FDG in healthy volunteers

PURPOSE

To investigate the performance of short-time dynamic imaging in quantifying kinetic metrics of 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG).

METHODS

Dynamic total-body positron emission tomography (PET) imaging was performed in 11 healthy volunteers for 75 min. The data were divided into 30-, 45- and 75-min groups. Nonlinear regression (NLR) generated constant rates (k1 to k3) and NLR-based Ki in various organs. The Patlak method calculated parametric Ki images to generate Patlak-based Ki values. Paired samples t-test or the Wilcoxon signed-rank test compared the kinetic metrics between the groups, depending on data normality. Deming regression and Bland-Altman analysis assessed the correlation and agreement between NLR- and Patlak-based Ki. A two-sided P < 0.05 was considered statistically significant.

RESULTS

The 45- and 75-min groups were similar in NLR-based kinetic metrics. The relative difference ranges were as follows: k1, from 3.4% (P = 0.627) in the spleen to 57.9% (P = 0.130) in the white matter; k2, from 6.0% (P = 0.904) in the spleen to 60.7% (P = 0.235) in the left ventricle (LV) myocardium; k3, from 45.6% (P = 0.302) in the LV myocardium to 96.3% (P = 0.478) in the liver; Ki, from 14.0% (P = 0.488) in the liver to 77.8% (P = 0.067) in the kidney. Patlak-based Ki values were also similar between these groups in all organs, except the grey matter (9.6%, P = 0.029) and cerebellum (14.4%, P = 0.002). However, significant differences in kinetic metrics were found between the 30-min and 75-min groups in most organs both in NLR- and Patlak-based analyses. The NLR- and Patlak-based Ki values significantly correlated, with no bias in any of the organs.

CONCLUSION

Dynamic imaging using a high-sensitivity total-body PET scanner for a shorter time of 45 min could achieve relevant kinetic metrics of 18F-FDG as done by long-time imaging.

Radiogenomic analysis of primary breast cancer reveals [18F]-fluorodeoxglucose dynamic flux-constants are positively associated with immune pathways and outperform static uptake measures in associating with glucose metabolism

BACKGROUND

PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers.

METHODS

Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging.

RESULTS

A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance.

CONCLUSIONS

In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

ACR Appropriateness Criteria® Imaging of the Axilla

This publication reviews the current evidence supporting the imaging approach of the axilla in various scenarios with broad differential diagnosis ranging from inflammatory to malignant etiologies. Controversies on the management of axillary adenopathy results in disagreement on the appropriate axillary imaging tests. Ultrasound is often the appropriate initial imaging test in several clinical scenarios. Clinical information (such as age, physical examinations, risk factors) and concurrent complete breast evaluation with mammogram, tomosynthesis, or MRI impact the type of initial imaging test for the axilla. Several impactful clinical trials demonstrated that selected patient's population can received sentinel lymph node biopsy instead of axillary lymph node dissection with similar overall survival, and axillary lymph node dissection is a safe alternative as the nodal staging procedure for clinically node negative patients or even for some node positive patients with limited nodal tumor burden. This approach is not universally accepted, which adversely affect the type of imaging tests considered appropriate for axilla. This document is focused on the initial imaging of the axilla in various scenarios, with the understanding that concurrent or subsequent additional tests may also be performed for the breast. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

caliPER: A software for blood-free parametric Patlak mapping using PET/MRI input function

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce caliPER, a modular and scalable software for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on PET/MR IDIFs and Patlak Plot analysis. caliPER generates regional values or parametric maps of net influx rate (K_i) using reconstructed dynamic PET images and anatomical MRI aligned to PET for IDIF vessel delineation. We evaluated the performance of caliPER for blood-free region-based and pixel-wise Patlak analyses of [¹⁸F] FDG by comparing caliPER IDIF to serial arterial blood input functions and its application in imaging brain glucose hypometabolism in Frontotemporal dementia. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to arterial blood input functions with a general bias of around 6-8%, even for arteries <5 mm. The K_i and cerebral metabolic rate of glucose estimated using caliPER IDIF were similar to estimates using arterial blood sampling (<2%) and within limits of whole brain values reported in literature. Overall, caliPER is a promising tool for irreversible PET tracer quantification and can simplify the ability to perform parametric analysis in clinical settings without the need for blood sampling.

Principles of Tracer Kinetic Analysis in Oncology, Part II: Examples and Future Directions

Learning Objectives: On successful completion of this activity, participants should be able to (1) describe examples of the application of PET tracer kinetic analysis to oncology; (2) list applications research and possible clinical applications in oncology where kinetic analysis is helpful; and (3) discuss future applications of kinetic modeling to cancer research and possible clinical cancer imaging practice.Financial Disclosure: This work was supported by KL2 TR001879, R01 CA211337, R01 CA113941, R33 CA225310, Komen SAC130060, R50 CA211270, and K01 DA040023. Dr. Pantel is a consultant or advisor for Progenics and Blue Earth Diagnostics and is a meeting participant or lecturer for Blue Earth Diagnostics. Dr. Mankoff is on the scientific advisory boards of GE Healthcare, Philips Healthcare, Reflexion, and ImaginAb and is the owner of Trevarx; his wife is the chief executive officer of Trevarx. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest.CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through April 2025.Kinetic analysis of dynamic PET imaging enables the estimation of biologic processes relevant to disease. Through mathematic analysis of the interactions of a radiotracer with tissue, information can be gleaned from PET imaging beyond static uptake measures. Part I of this 2-part continuing education paper reviewed the underlying principles and methodology of kinetic modeling. In this second part, the benefits of kinetic modeling for oncologic imaging are illustrated through representative case examples that demonstrate the principles and benefits of kinetic analysis in oncology. Examples of the model types discussed in part I are reviewed here: a 1-tissue-compartment model (15O-water), an irreversible 2-tissue-compartment model (18F-FDG), and a reversible 2-tissue-compartment model (3'-deoxy-3'-18F-fluorothymidine). Kinetic approaches are contrasted with static uptake measures typically used in the clinic. Overall, this 2-part review provides the reader with background in kinetic analysis to understand related research and improve the interpretation of clinical nuclear medicine studies with a focus on oncologic imaging.

Principles of Tracer Kinetic Analysis in Oncology, Part I: Principles and Overview of Methodology

Learning Objectives: On successful completion of this activity, participants should be able to describe (1) describe principles of PET tracer kinetic analysis for oncologic applications; (2) list methods used for PET kinetic analysis for oncology; and (3) discuss application of kinetic modeling for cancer-specific diagnostic needs.Financial Disclosure: This work was supported by KL2 TR001879, R01 CA211337, R01 CA113941, R33 CA225310, Komen SAC130060, R50 CA211270, and K01 DA040023. Dr. Pantel is a consultant or advisor for Progenics and Blue Earth Diagnostics and is a meeting participant or lecturer for Blue Earth Diagnostics. Dr. Mankoff is on the scientific advisory boards of GE Healthcare, Philips Healthcare, Reflexion, and ImaginAb and is the owner of Trevarx; his wife is the chief executive officer of Trevarx. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest.CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through March 2025PET enables noninvasive imaging of regional in vivo cancer biology. By engineering a radiotracer to target specific biologic processes of relevance to cancer (e.g., cancer metabolism, blood flow, proliferation, and tumor receptor expression or ligand binding), PET can detect cancer spread, characterize the cancer phenotype, and assess its response to treatment. For example, imaging of glucose metabolism using the radiolabeled glucose analog ¹⁸F-FDG has widespread applications to all 3 of these tasks and plays an important role in cancer care. However, the current clinical practice of imaging at a single time point remote from tracer injection (i.e., static imaging) does not use all the information that PET cancer imaging can provide, especially to address questions beyond cancer detection. Reliance on tracer measures obtained only from static imaging may also lead to misleading results. In this 2-part continuing education paper, we describe the principles of tracer kinetic analysis for oncologic PET (part 1), followed by examples of specific implementations of kinetic analysis for cancer PET imaging that highlight the added benefits over static imaging (part 2). This review is designed to introduce nuclear medicine clinicians to basic concepts of kinetic analysis in oncologic imaging, with a goal of illustrating how kinetic analysis can augment our understanding of in vivo cancer biology, improve our approach to clinical decision making, and guide the interpretation of quantitative measures derived from static images.

Characterising 18F-fluciclovine uptake in breast cancer through the use of dynamic PET/CT imaging

BACKGROUND

18F-fluciclovine is a synthetic amino acid positron emission tomography (PET) radiotracer that is approved for use in prostate cancer. In this clinical study, we characterised the kinetic model best describing the uptake of 18F-fluciclovine in breast cancer and assessed differences in tracer kinetics and static parameters for different breast cancer receptor subtypes and tumour grades.

METHODS

Thirty-nine patients with pathologically proven breast cancer underwent 20-min dynamic PET/computed tomography imaging following the administration of 18F-fluciclovine. Uptake into primary breast tumours was evaluated using one- and two-tissue reversible compartmental kinetic models and static parameters.

RESULTS

A reversible one-tissue compartment model was shown to best describe tracer uptake in breast cancer. No significant differences were seen in kinetic or static parameters for different tumour receptor subtypes or grades. Kinetic and static parameters showed a good correlation.

CONCLUSIONS

18F-fluciclovine has potential in the imaging of primary breast cancer, but kinetic analysis may not have additional value over static measures of tracer uptake.

CLINICAL TRIAL REGISTRATION

NCT03036943.

Generation of parametric Ki images for FDG PET using two 5-min scans

PURPOSE

The net uptake rate constant (K_i ) derived from dynamic imaging is considered the gold standard quantification index for FDG PET. In this study, we investigated the feasibility and assessed the clinical usefulness of generating K_i images for FDG PET using only two 5-min scans with population-based input function (PBIF).

METHODS

Using a Siemens Biograph mCT, 10 subjects with solid lung nodules underwent a single-bed dynamic FDG PET scan and 13 subjects (five healthy and eight cancer patients) underwent a whole-body dynamic FDG PET scan in continuous-bed-motion mode. For each subject, a standard K_i image was generated using the complete 0-90 min dynamic data with Patlak analysis (t* = 20 min) and individual patient's input function, while a dual-time-point K_i image was generated from two 5-min scans based on the Patlak equations at early and late scans with the PBIF. Different start times for the early (ranging from 20 to 55 min with an increment of 5 min) and late (ranging from 50 to 85 min with an increment of 5 min) scans were investigated with the interval between scans being at least 30 min (36 protocols in total). The optimal dual-time-point protocols were then identified. Regions of interest (ROI) were drawn on nodules for the lung nodule subjects, and on tumors, cerebellum, and bone marrow for the whole-body-imaging subjects. Quantification accuracy was compared using the mean value of each ROI between standard K_i (gold standard) and dual-time-point K_i , as well as between standard K_i and relative standardized uptake value (SUV) change that is currently used in clinical practice. Correlation coefficients and least squares fits were calculated for each dual-time-point protocol and for each ROI. Then, the predefined criteria for identifying a reliable dual-time-point K_i estimation for each ROI were empirically determined as: (1) the squared correlation coefficient (R² ) between standard K_i and dual-time-point K_i is larger than 0.9; (2) the absolute difference between the slope of the equality line (1.0) and that of the fitted line when plotting standard K_i versus dual-time-point K_i is smaller than 0.1; (3) the absolute value of the intercept of the fitted line when plotting standard K_i versus dual-time-point K_i normalized by the mean of the standard K_i across all subjects for each ROI is smaller than 10%. Using Williams' one-tailed t test, the correlation coefficient (R) between standard K_i and dual-time-point K_i was further compared with that between standard K_i and relative SUV change, for each dual-time-point protocol and for each ROI.

RESULTS

Reliable dual-time-point K_i images were obtained for all the subjects using our proposed method. The percentage error introduced by the PBIF on the dual-time-point K_i estimation was smaller than 1% for all 36 protocols. Using the predefined criteria, reliable dual-time-point K_i estimation could be obtained in 25 of 36 protocols for nodules and in 34 of 36 protocols for tumors. A longer time interval between scans provided a more accurate K_i estimation in general. Using the protocol of 20-25 min plus 80-85 or 85-90 min, very high correlations were obtained between standard K_i and dual-time-point K_i (R²  = 0.994, 0.980, 0.971 and 0.925 for nodule, tumor, cerebellum, and bone marrow), with all the slope values with differences ≤0.033 from 1 and all the intercept values with differences ≤0.0006 mL/min/cm³ from 0. The corresponding correlations were much lower between standard K_i and relative SUV change (R²  = 0.673, 0.684, 0.065, 0.246). Dual-time-point K_i showed a significantly higher quantification accuracy with respect to standard K_i than relative SUV change for all the 36 protocols (p < 0.05 using Williams' one-tailed t test).

CONCLUSIONS

Our proposed approach can obtain reliable K_i images and accurate K_i quantification from dual-time-point scans (5-min per scan), and provide significantly higher quantification accuracy than relative SUV change that is currently used in clinical practice.

Quantitation of multiple injection dynamic PET scans: an investigation of the benefits of pooling data from separate scans when mapping kinetics

Multiple injection dynamic positron emission tomography (PET) scanning is used in the clinical management of certain groups of patients and in medical research. The analysis of these studies can be approached in two ways: (i) separate analysis of data from individual tracer injections, or (ii), concatenate/pool data from separate injections and carry out a combined analysis. The simplicity of separate analysis has some practical appeal but may not be statistically efficient. We use a linear model framework associated with a kinetic mapping scheme to develop a simplified theoretical understanding of separate and combined analysis. The theoretical framework is explored numerically using both 1D and 2D simulation models. These studies are motivated by the breast cancer flow-metabolism mismatch studies involving15O-water (H2O) and18F-Fluorodeoxyglucose (FDG) and repeat15O-H2O injections used in brain activation investigations. Numerical results are found to be substantially in line with the simple theoretical analysis: mean square error characteristics of alternative methods are well described by factors involving the local voxel-level resolution of the imaging data, the relative activities of the individual scans and the number of separate injections involved. While voxel-level resolution has dependence on scan dose, after adjustment for this effect, the impact of a combined analysis is understood in simple terms associated with the linear model used for kinetic mapping. This is true for both data reconstructed by direct filtered backprojection or iterative maximum likelihood. The proposed analysis has potential to be applied to the emerging long axial field-of-view PET scanners.

Quantitative PET in the 2020s: a roadmap

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

Purpose

Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making.

Methods

We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers.

Results

Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes.

Conclusions

Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05265-8.

Ultra-low-activity total-body dynamic PET imaging allows equal performance to full-activity PET imaging for investigating kinetic metrics of 18F-FDG in healthy volunteers

PURPOSE

To investigate the feasibility of ultra-low-activity total-body positron emission tomography (PET) dynamic imaging for quantifying kinetic metrics of 2-[¹⁸F]-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) in normal organs and to verify its clinical relevance with full-activity imaging.

METHODS

Dynamic total-body PET imaging was performed in 20 healthy volunteers, with eight using full activity (3.7 MBq/kg) of ¹⁸F-FDG and 12 using 10× activity reduction (0.37 MBq/kg). Image contrast, in terms of liver-to-muscle ratio (LMR), liver-to-blood ratio (LBR), and blood-to-muscle ratio (BMR) of radioactivity concentrations were assessed. A two-tissue compartment model was fitted to the time-to-activity curves in organs based on regions of interest (ROIs) delineation using PMOD, and constant rates (k₁, k₂, and k₃) were generated. Kinetic constants, corresponding coefficients of variance (CoVs), image contrast, radiation dose, prompt counts, and data size were compared between full- and low-activity groups.

RESULTS

All constant rates, corresponding CoVs, and image contrast in different organs were comparable with none significant differences between full- and ultra-low-activity groups. PET images in the ultra-low-activity group generated significantly lower effective radiation dose (median, 0.419 vs. 4.886 mSv, P < 0.001), reduced prompt counts (median, 2.79 vs. 55.68 billion, P < 0.001), and smaller data size (median, 71.11 vs. 723.18 GB, P < 0.001).

CONCLUSION

Total-body dynamic PET imaging using 10× reduction of injected activity could achieve relevant kinetic metrics of ¹⁸F-FDG and comparable image contrast with full-activity imaging. Activity reduction results in significant decrease of radiation dose and data size, rendering it more acceptable and easier for data reconstruction, transmission, and storage for clinical practice.

18F-fluorodeoxyglucose (FDG) PET or 18F-fluorothymidine (FLT) PET to assess early response to aromatase inhibitors (AI) in women with ER+ operable breast cancer in a window-of-opportunity study

PURPOSE

This study evaluated the ability of ¹⁸F-Fluorodeoxyglucose (FDG) and ¹⁸F-Fluorothymidine (FLT) imaging with positron emission tomography (PET) to measure early response to endocrine therapy from baseline to just prior to surgical resection in estrogen receptor positive (ER+) breast tumors.

METHODS

In two separate studies, women with early stage ER+ breast cancer underwent either paired FDG-PET (n = 22) or FLT-PET (n = 27) scans prior to endocrine therapy and again in the pre-operative setting. Tissue samples for Ki-67 were taken for all patients both prior to treatment and at the time of surgery.

RESULTS

FDG maximum standardized uptake value (SUVmax) declined in 19 of 22 lesions (mean 17% (range -45 to 28%)). FLT SUVmax declined in 24 of 27 lesions (mean 26% (range -77 to 7%)). The Ki-67 index declined in both studies, from pre-therapy (mean 23% (range 1 to 73%)) to surgery [mean 8% (range < 1 to 41%)]. Pre- and post-therapy PET measures showed strong rank-order agreement with Ki-67 percentages for both tracers; however, the percent change in FDG or FLT SUVmax did not demonstrate a strong correlation with Ki-67 index change or Ki-67 at time of surgery.

CONCLUSIONS

A window-of-opportunity approach using PET imaging to assess early response of breast cancer therapy is feasible. FDG and FLT-PET imaging following a short course of neoadjuvant endocrine therapy demonstrated measurable changes in SUVmax in early stage ER+ positive breast cancers. The percentage change in FDG and FLT-PET uptake did not correlate with changes in Ki-67; post-therapy SUVmax for both tracers was significantly associated with post-therapy Ki-67, an established predictor of endocrine therapy response.

Update on Quantitative Imaging for Predicting and Assessing Response in Oncology

Molecular imaging has revolutionized clinical oncology by imaging-specific facets of cancer biology. Through noninvasive measurements of tumor physiology, targeted radiotracers can serve as biomarkers for disease characterization, prognosis, response assessment, and predicting long-term response/survival. In turn, these imaging biomarkers can be utilized to tailor therapeutic regimens to tumor biology. In this article, we review biomarker applications for response assessment and predicting long-term outcomes. ¹⁸F-fluorodeoxyglucose (FDG), a measure of cellular glucose metabolism, is discussed in the context of lymphoma and breast and lung cancer. FDG has gained widespread clinical acceptance and has been integrated into the routine clinical care of several malignancies, most notably lymphoma. The novel radiotracers 16α-¹⁸F-fluoro-17β-estradiol and ¹⁸F-fluorothymidine are reviewed in application to the early prediction of response assessment of breast cancer. Through illustrative examples, we explore current and future applications of molecular imaging biomarkers in the advancement of precision medicine.

Prognostic value of 18F-FDG PET and PET/CT for assessment of treatment response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis

Background

We performed a systematic review and meta-analysis to evaluate the prognostic significance of ¹⁸F-FDG PET and PET/CT for evaluation of responses to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Methods

We searched PubMed, Embase, and the Cochrane Library databases until June 2020 to identify studies that assessed the prognostic value of ¹⁸F-FDG PET scans during or after NAC with regard to overall (OS) and disease-free survival (DFS). Hazard ratios (HRs) and their 95% confidence intervals (CIs) were pooled meta-analytically using a random-effects model.

Results

Twenty-one studies consisting of 1630 patients were included in the qualitative synthesis. Twelve studies investigated the use of PET scans for interim response evaluation (during NAC) and 10 studies assessed post-treatment PET evaluation (after NAC). The most widely evaluated parameter distinguishing metabolic responders from poor responders on interim or post-treatment PET scans was %ΔSUVmax, defined as the percent reduction of SUVmax compared to baseline PET, followed by SUVmax and complete metabolic response (CMR). For the 17 studies included in the meta-analysis, the pooled HR of metabolic responses on DFS was 0.21 (95% confidence interval [CI], 0.14–0.32) for interim PET scans and 0.31 (95% CI, 0.21–0.46) for post-treatment PET scans. Regarding the influence of metabolic responses on OS, the pooled HRs for interim and post-treatment PET scans were 0.20 (95% CI, 0.09–0.44) and 0.26 (95% CI, 0.14–0.51), respectively.

Conclusions

The currently available literature suggests that the use of ¹⁸F-FDG PET or PET/CT for evaluation of response to NAC provides significant predictive value for disease recurrence and survival in breast cancer patients and might allow risk stratification and guide rational management.

Quantifying bias and precision of kinetic parameter estimation on the PennPET Explorer, a long axial field-of-view scanner

Long axial field-of-view (AFOV) PET scanners allow for full-body dynamic imaging in a single bed-position at very high sensitivity. However, the benefits for kinetic parameter estimation have yet to be studied. This work uses (1) a dynamic GATE simulation of [¹⁸F]-fluorothymidine (FLT) in a modified NEMA IQ phantom and (2) a lesion embedding study of spheres in a dynamic [¹⁸F]-fluorodeoxyglucose (FDG) human subject imaged on the PennPET Explorer. Both studies were designed using published kinetic data of lung and liver cancers and modeled using two tissue compartments. Data were reconstructed at various emulated doses. Sphere time-activity curves (TACs) were measured on resulting dynamic images, and TACs were fit using a two-tissue-compartment model (k₄ ≠ 0) for the FLT study and both a two-tissue-compartment model (k₄ = 0) and Patlak graphical analysis for the FDG study to estimate flux (K_i) and delivery (K₁) parameters. Quantification of flux and K1 shows lower bias and better precision for both radiotracers on the long AFOV scanner, especially at low doses. Dynamic imaging on a long AFOV system can be achieved for a greater range of injected doses, as low as 0.5-2 mCi depending on the sphere size and flux, compared to a standard AFOV scanner, while maintaining good kinetic parameter estimation.

Dynamic FDG-PET/CT in the Initial Staging of Primary Breast Cancer: Clinicopathological Correlations

Our aim was to evaluate correlation between clinicopathological features (clinical T and clinical N stages; histological type; nuclear grade; hormone-receptor and HER2 status, proliferation activity and tumor subtypes) of breast cancer and kinetic parameters measured by staging dynamic FDG-PET/CT examinations. Following ethical approval and patients’ informed consent we included 34 patients with 35 primary breast cancers in our prospective study. We performed dynamic PET imaging, and assessed plasma activity noninvasively. To delineate primary tumors we applied a frame-by-frame semi-automatic software-based correction of motion artefacts. FDG two-compartment kinetic modelling was applied to assess K1, k2, k3 rate coefficients and to calculate Ki (tracer flux constant) and MRFDG (FDG metabolic rate). We found that k3, Ki and MRFDG were significantly higher in higher grade (p = 0.0246, 0.0089 and 0.0076, respectively), progesterone-receptor negative (p = 0.0344, 0.0217 and 0.0132) and highly-proliferating (p = 0.0414, 0.0193 and 0.0271) tumors as well as in triple-negative and hormone-receptor negative/HER2-positive subtypes (p = 0.0310, 0.0280 and 0.0186). Ki and MRFDG were significantly higher in estrogen-receptor negative tumors (p = 0.0300 and 0.0247, respectively). Ki was significantly higher in node-positive than in node-negative disease (p = 0.0315). None of the assessed FDG-kinetic parameters showed significant correlation with stromal TIL. In conclusion, we confirmed a significant relationship between kinetic parameters measured by dynamic PET and the routinely assessed clinicopathological factors of breast cancer: high-grade, hormone-receptor negative tumors with high proliferation rate are characterized by higher cellular FDG-uptake and FDG-phosphorylation rate. Furthermore, we found that kinetic parameters based on the dynamic examinations are probably not influenced by stromal TIL infiltration.

Comparison of different motion correction techniques for dynamic FDG-PET/CT studies in breast cancer patients

BACKGROUND

Our aim was to evaluate interchangeability of different motion correction methods in the assessment of dynamic FDG-PET/CT studies in breast cancer patients as well as to assess the interrater reliability of these methods.

METHODS

In our prospective study we included patients with malignant breast tumours. Dynamic PET acquisition lasted for 60 minutes after tracer (FDG) injection. Every study was assessed by the same two experienced observers. We assessed plasma activity noninvasively. In case of the primary tumour VOIs we applied two different approaches to correct motion artefacts: method I) frame-by-frame manual motion correction; method II) frame-by-frame semi-automatic software-based motion correction. FDG two-compartment kinetic modelling was applied to assess K<inf>1</inf>, k<inf>2</inf>, k<inf>3</inf> rate coefficients and to calculate K<inf>i</inf> (tracer flux constant) and MRFDG (FDG metabolic rate).

RESULTS

Thirty-five lesions detected during 34 dynamic studies were included in this current analysis. Interrater reliability of both applied motion correction methods proved to be excellent (ICC=0.89-0.99), except K<inf>i</inf> measured by method I (ICC=0.66). Bland-Altman analysis revealed that method II resulted in significantly lower values than method I regarding k<inf>3</inf> and K<inf>i</inf> in case of both observers, and regarding MRFDG in one of the observers. In case of K<inf>1</inf> and k<inf>2</inf> the two methods were in good agreement.

CONCLUSIONS

Both applied methods proved to be reproducible and reliable, especially method II, where every measured kinetic parameter showed excellent interrater reliability. Different approaches of motion correction could have a significant effect on the results of the kinetic modelling; therefore careful selection of the most reliable method is advised.

Hyperpolarized 13C MRI: Path to Clinical Translation in Oncology

This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging's (MRI's) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.

Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer

Late-phase clinical trials investigating metformin as a cancer therapy are underway. However, there remains controversy as to the mode of action of metformin in tumors at clinical doses. We conducted a clinical study integrating measurement of markers of systemic metabolism, dynamic FDG-PET-CT, transcriptomics, and metabolomics at paired time points to profile the bioactivity of metformin in primary breast cancer. We show metformin reduces the levels of mitochondrial metabolites, activates multiple mitochondrial metabolic pathways, and increases 18-FDG flux in tumors. Two tumor groups are identified with distinct metabolic responses, an OXPHOS transcriptional response (OTR) group for which there is an increase in OXPHOS gene transcription and an FDG response group with increased 18-FDG uptake. Increase in proliferation, as measured by a validated proliferation signature, suggested that patients in the OTR group were resistant to metformin treatment. We conclude that mitochondrial response to metformin in primary breast cancer may define anti-tumor effect.

Dynamic whole-body PET imaging: principles, potentials and applications

PURPOSE

In this article, we discuss dynamic whole-body (DWB) positron emission tomography (PET) as an imaging tool with significant clinical potential, in relation to conventional standard uptake value (SUV) imaging.

BACKGROUND

DWB PET involves dynamic data acquisition over an extended axial range, capturing tracer kinetic information that is not available with conventional static acquisition protocols. The method can be performed within reasonable clinical imaging times, and enables generation of multiple types of PET images with complementary information in a single imaging session. Importantly, DWB PET can be used to produce multi-parametric images of (i) Patlak slope (influx rate) and (ii) intercept (referred to sometimes as "distribution volume"), while also providing (iii) a conventional 'SUV-equivalent' image for certain protocols.

RESULTS

We provide an overview of ongoing efforts (primarily focused on FDG PET) and discuss potential clinically relevant applications.

CONCLUSION

Overall, the framework of DWB imaging [applicable to both PET/CT(computed tomography) and PET/MRI (magnetic resonance imaging)] generates quantitative measures that may add significant value to conventional SUV image-derived measures, with limited pitfalls as we also discuss in this work.

Practical Clinical Measurement of Radiotracer Concentration in Blood: Initial Device Concept and Feasibility Testing

Kinetic analysis of PET data requires continuous measurement of radioactivity in the arterial blood throughout the acquisition time, termed the arterial input function. The arterial input function is used as an input to compartmental modeling, which can be a better predictor of disease progression than SUV measurements from static PET images. Current common methods of measuring blood concentrations include image-derived, population-based, and manual sampling. These all have challenges due to logistical and technologic issues, as well as patient burden. The aim of this study was to design, develop, and assess a device that is practical and effective for the routine measurement of β-emitting radiotracer concentration in blood without the drawbacks of current methods and for which metabolite analysis is not required. Methods: Designs that integrated a scintillating fiber and a silicon photomultiplier with a general-purpose venous access catheter for in vivo measurement were considered. Other design requirements included miniaturization, high sampling rates, and stopping power for β-particles. Preliminary prototypes were designed to test the feasibility of the concept. Phantom tests were developed to mimic human vasculature. Tests of linearity, sensitivity, signal-to-noise ratios, the impact of vein diameter, and the influence of γ-radiation were conducted. Results: Prototype sensors were constructed using 2 different diameters of polystyrene-based scintillating fibers. Fibers were custom-polished and fixed to a silicon photomultiplier. Sensor output was linear, with R ² = 0.999 over the range from 0.037 to 9.25 MBq/mL. Absolute sensitivity was approximately 450 counts per second per MBq/mL. Measured signal-to-noise ratios ranged from 1.2:1 to 3.2:1 using a blood-to-tissue concentration ratio of 1:1. Sensor output increased with vein diameter and showed no sensitivity to γ-radiation. Conclusion: In experiments with phantom models, the prototype provided accurate measurements of β-emitting radiotracer concentration. The design will be refined for in vivo testing. The ability to routinely gather blood input function data would facilitate the adoption of kinetic modeling of PET data.

How Long of a Dynamic 3'-Deoxy-3'-[18F]fluorothymidine ([18F]FLT) PET Acquisition Is Needed for Robust Kinetic Analysis in Breast Cancer?

PURPOSE

To quantitatively evaluate the minimally required scanning time of 3'-deoxy-3'-[¹⁸F]fluorothymidine ([¹⁸F]FLT) positron emission tomography (PET) dynamic acquisition for accurate kinetic assessment of the proliferation in breast cancer tumors.

PROCEDURES

Within a therapeutic intervention trial, 26 breast tumors of 8 breast cancer patients were analyzed from 30-min dynamic [¹⁸F]FLT-PET acquisitions. PET/CT was acquired on a Gemini TF 64 system (Philips Healthcare) and reconstructed into 26 frames (8 × 15 s, 6 × 30 s, 5 × 1 min, 5 × 2 min, and 2 × 5 min). Maximum activity concentrations (Bq/ml) of volume of interests over tumors and plasma in descending aorta were obtained over time frames. Kinetic parameters were estimated using in-house developed software with the two-tissue three-compartment irreversible model (2TCM) (K₁, k₂, k₃, and K_i; k₄ = 0) and Patlak model (K_i) based on different acquisition durations (T_d) (10, 12, 14, 16, 20, 25, and 30 min, separately). Different linear regression onset time (T₀) points (1, 2, 3, 4, and 5 min) were applied in Patlak analysis. K_i of the 30-min data set was taken as the gold standard for comparison. Pearson product-moment correlation coefficient (R) of 0.9 was chosen as a limit for the correlation.

RESULTS

The correlation of kinetic parameters between the gold standard and the abbreviated dynamic data series increased with longer T_d from 10 to 30 min. k₂ and k₃ using 2TCM and K_i using Patlak model revealed poor correlations for dynamic PET with T_d ≤ 14 min (k₂: R = 0.84, 0.85, 0.86; k₃: R = 0.67, 0.67, 0.67; K_i: R = 0.72, 0.78, 0.87 at T_d = 10, 12, and 14 min, respectively). Excellent correlations were shown for all kinetic parameters when T_d ≥ 16 min regardless of the kinetic model and T₀ value (R > 0.9).

CONCLUSIONS

This study indicates that a 16-min dynamic PET acquisition appears to be sufficient to provide accurate [¹⁸F]FLT kinetics to quantitatively assess the proliferation in breast cancer lesions.

Prediction of tumor differentiation using sequential PET/CT and MRI in patients with breast cancer

OBJECTIVE

The aim of this study is to assess tumor differentiation using parameters from sequential positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) in patients with breast cancer.

METHODS

This retrospective study included 78 patients with breast cancer. All patients underwent sequential PET/CT and MRI. For fluorodeoxyglucose (FDG)-PET image analysis, the maximum standardized uptake value (SUV_max) of FDG was assessed at both 1 and 2 h and metabolic tumor volume (MTV) and total lesion glycolysis (TLG). The kinetic analysis of dynamic contrast-enhanced MRI parameters was performed using dynamic enhancement curves. We assessed diffusion-weighted imaging (DWI)-MRI parameters regarding apparent diffusion coefficient (ADC) values. Histologic grades 1 and 2 were classified as low-grade, and grade 3 as high-grade tumor.

RESULTS

Forty-five lesions of 78 patients were classified as histologic grade 3, while 26 and 7 lesions were grade 2 and grade 1, respectively. Patients with high-grade tumors showed significantly lower ADC-mean values than patients with low-grade tumors (0.99 ± 0.19 vs.1.12 ± 0.32, p = 0.007). With respect to SUV_max1, MTV2.5, and TLG2.5, patients with high-grade tumors showed higher values than patients with low-grade tumors: SUV_max1 (7.92 ± 4.5 vs.6.19 ± 3.05, p = 0.099), MTV2.5 (7.90 ± 9.32 vs.4.38 ± 5.10, p = 0.095), and TLG2.5 (40.83 ± 59.17 vs.19.66 ± 26.08, p = 0.082). However, other parameters did not reveal significant differences between low-grade and high-grade malignancies. In receiver-operating characteristic (ROC) curve analysis, ADC-mean values showed the highest area under the curve of 0.681 (95%CI 0.566-0.782) for assessing high-grade malignancy.

CONCLUSIONS

Lower ADC-mean values may predict the poor differentiation of breast cancer among diverse PET-MRI functional parameters.

Inter-operator variability in compartmental kinetic analysis of 18F-fluoromisonidazole dynamic PET

PURPOSE

To assess the inter-operator variability in compartment analysis (CA) of dynamic-FMISO (dyn-FMISO) PET.

METHODS

Study-I: Five investigators conducted CA for 23 NSCLC dyn-FMISO tumor time-activity-curves. Study-II: Four operators performed CA for four NSCLC dyn-FMISO datasets. Repeatability of Kinetic-Rate-Constants (KRCs) was assessed.

RESULTS

Study-I: Strong correlation (ICC > 0.9) and interchangeable results among operators existed for all KRCs. Study-II: Up to 103% variability in tumor segmentation, and weaker ICC in KRCs (ICC-V_B = 0.53; ICC-K₁ = 0.91; ICC-K₁/k₂ = 0.25; ICC-k3 = 0.32; ICC-K_i = 0.54) existed. All KRCs were repeatable among the different operators.

CONCLUSIONS

Inter-operator variability in CA of dyn-FMISO was shown to be within statistical errors.

Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients

Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with O15-labeled water (H2O) and F18-labeled fluorodeoxyglucose (FDG) has been shown to be a promising diagnostic for locally advanced breast cancer (LABCa) patients. The mismatch measurement involves kinetic analysis with the arterial blood time course (AIF) as an input function. We evaluate the use of a statistical method for AIF extraction (SAIF) in these studies. Fifty three LABCa patients had dynamic PET studies with H2O and FDG. For each PET study, two AIFs were recovered, an SAIF extraction and also a manual extraction based on a region of interest placed over the left ventricle (LV-ROI). Blood flow-metabolism mismatch was obtained with each AIF, and kinetic and prognostic reliability comparisons were made. Strong correlations were found between kinetic assessments produced by both AIFs. SAIF AIFs retained the full prognostic value, for pathologic response and overall survival, of LV-ROI AIFs.

Dynamic 2-Deoxy-2-[18F]Fluoro-D-Glucose Positron Emission Tomography for Chemotherapy Response Monitoring of Breast Cancer Xenografts

PURPOSE

Non-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography ([¹⁸F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens.

PROCEDURES

Sixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [¹⁸F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUV_E and SUV_L, respectively); the rate constants k ₁, k ₂, and k ₃, and the intravascular fraction v _B were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response.

RESULTS

Treatment responders had significantly larger perfusion-related parameters (k ₁ and k ₂) and lower metabolism-related parameter (k ₃) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k ₁ and k ₂ at day 10 and changes in k ₃ explained most of the variability in response to therapy, whereas SUV_L and particularly SUV_E were of lesser importance.

CONCLUSIONS

Overall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [¹⁸F]FDG uptake such as SUV_E and SUV_L apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.

Multiparametric Imaging of Tumor Hypoxia and Perfusion with 18F-Fluoromisonidazole Dynamic PET in Head and Neck Cancer

Tumor hypoxia and perfusion are independent prognostic indicators of patient outcome. We developed the methodology for and investigated the utility of multiparametric imaging of tumor hypoxia and perfusion with ¹⁸F-fluoromisonidazole (¹⁸F-FMISO) dynamic PET (dPET) in head and neck cancer. Methods: One hundred twenty head and neck cancer patients underwent 0- to 30-min ¹⁸F-FMISO dPET in a customized immobilization mask, followed by 10-min static acquisitions starting at 93 ± 6 and 160 ± 13 min after injection. A total of 248 lesions (≥2 cm³) were analyzed. Voxelwise pharmacokinetic modeling was conducted using an irreversible 1-plasma 2-tissue-compartment model to calculate surrogate biomarkers of tumor hypoxia (k₃), perfusion (K₁), and ¹⁸F-FMISO distribution volume. The analysis was repeated with truncated dPET datasets. Results: Substantial inter- and intratumor heterogeneity was observed for all investigated metrics. Equilibration between the blood and unbound ¹⁸F-FMISO was rapid in all tumors. ¹⁸F-FMISO distribution volume deviated from the expected value of unity, causing discrepancy between k₃ maps and total ¹⁸F-FMISO uptake and reducing the dynamic range of total ¹⁸F-FMISO uptake for quantifying the degree of hypoxia. Both positive and negative trends between hypoxia and perfusion were observed in individual lesions. All investigated metrics were reproducible when calculated from a truncated 20-min dataset. Conclusion:¹⁸F-FMISO dPET provides the data necessary to generate parametric maps of tumor hypoxia, perfusion, and radiotracer distribution volume. These data clarify the ambiguity in interpreting ¹⁸F-FMISO uptake and improve the characterization of lesions. We show total acquisition times can be reduced to 20 min, facilitating the translation of ¹⁸F-FMISO dPET into the clinic.

Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach

In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic ¹⁸F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical ¹⁸F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic ¹⁸F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic ¹⁸F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor heterogeneity using dynamic PET studies. Because SC tumor segmentation is based on the intrinsic structure of the underlying data, it can be easily applied to other cancer types as well.

Molecular Imaging and Precision Medicine in Breast Cancer

Precision medicine, basing treatment approaches on patient traits and specific molecular features of disease processes, has an important role in the management of patients with breast cancer as targeted therapies continue to improve. PET imaging offers noninvasive information that is complementary to traditional tissue biomarkers, including information about tumor burden, tumor metabolism, receptor status, and proliferation. Several PET agents that image breast cancer receptors can visually demonstrate the extent and heterogeneity of receptor-positive disease and help predict which tumors are likely to respond to targeted treatments. This review presents applications of PET imaging in the targeted treatment of breast cancer.

Understanding and effectively addressing breast cancer in African American women: Unpacking the social context

Black women have a higher incidence of breast cancer before the age of 40 years, more severe disease at all ages, and an elevated mortality risk in comparison with white women. There is limited understanding of the contribution of social factors to these patterns. Elucidating the role of the social determinants of health in breast cancer disparities requires greater attention to how risk factors for breast cancer unfold over the lifecourse and to the complex ways in which socioeconomic status and racism shape exposure to psychosocial, physical, chemical, and other individual and community-level assaults that increase the risk of breast cancer. Research that takes seriously the social context in which black women live is also needed to maximize the opportunities to prevent breast cancer in this underserved group. Cancer 2016;122:2138-49. © 2016 American Cancer Society.