Why harmonization is needed when using FDG PET/CT as a prognosticator: demonstration with EARL-compliant SUV as an independent prognostic factor in lung cancer

Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value

BACKGROUND

PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA.

METHODS

This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC).

RESULTS

67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients.

CONCLUSION

Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out.

A simple nomogram for predicting occult lymph node metastasis of non-small cell lung cancer from preoperative computed tomography findings, including the volume-doubling time

PURPOSE

Latent lymph node metastasis is a clinical concern in the surgical treatment of non-small cell lung cancer (NSCLC). The present study identified a simple tool, including the volume-doubling time (VDT), for evaluating the risk of nodal metastasis.

METHODS

We reviewed, retrospectively, 560 patients who underwent radical resection for cN0M0 NSCLC. The whole tumor VDT and solid component VDT (SVDT) for differentiating the histological type and adenocarcinoma subtype were analyzed and a nomogram was constructed using variables selected through a stepwise selection method. The model was assessed through a calibration curve and decision curve analysis (DCA).

RESULTS

Lymph node metastases were detected in 89 patients (15.9%). The SVDT tended to be longer in patients with adenocarcinoma (294.5 days, p < 0.0001) than in those with other histological types of NSCLC, but was shorter when the solid/micropapillary component was predominant (127.0 days, p < 0.0001). The selected variables (tumor location, solid component diameter, consolidation tumor ratio, SVDT, and carcinoembryonic antigen) demonstrated significant differences and were used for the nomogram. The calibration curve indicated consistency, and the DCA showed validity across most threshold ranges from 0 to 68%.

CONCLUSIONS

The established nomogram is a useful tool for the preoperative prediction of lymph node metastasis, and the SVDT was the most influential factor in the nomogram.

Enhancing Interoperability and Harmonisation of Nuclear Medicine Image Data and Associated Clinical Data

Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions.

Comparative analysis of batch correction methods for FDG PET/CT using metabolic radiogenomic data of lung cancer patients

In radiomics research, the issue of different instruments being used is significant. In this study, we compared three correction methods to reduce the batch effects in radiogenomic data from fluorodeoxyglucose (FDG) PET/CT images of lung cancer patients. Texture features of the FDG PET/CT images and genomic data were retrospectively obtained. The features were corrected with different methods: phantom correction, ComBat method, and Limma method. Batch effects were estimated using three analytic tools: principal component analysis (PCA), the k-nearest neighbor batch effect test (kBET), and the silhouette score. Finally, the associations of features and gene mutations were compared between each correction method. Although the kBET rejection rate and silhouette score were lower in the phantom-corrected data than in the uncorrected data, a PCA plot showed a similar variance. ComBat and Limma methods provided correction with low batch effects, and there was no significant difference in the results of the two methods. In ComBat- and Limma-corrected data, more texture features exhibited a significant association with the TP53 mutation than in those in the phantom-corrected data. This study suggests that correction with ComBat or Limma methods can be more effective or equally as effective as the phantom method in reducing batch effects.

The Medical Informatics Initiative and the Network University Medicine - Perspectives for Nuclear Medicine

Digitization in the healthcare sector and the support of clinical workflows with artificial intelligence (AI), including AI-supported image analysis, represent a great challenge and equally a promising perspective for preclinical and clinical nuclear medicine. In Germany, the Medical Informatics Initiative (MII) and the Network University Medicine (NUM) are of central importance for this transformation. This review article outlines these structures and highlights their future role in enabling privacy-preserving federated multi-center analyses with interoperable data structures harmonized between site-specific IT infrastructures. The newly founded working group "Digitization and AI" in the German Society of Nuclear Medicine (DGN) as well as the Fach- und Organspezifische Arbeitsgruppe (FOSA, specialty- and organ-specific working group) founded for the field of nuclear medicine (FOSA Nuklearmedizin) within the NUM aim to initiate and coordinate measures in the context of digital medicine and (image-)data-driven analyses for the DGN.

A machine learning tool to improve prediction of mediastinal lymph node metastases in non-small cell lung cancer using routinely obtainable [18F]FDG-PET/CT parameters

BACKGROUND

In patients with non-small cell lung cancer (NSCLC), accuracy of [18F]FDG-PET/CT for pretherapeutic lymph node (LN) staging is limited by false positive findings. Our aim was to evaluate machine learning with routinely obtainable variables to improve accuracy over standard visual image assessment.

METHODS

Monocentric retrospective analysis of pretherapeutic [18F]FDG-PET/CT in 491 consecutive patients with NSCLC using an analog PET/CT scanner (training + test cohort, n = 385) or digital scanner (validation, n = 106). Forty clinical variables, tumor characteristics, and image variables (e.g., primary tumor and LN SUVmax and size) were collected. Different combinations of machine learning methods for feature selection and classification of N0/1 vs. N2/3 disease were compared. Ten-fold nested cross-validation was used to derive the mean area under the ROC curve of the ten test folds ("test AUC") and AUC in the validation cohort. Reference standard was the final N stage from interdisciplinary consensus (histological results for N2/3 LNs in 96%).

RESULTS

N2/3 disease was present in 190 patients (39%; training + test, 37%; validation, 46%; p = 0.09). A gradient boosting classifier (GBM) with 10 features was selected as the final model based on test AUC of 0.91 (95% confidence interval, 0.87-0.94). Validation AUC was 0.94 (0.89-0.98). At a target sensitivity of approx. 90%, test/validation accuracy of the GBM was 0.78/0.87. This was significantly higher than the accuracy based on "mediastinal LN uptake > mediastinum" (0.7/0.75; each p < 0.05) or combined PET/CT criteria (PET positive and/or LN short axis diameter > 10 mm; 0.68/0.75; each p < 0.001). Harmonization of PET images between the two scanners affected SUVmax and visual assessment of the LNs but did not diminish the AUC of the GBM.

CONCLUSIONS

A machine learning model based on routinely available variables from [18F]FDG-PET/CT improved accuracy in mediastinal LN staging compared to established visual assessment criteria. A web application implementing this model was made available.

Evaluation of Data-Driven Respiration Gating in Continuous Bed Motion in Lung Lesions

Respiration gating is used in PET to prevent image quality degradation due to respiratory effects. In this study, we evaluated a type of data-driven respiration gating for continuous bed motion, OncoFreeze AI, which was implemented to improve image quality and the accuracy of semiquantitative uptake values affected by respiratory motion. Methods: ¹⁸F-FDG PET/CT was performed on 32 patients with lung lesions. Two types of respiration-gated images (OncoFreeze AI with data-driven respiration gating, device-based amplitude-based OncoFreeze with elastic motion compensation) and ungated images (static) were reconstructed. For each image, we calculated SUV and metabolic tumor volume (MTV). The improvement rate (IR) from respiration gating and the contrast-to-noise ratio (CNR), which indicates the improvement in image noise, were also calculated for these indices. IR was also calculated for the upper and lower lobes of the lung. As OncoFreeze AI assumes the presence of respiratory motion, we examined quantitative accuracy in regions where respiratory motion was not present using a ⁶⁸Ge cylinder phantom with known quantitative accuracy. Results: OncoFreeze and OncoFreeze AI showed similar values, with a significant increase in SUV and decrease in MTV compared with static reconstruction. OncoFreeze and OncoFreeze AI also showed similar values for IR and CNR. OncoFreeze AI increased SUV_max by an average of 18% and decreased MTV by an average of 25% compared with static reconstruction. From the IR results, both OncoFreeze and OncoFreeze AI showed a greater IR from static reconstruction in the lower lobe than in the upper lobe. OncoFreeze and OncoFreeze AI increased CNR by 17.9% and 18.0%, respectively, compared with static reconstruction. The quantitative accuracy of the ⁶⁸Ge phantom, assuming a region of no respiratory motion, was almost equal for the static reconstruction and OncoFreeze AI. Conclusion: OncoFreeze AI improved the influence of respiratory motion in the assessment of lung lesion uptake to a level comparable to that of the previously launched OncoFreeze. OncoFreeze AI provides more accurate imaging with significantly larger SUVs and smaller MTVs than static reconstruction.

A review of harmonization strategies for quantitative PET

PET can reveal in vivo biological processes at the molecular level. PET-derived quantitative values have been used as a surrogate marker for clinical decision-making in numerous clinical studies and trials. However, quantitative values in PET are variable depending on technical, biological, and physical factors. The variability may have a significant impact on a study outcome. Appropriate scanner calibration and quality control, standardization of imaging protocols, and any necessary harmonization strategies are essential to make use of PET as a biomarker with low bias and variability. This review summarizes benefits, limitations, and remaining challenges for harmonization of quantitative PET, including whole-body PET in oncology, brain PET in neurology, PET/MR, and non-¹⁸F PET imaging. This review is expected to facilitate harmonization of quantitative PET and to promote the contribution of PET-derived biomarkers to research and development in medicine.

Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis

PURPOSE

This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC).

METHODS

A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software.

RESULTS

13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis.

CONCLUSION

Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.

Prediction of the Presence of Targetable Molecular Alteration(s) with Clinico-Metabolic 18 F-FDG PET Radiomics in Non-Asian Lung Adenocarcinoma Patients

This study aimed to investigate if combining clinical characteristics with pre-therapeutic 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) radiomics could predict the presence of molecular alteration(s) in key molecular targets in lung adenocarcinoma. This non-interventional monocentric study included patients with newly diagnosed lung adenocarcinoma referred for baseline PET who had tumour molecular analyses. The data were randomly split into training and test datasets. LASSO regression with 100-fold cross-validation was performed, including sex, age, smoking history, AJCC cancer stage and 31 PET variables. In total, 109 patients were analysed, and it was found that 63 (57.8%) patients had at least one molecular alteration. Using the training dataset (n = 87), the model included 10 variables, namely age, sex, smoking history, AJCC stage, excessKustosis_HISTO, sphericity_SHAPE, variance_GLCM, correlation_GLCM, LZE_GLZLM, and GLNU_GLZLM. The ROC analysis for molecular alteration prediction using this model found an AUC equal to 0.866 (p < 0.0001). A cut-off value set to 0.48 led to a sensitivity of 90.6% and a positive likelihood ratio (LR+) value equal to 2.4. After application of this cut-off value in the unseen test dataset of patients (n = 22), the test presented a sensitivity equal to 90.0% and an LR+ value of 1.35. A clinico-metabolic 18 F-FDG PET phenotype allows the detection of key molecular target alterations with high sensitivity and negative predictive value. Hence, it opens the way to the selection of patients for molecular analysis.

The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer

The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUV_max and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.

Influences on PET Quantification and Interpretation

Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology-both imaging hardware and reconstruction software-into clinical care, we now find ourselves in a transition period in which traditional and new technologies coexist. The effects on the clinical value of PET imaging and its interpretation in routine clinical practice require careful reevaluation. In this review, we provide a comprehensive summary of important factors influencing quantification and interpretation with a focus on recent developments in PET technology. Finally, we discuss the relationship between quantitative accuracy and subjective image interpretation.

What validation tests can be done by the clinical medical physicist while waiting for the standardization of quantitative SPECT/CT imaging?

OBJECTIVE

The aim of the study was to assess the accuracy of quantitative SPECT/CT imaging in a clinical setting and to compare test results from two nuclear medicine departments.

METHODS

Phantom studies were carried out with two gamma cameras manufactured by GE Healthcare: Discovery NM/CT 670 and NM/CT 850, used in two nuclear medicine departments. The data were collected using a cylindrical uniform phantom and a NEMA/IEC NU2 Body Phantom, filled with ^99mTc-pertechnetate.

RESULTS

The convergence of activity concentration recovery was validated for the two gamma cameras operating in two medical centers using the cylindrical uniform phantom. The comparison of results revealed a 5% difference in the background calibration factor Bg. cal; 6% difference in COV, and a 0.6% difference in total activity deviation ∆A_tot. Recovery coefficients (RC_max) for activity concentration in spheres of the NEMA/IEC NU2 Body Phantom were measured for different image reconstruction techniques. RC_max was in the range of 0.2-0.4 for the smallest sphere (ϕ 10 mm), and 1.3-1.4 for the largest sphere (ϕ 37 mm). Conversion factors for SUVmax and SUVmean for the gamma camera systems used were 0.99 and 1.13, respectively.

CONCLUSIONS

(1) Measurements taken in our study confirmed the clinical suitability of 5 parameters of image quality (Bg. cal-background calibration factor, ∆A_tot-total activity deviation, COV-coefficient of variation used for image noise assessment, Q_H-hot contrast, AM-accuracy of measurements, or RC-recovery coefficient) for the validation of SPECT/CT system performance in terms of correct quantitative acquisitions of images. (2) This work shows that absolute SPECT/CT quantification is achievable in clinical nuclear medicine centers. Results variation of quantitative analyses between centers is mainly related to the use of different reconstruction methods. (3) It is necessary to standardize the technique of measuring the SUV conversion factor obtained with different SPECT/CT scanners.

Comparison between tumour metabolism derived from 18F-FDG PET/CT and accurate cytogenetic stratification in newly diagnosed multiple myeloma patients

Background

¹⁸F-fluorodeoxyglucose positron emission tomography integrated with computed tomography (¹⁸F-FDG PET/CT) is a useful tool for baseline staging in newly diagnosed multiple myeloma (MM) but also for prognostic stratification. This monocentric retrospective study aimed at examining the relation between baseline tumour metabolism assessed by ¹⁸F-FDG PET/CT and linear predictor (LP) score, a new cytogenetic stratification score.

Methods

From March 2012 to March 2019, 57 patients with newly diagnosed MM addressed to our institution for baseline ¹⁸F-FDG PET/CT were included. LP score was determined on systematic iliac crest bone marrow samples. Obtained on CD138-sorted bone marrow plasma cells, this recent composite cytogenetic stratification is a 6-marker based weighted score using fluorescence in situ hybridization (FISH) ± single nucleotide polymorphism (SNP) arrays. We compared quantitative metabolic parameters and LP score using a Kruskal-Wallis test and visual suspicion of diffuse bone marrow involvement (DBI; based on hepatic background as threshold of positivity) and cytogenetic data using a Chi-squared test.

Results

The distribution of total metabolic tumour volume (TMTV) and total lesion glycolysis (TLG) values among the three LP score categories was almost stochastic, with no significant association (P=0.70). Additionally, no significant association between TMTV/TLG and any of the six cytogenetic abnormalities included in LP score calculation. A significant association was found between visual high suspicion of DBI and LP score (P=0.036), and between this visual parameter and the presence of 1q gain (P=0.049).

Conclusions

There is no significant association between quantitative metabolic parameters assessed with ¹⁸F-FDG PET/CT and LP score in patients with newly diagnosed MM, suggesting a potential complementarity of these biomarkers for prognostic stratification. A significant association was found between high visual suspicion of DBI and LP score.

The ratio between the whole-body and primary tumor burden, measured on 18F-FDG PET/CT studies, as a prognostic indicator in advanced non-small cell lung cancer

Objective

To determine whether the whole-body tumor burden, as quantified by ¹⁸F-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT), is a prognostic indicator in advanced (stage III or IV) non-small cell lung cancer (NSCLC).

Materials and Methods

This was a prospective study in which we evaluated ¹⁸F-FDG PET/CT staging parameters to quantify tumor burdens in patients with stage III or IV NSCLC. The following parameters were evaluated for the whole body (including the primary tumor) and for the primary tumor alone, respectively: maximum standardized uptake volume (wbSUV_max and tuSUV_max); metabolic tumor volume (wbMTV and tuMTV); and total lesion glycolysis (wbTLG and tuTLG). To determine whether the ¹⁸F-FDG PET/CT parameters were associated with overall survival (OS) and progression-free survival (PFS), we evaluated the wbSUV_max/tuSUV_max, wbMTV/tuMTV, and wbTLG/tuTLG ratios.

Results

¹⁸F-FDG PET/CT was performed for staging in 52 patients who were followed for a median of 11.0 months (mean, 11.7 months). The estimated median PFS and OS were 9.6 months and 11.6 months, respectively. In the univariate analysis, OS was found to correlate significantly with wbTLG (hazard ratio [HR] = 1.001; 95% confidence interval [95 CI]: 1.000-1.001; p = 0.0361) and with the wbTLG/tuTLG ratio (HR = 1.705; 95% CI: 1.232-2.362; p = 0.0013). In the multivariate analysis, only the wbTLG/tuTLG ratio was independently associated with OS (HR = 1.660; 95% CI: 1.193-2.310; p = 0.0027).

Conclusion

The wbTLG/tuTLG ratio is an independent prognostic indicator of OS in advanced-stage NSCLC.

Baseline total metabolic tumour volume on 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography as a promising biomarker in patients with advanced non-small cell lung cancer treated with first-line pembrolizumab

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have become the standard of care in the management of advanced non-small cell lung cancer (NSCLC). Nevertheless, only a small proportion of patients benefit from ICIs. The aim of the present study is to assess whether 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography ([18F]FDG-PET/CT)-derived parameters may be used as biomarkers in patients with advanced NSCLC receiving first-line pembrolizumab.

MATERIALS AND METHODS

This is a monocentric retrospective cohort study including patients with advanced NSCLC (stage IV) and Programmed death-ligand 1 (PD-L1) expression ≥50% treated with pembrolizumab. A control group of patients treated with epidermal growth factor receptor (EGFR) inhibitors for EGFR-mutated NSCLC was also enrolled. Only patients with a positive [18F]18F-FDG PET/CT result within 60 days from treatment initiation were included.Total metabolic tumour volume (tMTV) was calculated for each lesion using a dedicated software (PET VCAR; GE Healthcare), which semiautomatically delineates the tumour's contours with a maximum standardised uptake value (SUVmax) threshold of 42% within the lesion. tMTV was obtained summing each lesion's MTV. Potential prognostic parameters for overall survival (OS) were analysed (tMTV, SUVmax, bone/liver metastasis, neutrophil:lymphocyte ratio ≥4, Eastern Cooperative Oncology Group performance status ≥2, lactate dehydrogenase above the upper limit of normal).

RESULTS

Overall, 34 patients treated with first line-pembrolizumab and 40 patients treated with EGFR tyrosine kinase inhibitors were included. In the pembrolizumab group, the median follow-up was 20.3, while the median OS was 4.7 months (95% confidence interval [CI] = 0.3-9.1) for patients with tMTV ≥75 cm³ vs not reached (NR) for patients with tMTV <75 cm³ (95% CI = NR-NR; hazard ratio [HR] = 5.37; 95% CI = 1.72-16.77; p = 0.004). No difference was found in the control group (HR = 1.43; 95% CI = 0.61-3.34; p = 0.411).

CONCLUSION

Our data suggest that tMTV ≥75cm³ can be used as a prognostic biomarker of poor outcomes in patients with PD-L1-high advanced NSCLC treated with first-line pembrolizumab. This information could be useful for the selection of patients who may require the addition of chemotherapy to pembrolizumab.

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume-wMTV, total lesion glycolysis-wTLG, higher standardized uptake volume maximum and mean-SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

Radiomics model of dual-time 2-[18F]FDG PET/CT imaging to distinguish between pancreatic ductal adenocarcinoma and autoimmune pancreatitis

OBJECTIVES

Pancreatic ductal adenocarcinoma (PDAC) and autoimmune pancreatitis (AIP) are diseases with a highly analogous visual presentation that are difficult to distinguish by imaging. The purpose of this research was to create a radiomics-based prediction model using dual-time PET/CT imaging for the noninvasive classification of PDAC and AIP lesions.

METHODS

This retrospective study was performed on 112 patients (48 patients with AIP and 64 patients with PDAC). All cases were confirmed by imaging and clinical follow-up, and/or pathology. A total of 502 radiomics features were extracted from the dual-time PET/CT images to develop a radiomics decision model. An additional 12 maximum intensity projection (MIP) features were also calculated to further improve the radiomics model. The optimal radiomics feature set was selected by support vector machine recursive feature elimination (SVM-RFE), and the final classifier was built using a linear SVM. The performance of the proposed dual-time model was evaluated using nested cross-validation for accuracy, sensitivity, specificity, and area under the curve (AUC).

RESULTS

The final prediction model was developed from a combination of the SVM-RFE and linear SVM with the required quantitative features. The multimodal and multidimensional features performed well for classification (average AUC: 0.9668, accuracy: 89.91%, sensitivity: 85.31%, specificity: 96.04%).

CONCLUSIONS

The radiomics model based on 2-[¹⁸F]fluoro-2-deoxy-D-glucose (2-[¹⁸F]FDG) PET/CT dual-time images provided promising performance for discriminating between patients with benign AIP and malignant PDAC lesions, which shows its potential for use as a diagnostic tool for clinical decision-making.

KEY POINTS

• The clinical symptoms and imaging visual presentations of PDAC and AIP are highly similar, and accurate differentiation of PDAC and AIP lesions is difficult. • Radiomics features provided a potential noninvasive method for differentiation of AIP from PDAC. • The diagnostic performance of the proposed radiomics model indicates its potential to assist doctors in making treatment decisions.

Harmonized pretreatment quantitative volume-based FDG-PET/CT parameters for prognosis of stage I-III breast cancer: Multicenter study

OBJECTIVES

This study investigated harmonized pretreatment volume-based quantitative FDG-PET/CT parameters in breast cancer patients for prognostic value.

RESULTS

During a median overall follow-up period of 5.3 years, 91 patients had recurrence and 40 died. Multivariate analysis of ER-positive/HER2-negative patients showed high maximum standardized uptake value (SUVmax) (p = 0.018), high total lesion glycolysis (TLG) (p = 0.010), and clinical N-classification (p = 0.0027) as independent negative predictors of RFS, while high maximum SUVmax (p = 0.037), advanced clinical T-classification (p = 0.030), and advanced TNM stage (p = 0.0067) were independent negative predictors of OS. For recurrence and death in HER2-positive patients, high total TLG (p = 0.037, p = 0.0048, respectively) and advanced TNM stage (p = 0.048, p = 0.046, respectively) were independent prediction factors. In the triple-negative group, independent factors related to recurrence and death were high maximum SUVmax (p = 0.0014, p = 0.0003, respectively) and advanced TNM stage (p < 0.0001, p < 0.0001, respectively).

MATERIALS AND METHODS

Records of 546 stage I-III invasive breast cancer patients, including 344 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, 110 HER2-positive, and 92 triple-negative cases, treated at four institutions were reviewed retrospectively. Harmonized primary tumor and nodal maximum SUVmax, metabolic tumor volume (MTV), and TLG indicated in pretreatment FDG-PET/CT results were analyzed. Evaluations of relationships of clinicopathological factors, volume-based quantitative parameters, recurrence-free survival (RFS), and overall survival (OS) for each subtype were performed with a Cox proportional hazards model and log-rank test.

CONCLUSIONS

The results indicated that potential surrogate markers for prognosis in patients with the three main subtypes of operable breast cancer include harmonized pretreatment quantitative volume-based FDG-PET/CT parameters, particularly whole-lesion SUVmax and TLG.

Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies

Background

Asphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies.

Methods

This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF_4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF_4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF_2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases.

Results

Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF_4/8, PSF + TOF_2/17, Q.Clear and the reference algorithm TOF_4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF_4/8, 2%; PSF + TOF_2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF_4/8, 38% reduced to 2%; PSF + TOF_2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s.

Conclusions

ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.

Combined dual energy and iterative metal artefact reduction for PET/CT in head and neck cancer

Metal artefacts in PET/CT images hamper diagnostic accuracy in head and neck cancer (HNC). The aim of this study is to characterise the clinical effects of metal artefacts on PET/CT in HNC and to inform decision-making concerning implementation of MAR techniques. We study a combined dual energy CT and inpainting-based metal artefact reduction (DECT-I-MAR) technique for PET/CT in three settings: (A) A dental phantom with a removable amalgam-filled tooth to evaluate the PET error in comparison to a known reference. (B) PET-positive patients with metallic implants to demostrate the relationship between CT metal artefacts and PET error. (C) Metabolic tumour volumes (MTVs) delineated in PET-positive patients with metal implants to evaluate the clinical impact. In (A) DECT-I-MAR reduced the PET error significantly. In (B) we demonstrate an increasing PET error with increasing CT artefact severity in patients. In (C) it is shown that the presence of artefacts in the same axial slices as the tumour significantly decrease biomarker stability and increase delineation variability. This work shows the practical feasibility of DECT-I-MAR based PET/CT imaging, and indicates a positive clinical impact of using the technique routinely for HNC patients. The impact of CT artefacts on PET is considerable, especially in workflows where quantitative PET biomarkers and tumour volumes are used. In such cases, and for patients with tumours in proximity of metals, we recommend that a MAR technique for PET/CT is employed.

FDG-PET biomarkers associated with long-term benefit from first-line immunotherapy in patients with advanced non-small cell lung cancer

OBJECTIVE

To determine FDG-PET biomarkers associated with long-term benefit (LTB) and survival in advanced non-small cell lung cancer (NSCLC) patients receiving first-line immunotherapy.

METHODS

In this multicenter study, we retrospectively analyzed advanced NSCLC patients with a PD-L1 tumor proportion score (TPS) ≥ 50%, who underwent FDG-PET/CT before first-line pembrolizumab, received from August 2017 to September 2019. Parameters extracted were SUVmax, SUVmean, TMTV (total metabolic tumor volume) and TLG (total lesion glycolysis). LTB was defined as objective (complete or partial) response or stable disease as best overall response, maintained for ≥ 12 months. A multivariate prediction model was developed using logistic regression for LTB and Cox models for progression-free survival (PFS) and overall survival (OS).

RESULTS

On the 63 eligible patients, with a median follow-up of 13.4 (range, 1.5-29.1) months, 17 (27%) had LTB. Median PFS and OS were 7.7 months (95%CI 5.0-10.5) and 12.1 months (95%CI 8.6-15.6). In multivariate analyses, high TMTV (> 84cm³) and high tumor SUVmean (> 10.1) remained independent factors for predicting LTB (OR 0.2; p = 0.03 and OR 3.7; p = 0.04) and PFS (HR 2.2; p = 0.02 and HR 0.5; p = 0.045). High TMTV was significantly associated with poor OS (HR 3.1; p = 0.03). No association was observed between tumor SUVmax or TLG and clinical outcomes.

CONCLUSIONS

In patients with advanced NSCLC and PD-L1 TPS ≥ 50%, baseline low TMTV and high tumor SUVmean correlate with survival and LTB from upfront pembrolizumab. Beyond the initial staging, FDG-PET/CT scan could provide relevant biomarkers associated with clinical outcomes that should be taken into account when considering first-line treatment options.

Maximum standardized uptake value of primary tumor (SUVmax_PT) and horizontal range between two most distant PET-positive lymph nodes predict patient outcome in inoperable stage III NSCLC patients after chemoradiotherapy

Background

18F-FDG-positron emission tomography (PET)/computed tomography (CT) is a standard for initial staging in patients with locally advanced stage III non-small cell lung cancer (NSCLC). We evaluated a PET/CT staging score to characterize disease extension and patient outcome in this disease.

Methods

Ninety-nine consecutive patients with NSCLC stage IIIA–B (UICC 7th edition), who underwent 18F-FDG-PET/CT before the start of chemoradiotherapy (CRT) were analyzed. Maximum standardized uptake value of primary tumor (SUVmax_PT) and range between two most distant PET-positive (SUV ≥2.5) lymph nodes in two directions were analyzed for their correlation with patient outcome. The vertical distance was defined as A- and the horizontal as a B-line.

Results

According to the results of univariate analysis, score included the SUVmax_PT and horizontal B-line, patients were divided into three risk subgroups: low, intermediate and high-risk subgroups. Subgroups were defined as SUVmax_PT <8 and B-line <3.7 cm, SUVmax_PT >8 or B-line >3.7 cm and SUVmax_PT >8 plus B-line >3.7 cm, respectively. Twenty-eight (28%), 45 (46%) and 26 (26%) patients were assigned to the low, intermediate and high-risk subgroup, respectively. Median event-free survival (EFS) in low, intermediate and high-risk subgroups was 16 (95% CI: 7–25), 13 (95% CI: 12–15) and 10 (95% CI: 7–13) months (P=0.002, log-rank test). Median OS in the low, intermediate and high-risk subgroups was 40 (95% CI: 11–69), 23 (95% CI: 15–31) and 14 (95% CI: 13–14) months (P=0.0001, log-rank test). In the multivariate analysis, SUV, B-line and PET/CT score were significantly associated with EFS [harard ratio (HR) 2.12 (95% CI: 1.27–3.55) and intermediate risk HR 2.01 (95% CI: 1.13–3.59), P=0.003] and OS [high-risk HR 2.79 (95% CI: 1.16–4.55) and intermediate risk HR 2.30 (95% CI: 1.58–4.94), P=0.001].

Conclusions

A PET/CT score was developed for inoperable stage III NSCLC patients treated with CRT and was an independent predictor of patient outcome in the single-center cohort.