Comparison of different automatic methods for the delineation of the total metabolic tumor volume in I-II stage Hodgkin Lymphoma

Towards improved diagnosis: radiomics and quantitative biomarkers in 18F-PSMA-1007 and 18F-fluorocholine PET/CT for prostate cancer recurrence

OBJECTIVE

This study compared the radiomic features and quantitative biomarkers of 18F-PSMA-1007 [prostate-specific membrane antigen (PSMA)] and 18F-fluorocholine (FCH) PET/computed tomography (CT) in prostate cancer patients with biochemical recurrence (BCR) enrolled in the phase 3, prospective, multicenter BIO-CT-001 trial.

METHODS

A total of 106 patients with BCR, who had undergone primary definitive treatment for prostate cancer, were recruited to this prospective study. All patients underwent one PSMA and one FCH PET/CT examination in randomized order within 10 days. They were followed up for a minimum of 6 months. Pathology, prostate-specific antigen (PSA), PSA doubling time, PSA velocity, and previous or ongoing treatment were analyzed. Using LifeX software, standardized uptake value (SUV) maximum, SUVmean, PSMA and choline total volume (PSMA-TV/FCH-TV), and total lesion PSMA and choline (TL-PSMA/TL-FCH) of all identified metastatic lesions in both tracers were calculated.

RESULTS

Of the 286 lesions identified, the majority 140 (49%) were lymph node metastases, 118 (41.2%) were bone metastases and 28 lesions (9.8%) were locoregional recurrences of prostate cancer. The median SUVmax value was significantly higher for 18F-PSMA compared with FCH for all 286 lesions (8.26 vs. 4.99, respectively, P < 0.001). There were statistically significant differences in median SUVmean, TL-PSMA/FCH, and PSMA/FCH-TV as per table 2 between the two radiotracers (4.29 vs. 2.92, 1.97 vs. 1.53, and 7.31 vs. 4.37, respectively, P < 0.001). The correlation between SUVmean/SUVmax and PSA level was moderate, both for 18F-PSMA (r = 0.44, P < 0.001; r = 0.44, P < 0.001) and FCH (r = 0.35, P < 0.001; r = 0.41, P < 0.001). TL-PSMA/FCH demonstrated statistically significant positive correlations with both PSA level and PSA velocity for both 18F-PSMA (r = 0.56, P < 0.001; r = 0.57, P < 0.001) and FCH (r = 0.49, P < 0.001; r = 0.51, P < 0.001). While patients who received hormone therapy showed higher median SUVmax values for both radiotracers compared with those who did not, the difference was statistically significant only for 18F-PSMA (P < 0.05).

CONCLUSION

Our analysis using both radiomic features and quantitative biomarkers demonstrated the improved performance of 18F-PSMA-1007 compared with FCH in identifying metastatic lesions in prostate cancer patients with BCR.

Exploring the applicability of a lesion segmentation method on [18F]fluorothymidine PET/CT images in diffuse large B-cell lymphoma

BACKGROUND AND PURPOSE

The determination of the total metabolic tumour volume based on [18F]fluorothymidine ([18F]FLT) PET/CT images in diffuse large B-cell lymphoma has a potential clinical value for detecting early relapse in this type of heterogeneous lymphoproliferative tumours. Tumour segmentation is a key step in this process. For this purpose, our objective was to determine a segmentation threshold of [18F]FLT PET/CT images, based on a reference tissue uptake, on a cohort of patients with diffuse large B-cell lymphoma (DLBCL) that have been scanned at different stages of the treatment.

METHODS

We enrolled 23 adult patients with DLBCL confirmed in II-IV stages without nervous system compromise. All patients were scanned using [18F]FLT PET/CT at the time of diagnosis (baseline PET), interim PET (iPET), and at the end of treatment (fPET). The administered activity was 1.8-2.6 MBq/kg body weight, performed 60-70 min after injection and without use of contrast-enhanced CT. First, we assessed the [18F]FLT uptake stability in liver and bone marrow along the patient follow-up. For the lesion segmentation, three threshold values were assessed.

RESULTS

Both, liver, and bone marrow can be indistinctly taken as reference tissue. The SUV threshold for a voxel to be considered as belonging to a lesion is expressed in terms of a percentage relative to the patient's uptake in the reference tissue. Found thresholds were: for liver, 62%, 33%, 27%; and for bone marrow, 35%, 21% and 22%, for baseline, iPET and fPET stages, respectively. The relative threshold throughout the treatment has a decreasing tendency along the stages.

CONCLUSION

Based on the results obtained with [18F]FLT PET/CT during staging and follow-up in patients with DLBCL, reference values were obtained for each stage referring to liver and bone marrow uptake that could be used in clinical practice oncology.

Prognostic value of the International Metabolic Prognostic Index for lymphoma patients receiving chimeric antigen receptor T-cell therapy

PURPOSE

Chimeric antigen receptor T-cell therapy (CART) prolongs survival for patients with relapsed/refractory B-cell non-Hodgkin's lymphoma. The recently introduced International Metabolic Prognostic Index (IMPI) was shown to improve prognostication in the first-line treatment of large B-cell lymphoma. Here, we investigate the prognostic value of the IMPI for progression-free (PFS) and overall survival (OS) in the setting of CD19 CART.

METHODS

Consecutively treated patients with baseline ¹⁸F-FDG PET/CT imaging and follow-up imaging at 30 days after CART were included. IMPI is composed of age, stage, and metabolic tumor volume (MTV) at baseline and was compared with the International Prognostic Index (IPI). Both indices were grouped into quartiles, as previously described for IPI. In addition, the continuous IMPI was subdivided into tertiaries for better separation of risk groups. Overall response rate (ORR), depth of response (DoR), and PFS were determined based on Lugano criteria. Proportional Cox regression analysis studied association of IMPI and IPI with PFS and OS.

RESULTS

Thirty-nine patients were included. The IPI was 1 in 23%, 2 in 21%, 3 in 26%, 4 in 21%, and 5 in 10% of the patients. IMPI^{low risk}, IMPI^{intermediate risk}, and IMPI^{high risk} patients had 30-day ORR of 69%, 62%, and 62% and 30-day DoR of - 67%, - 66%, and - 54% with a PFS of 187 days, 97 days, and 87 days, respectively. ORR and DoR showed no correlation with lower IMPI (r = 0.065, p = 0.697). Dividing patients into three risk groups showed a significant trend for PFS stratification (p = 0.030), while IPI did not (p = 0.133). Neither IPI nor IMPI yielded a significant association with OS after CART (both p > 0.05).

CONCLUSION

In the context of CART, the IMPI yielded prognostic value regarding PFS estimation. In contrast with IMPI in the first-line DLBCL setting, we did not observe a significant association of IMPI at baseline with OS after CART.

Technologist-Based Implementation of Total Metabolic Tumor Volume into Clinical Practice

Metabolic tumor volume (MTV) is defined as the total metabolically active tumor volume seen on ¹⁸F-FDG PET/CT examinations. Calculating MTV is often time-consuming, requiring a high degree of manual input. In this study, the MTV calculations of a board-certified nuclear radiologist were compared with those of 2 nuclear medicine technologists. As part of the technologists' educational program, after their classroom time they were trained by the radiologist for 30 min. The technologists calculated MTV within 7.5% of the radiologist's calculations in a set of patients who had diffuse large B-cell lymphoma and were undergoing initial staging ¹⁸F-FDG PET/CT. These findings suggest that nuclear medicine technologists may help accelerate implementation of MTV into clinical practice with favorable accuracy, possibly as an initial step followed by validation by the interpreting physician. The aim of this study was to explore whether efficiency is improved by integrating nuclear medicine technologists into a semiautomated workflow to calculate total MTV.

Clinical and Radiographic Predictors of Progression and Survival in Relapsed/Refractory Lymphoma Patients Receiving Anti-CD19 CAR T-cell Therapy

INTRODUCTION

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized treatment of relapsed/refractory (R/R) B-cell lymphomas, though certain patients do not respond to treatment or relapse afterwards. The purpose of this study is to determine patient variables that are predictive of response to CAR-T therapy.

METHODS

We conducted a retrospective review of 59 R/R B-cell non-Hodgkin lymphoma patients who received anti-CD19 CAR T-cell therapy. Risk factors for progression free survival (PFS) and overall survival (OS) were identified and multivariate logistic regression models for PFS and OS at 1 year were created using stepwise selection. The final multivariate logistic regression models were used to estimate the area under the receiver operating curve (AUROC).

RESULTS

At median follow up of 25.6 months, median overall survival was not reached, and median progression free survival was 5.7 months. Stage IV disease (odds ratio (OR) 9.335, P = .025) was identified as a predictive variable for progression at day 365 with an AUC of 0.7922 (P < .001). IPI (OR 2.828, P = .014), ALC ≥ 0.50 at collection (OR 0.183, P = .043), CRP ≥ 11 (OR 6.177, P = .019), and tocilizumab administration (OR 0.062, P = .005) as predictors for death at day 365 with an AUC 0.8626 (P < .001).

CONCLUSION

Clinical variables identify R/R lymphoma patients who are at risk for progression and poor overall survival after CAR T-cell therapy. IPI, CRP, ALC, and tocilizumab administration may be predictors of survival.

Prognostic value of genetic alterations and 18F-FDG PET/CT imaging features in diffuse large B cell lymphoma

The current standard front-line therapy for patients with diffuse large-B cell lymphoma (DLBCL)-rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP)-is found to be ineffective in up to one-third of them. Thus, their early identification is an important step towards testing alternative treatment options. In this retrospective study, we assessed the ability of ¹⁸F-FDG PET/CT imaging features (radiomic + PET conventional parameters) plus clinical data, alone or in combination with genomic parameters to predict complete response to first-line treatment. Imaging features were extracted from images prior treatment. Lesions were segmented as a whole to reflect tumor burden. Multivariate logistic regression predictive models for response to first-line treatment trained with clinical and imaging features, or with clinical, imaging, and genomic features were developed. For imaging feature selection, a manual selection approach or a linear discriminant analysis (LDA) for dimensionality reduction were applied. Confusion matrices and performance metrics were obtained to assess model performance. Thirty-three patients (median [range] age, 58 [49-69] years) were included, of whom 23 (69.69%) achieved long-term complete response. Overall, the inclusion of genomic features improved prediction ability. The best performance metrics were obtained with the combined model including genomic data and built applying the LDA method (AUC of 0.904, and 90% of balanced accuracy). The amplification of BCL6 was found to significantly contribute to explain response to first-line treatment in both manual and LDA models. Among imaging features, radiomic features reflecting lesion distribution heterogeneity (GLSZM_GrayLevelVariance, Sphericity and GLCM_Correlation) were predictors of response in manual models. Interestingly, when the dimensionality reduction was applied, the whole set of imaging features-mostly composed of radiomic features-significantly contributed to explain response to front-line therapy. A nomogram predictive for response to first-line treatment was constructed. In summary, a combination of imaging features, clinical variables and genomic data was able to successfully predict complete response to first-line treatment in DLBCL patients, with the amplification of BCL6 as the genetic marker retaining the highest predictive value. Additionally, a panel of imaging features may provide important information when predicting treatment response, with lesion dissemination-related radiomic features deserving especial attention.

Prospective Evaluation of Different Methods for Volumetric Analysis on [18F]FDG PET/CT in Pediatric Hodgkin Lymphoma

Rationale: Therapy response evaluation by 18F-fluorodeoxyglucose PET/CT (FDG PET) has become a powerful tool for the discrimination of responders from non-responders in pediatric Hodgkin lymphoma (HL). Recently, volumetric analyses have been regarded as a valuable tool for disease prognostication and biological characterization in cancer. Given the multitude of methods available for volumetric analysis in HL, the AIEOP Hodgkin Lymphoma Study Group has designed a prospective analysis of the Italian cohort enrolled in the EuroNet-PHL-C2 trial. Methods: Primarily, the study aimed to compare the different segmentation techniques used for volumetric assessment in HL patients at baseline (PET1) and during therapy: early (PET2) and late assessment (PET3). Overall, 50 patients and 150 scans were investigated for the current analysis. A dedicated software was used to semi-automatically delineate contours of the lesions by using different threshold methods. More specifically, four methods were applied: (1) fixed 41% threshold of the maximum standardized uptake value (SUVmax) within the respective lymphoma site (V41%), (2) fixed absolute SUV threshold of 2.5 (V2.5); (3) SUVmax(lesion)/SUVmean liver >1.5 (Vliver); (4) adaptive method (AM). All parameters obtained from the different methods were analyzed with respect to response. Results: Among the different methods investigated, the strongest correlation was observed between AM and Vliver (rho > 0.9; p < 0.001 for SUVmean, MTV and TLG at all scan timing), along with V2.5 and AM or Vliver (rho 0.98, p < 0.001 for TLG at baseline; rho > 0.9; p < 0.001 for SUVmean, MTV and TLG at PET2 and PET3, respectively). To determine the best segmentation method, we applied logistic regression and correlated different results with Deauville scores at late evaluation. Logistic regression demonstrated that MTV (metabolic tumor volume) and TLG (total lesion glycolysis) computation according to V2.5 and Vliver significantly correlated to response to treatment (p = 0.01 and 0.04 for MTV and 0.03 and 0.04 for TLG, respectively). SUVmean also resulted in significant correlation as absolute value or variation. Conclusions: The best correlation for volumetric analysis was documented for AM and Vliver, followed by V2.5. The volumetric analyses obtained from V2.5 and Vliver significantly correlated to response to therapy, proving to be preferred thresholds in our pediatric HL cohort.

Lymphoma tumor burden before chimeric antigen receptor T-Cell treatment: RECIL vs. Lugano vs. metabolic tumor assessment

Purpose

High tumor burden has emerged as a negative predictor of efficacy in chimeric antigen receptor T-cell therapy (CART) in patients with refractory or relapsed large B-cell lymphoma. This study analyzed the deviation among imaging-based tumor burden (TB) metrics and their association with progression-free (PFS) and overall survival (OS).

Materials and methods

In this single-center observational study, we included all consecutively treated patients receiving CD19 CART with available baseline PET-CT imaging. Imaging-based TB was determined based on response evaluation criteria in lymphoma (RECIL), the Lugano criteria, and metabolic tumor volume. Total, nodal and extranodal TB were represented, according to the respective criteria, by sum of longest diameters (TB_RECIL), sum of product of perpendicular diameters (TB_Lugano), and metabolic tumor volume (TB_MTV). Correlation statistics were used for comparison. Proportional Cox regression analysis studied the association of TB metrics with PFS and OS.

Results

34 consecutive patients were included (median age: 67 years, 41% female) with total median baseline TB_RECIL of 12.5 cm, TB_Lugano of 4,030 mm² and TB_MTV of 330 mL. The correlation of TB_RECIL and TB_Lugano with TB_MTV was strong (ρ=0.744, p<0.001 and ρ=0.741, p<0.001), with lowest correlation for extranodal TB_RECIL with TB_MTV (ρ=0.660, p<0.001). Stratification of PFS was strongest by total TB_MTV>50% (HR=2.915, p=0.042), whereas total TB_RECIL>50% and total TB_Lugano>50% were not significant (both p>0.05). None of the total TB metrics were associated with OS (all p>0.05).

Conclusion

Pre-CART TB metrics vary significantly based on the assessment method, impacting their association with survival outcomes. The correlation between TB_RECIL, TB_Lugano and TB_MTV was influenced by disease phenotype and prior bridging therapy. TB method of assessment must be considered when interpreting the impact of TB on outcomes in clinical trials. Considering the heterogeneity, our results argue for standardization and harmonization across centers.

The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in 18F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma

Consensus about a standard segmentation method to derive metabolic tumor volume (MTV) in classical Hodgkin lymphoma (cHL) is lacking, and it is unknown how different segmentation methods influence quantitative PET features. Therefore, we aimed to evaluate the delineation and completeness of lesion selection and the need for manual adaptation with different segmentation methods, and to assess the influence of segmentation methods on the prognostic value of MTV, intensity, and dissemination radiomics features in cHL patients. Methods: We analyzed a total of 105 ¹⁸F-FDG PET/CT scans from patients with newly diagnosed (n = 35) and relapsed/refractory (n = 70) cHL with 6 segmentation methods: 2 fixed thresholds on SUV4.0 and SUV2.5, 2 relative methods of 41% of SUV_max (41max) and a contrast-corrected 50% of SUV_peak (A50P), and 2 combination majority vote (MV) methods (MV2, MV3). Segmentation quality was assessed by 2 reviewers on the basis of predefined quality criteria: completeness of selection, the need for manual adaptation, and delineation of lesion borders. Correlations and prognostic performance of resulting radiomics features were compared among the methods. Results: SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low ¹⁸F-FDG uptake. SUV2.5 most frequently included all lesions but required minor manual adaptations and generally overestimated MTV. In contrast, few lesions were missed when using 41max, A50P, MV2, and MV3, but these segmentation methods required extensive manual adaptation and overestimated MTV in most cases. MTV and dissemination features significantly differed among the methods. However, correlations among methods were high for MTV and most intensity and dissemination features. There were no significant differences in prognostic performance for all features among the methods. Conclusion: A high correlation existed between MTV, intensity, and most dissemination features derived with the different segmentation methods, and the prognostic performance is similar. Despite frequently missing small lesions with low ¹⁸F-FDG avidity, segmentation with a fixed threshold of SUV4.0 required the least manual adaptation, which is critical for future research and implementation in clinical practice. However, the importance of small, low ¹⁸F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.