Prognostic value of baseline metabolic tumor volume and total lesion glycolysis in patients with lymphoma: A meta-analysis

Circulating Tumor DNA as a Complementary Prognostic Biomarker during CAR-T Therapy in B-Cell Non-Hodgkin Lymphomas

The emergence of CD19-directed chimeric antigen receptor T-cell (CAR-T) therapy has revolutionized the treatment paradigm for R/R B-cell NHLs. However, challenges persist in accurately evaluating treatment response and detecting early relapse, necessitating the exploration of novel biomarkers. Circulating tumor DNA (ctDNA) via liquid biopsy is a non-invasive tool for monitoring therapy efficacy and predicting treatment outcomes in B-NHL following CAR-T therapy. By overcoming the limitations of conventional imaging modalities, ctDNA assessments offer valuable insights into response dynamics, molecular mechanisms of resistance, and early detection of molecular relapse. Integration of ctDNA monitoring into clinical practice holds promise for personalized therapeutic strategies, guiding the development of novel targeted therapies, and enhancing patient outcomes. However, standardization of assay methodologies and consensus on clinical response metrics are imperative to unlock the full potential of ctDNA in the management of B-NHL. Prospective validation of ctDNA in clinical trials is necessary to establish its role as a complementary decision aid.

Evaluation of therapeutic effect and prognostic value of 18F-FDG PET/CT in different treatment nodes of DLBCL patients

BACKGROUND

In the present study, we aimed to investigate the role of baseline (B), interim (I) and end-of-treatment (Eot) 18F-FDG PET/CT in assessing the prognosis of diffuse large B cell lymphoma (DLBCL), so as to identify patients who need intensive treatment at an early stage.

METHODS

A total of 127 DLBCL patients (62 men; 65 women; median age 62 years) were retrospectively analyzed in this study. Baseline (n = 127), interim (n = 127, after 3-4 cycles) and end-of-treatment (n = 53, after 6-8 cycles) PET/CT images were re-evaluated; semi-quantitative parameters such as maximum standardized uptake value of lesion-to-liver ratio (SUVmax(LLR)) and lesion-to-mediastinum ratio (SUVmax(LMR)), total metabolic tumor volume (TMTV) and total metabolic tumor volume (TLG) were recorded. ΔTLG1 was the change of interim relative to baseline TLG (I to B), ΔTLG2 (Eot to B). ΔSUVmax and ΔTMTV were the same algorithm. The visual Deauville 5-point scale (D-5PS) has been adopted as the major criterion for PET evaluation. Visual analysis (VA) and semi-quantitative parameters were assessed for the ability to predict progression-free survival (PFS) and overall survival (OS) by using Kaplan-Meier method, cox regression and logistic regression analysis. When visual and semi-quantitative analysis are combined, the result is only positive if both are positive.

RESULTS

At a median follow-up of 34 months, the median PFS and OS were 20 and 32 months. The survival curve analysis showed that advanced stage and IPI score with poor prognosis, ΔSUVmax(LLR)1 < 89.2%, ΔTMTV1 < 91.8% and ΔTLG1 < 98.8%, ΔSUVmax(LLR)2 < 86.4% were significantly related to the shortening of PFS in patient (p < 0.05). ΔSUVmax(LLR)1 < 83.2% and ΔTLG1 < 97.6% were significantly correlated with the shortening of OS in patients (p < 0.05). Visual analysis showed that incomplete metabolic remission at I-PET and Eot-PET increased the risk of progress and death. In terms of predicting recurrence by I-PET, the combination of visual and semi-quantitative parameters showed higher positive predictive value (PPV) and specificity than a single index.

CONCLUSION

Three to four cycles of R-CHOP treatment may be a time point for early prediction of early recurrence/refractory (R/R) patients and active preemptive treatment. Combined visual analysis with semi-quantitative parameters of 18F-FDG PET/CT at interim can improve prognostic accuracy and may allow for more precise screening of patients requiring early intensive therapy.

Utility of FDG-PET in predicting the histology of relapsed or refractory lymphoma

ABSTRACT

18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) is a valuable prognostic tool in modern lymphoma care. In this study, we explored the use of quantitative FDG-PET parameters in predicting the histology of suspected relapsed or refractory (R/R) lymphoma. We retrospectively analyzed 290 FDG-PET scans performed for suspected R/R lymphoma. FDG-PET parameters measured were maximum and mean standardized uptake value (SUVMax and SUVMean), total metabolic tumor volume, and total lesion glycolysis (TLG). Receiver operating characteristic curve analysis was used to obtain the optimal thresholds that best discriminate (1) benign vs R/R lymphoma, (2) indolent vs aggressive non-Hodgkin lymphoma (NHL), and (3) aggressive transformation of indolent NHL. We found that although all 4 FDG-PET parameters discriminated R/R lymphoma from benign histology, TLG was the best performing parameter (optimal cut-off ≥245, sensitivity 63%, specificity 86%, positive predictive value [PPV] 97%, negative predictive value [NPV] 30%, area under the curve [AUC] 0.798, and P < .001). SUVMax discriminated aggressive from indolent NHL with modest accuracy (optimal threshold ≥15, sensitivity 46%, specificity 79%, PPV 82%, NPV 38%, AUC 0.638, and P < .001). In patients with a prior diagnosis of indolent NHL, SUVMax was a modest predictor of transformation (optimal cut-off ≥12, sensitivity 71%, specificity 61%, PPV 50%, NPV 78%, AUC 0.676, and P .006). Additionally, SUVMax ≥25 and an increase in SUVMax (ΔSUVMax) from baseline ≥150% were highly specific (96% and 94%, respectively). These FDG-PET thresholds can aid in identification of suspected R/R lymphoma cases with higher likelihood of R/R disease and aggressive transformation of indolent NHL, guiding the necessity and urgency of biopsy.

Optimization of Metabolic Tumor Volume as a Prognostic Marker in CAR T-Cell Therapy for Aggressive Large B-cell NHL

BACKGROUND

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has become a standard of care in relapsed/refractory (R/R) aggressive large B-cell non-Hodgkin lymphomas (B-NHL) though the majority of recipients do not receive durable disease benefit, prompting the need to better define risk factors for relapse/progression.

OBJECTIVES

We performed a single-center, retrospective analysis of patients treated with commercial CAR T-cell therapy to evaluate the impact of tumor burden, as measured by whole-body metabolic tumor volume (MTV) from 18F fluorodeoxyglucose PET imaging, on treatment outcomes.

STUDY DESIGN

Sixty-one patients treated with CAR T-cell therapy for R/R B-NHL between May 2016 and November 2021 were included.

RESULTS

Using a receiver operating characteristic curve-based MTV optimization cutoff of 450 mL, 1-year progression-free survival (PFS) was 22% for high MTV versus 54% for low MTV (P < .01), and 1-year overall survival (OS) was 37% and 73%, respectively (P = .01). In a subset of 46 patients, residual MTV of less than 106 mL at the day 30 (D30) disease assessment was associated with significantly improved outcomes (1-year OS 85% vs. 13%, P < .01). Incorporation of pretreatment MTV to the International Prognostic Index (IPI) scoring system significantly distinguished 2-year PFS and OS outcomes by 3 risk groups.

CONCLUSIONS

Our findings suggest that both pretreatment and D30 MTV are predictive of outcomes among R/R B-NHL patients treated with CAR T-cell therapy. These data indicate that efforts to reduce pretreatment tumor burden may improve longitudinal clinical outcomes. Furthermore, D30 postinfusion MTV quantification may aid clinicians in optimally identifying patients at high-risk for progression, and in whom closer disease monitoring should be considered. MTV also adds prognostic value to patients with high-risk IPI and holds promise for incorporation in novel risk scoring systems which can identify patients prior to CAR T-cell therapy at highest risk of adverse outcomes.

Targeting the Metabolic Paradigms in Cancer and Diabetes

Dysregulated metabolic dynamics are evident in both cancer and diabetes, with metabolic alterations representing a facet of the myriad changes observed in these conditions. This review delves into the commonalities in metabolism between cancer and type 2 diabetes (T2D), focusing specifically on the contrasting roles of oxidative phosphorylation (OXPHOS) and glycolysis as primary energy-generating pathways within cells. Building on earlier research, we explore how a shift towards one pathway over the other serves as a foundational aspect in the development of cancer and T2D. Unlike previous reviews, we posit that this shift may occur in seemingly opposing yet complementary directions, akin to the Yin and Yang concept. These metabolic fluctuations reveal an intricate network of underlying defective signaling pathways, orchestrating the pathogenesis and progression of each disease. The Warburg phenomenon, characterized by the prevalence of aerobic glycolysis over minimal to no OXPHOS, emerges as the predominant metabolic phenotype in cancer. Conversely, in T2D, the prevailing metabolic paradigm has traditionally been perceived in terms of discrete irregularities rather than an OXPHOS-to-glycolysis shift. Throughout T2D pathogenesis, OXPHOS remains consistently heightened due to chronic hyperglycemia or hyperinsulinemia. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, featuring differential tissue-specific alterations that affect OXPHOS. Recent findings suggest that addressing the metabolic imbalance in both cancer and diabetes could offer an effective treatment strategy. Numerous pharmaceutical and nutritional modalities exhibiting therapeutic effects in both conditions ultimately modulate the OXPHOS-glycolysis axis. Noteworthy nutritional adjuncts, such as alpha-lipoic acid, flavonoids, and glutamine, demonstrate the ability to reprogram metabolism, exerting anti-tumor and anti-diabetic effects. Similarly, pharmacological agents like metformin exhibit therapeutic efficacy in both T2D and cancer. This review discusses the molecular mechanisms underlying these metabolic shifts and explores promising therapeutic strategies aimed at reversing the metabolic imbalance in both disease scenarios.

Prognostic Impact of Serum β2-Microglobulin Levels in Hodgkin Lymphoma Treated with ABVD or Equivalent Regimens: A Comprehensive Analysis of 915 Patients

The significance of serum beta-2 microglobulin (sβ2m) in Hodgkin lymphoma (HL) is controversial. We analyzed 915 patients with HL, who were treated with ABVD or equivalent regimens with or without radiotherapy. Sβ2m levels were measured by a radioimmunoassay (upper normal limit 2.4 mg/L). Sequential cutoffs (1.8-3.0 by 0.1 mg/L increments, 3.5 and 4.0 mg/L) were tested along with ROC analysis. The median sβ2m levels were 2.20 mg/L and were elevated (>2.4 mg/L) in 383/915 patients (41.9%). Higher sβ2m was associated with inferior freedom from progression (FFP) at all tested cutoffs. The best cutoff was 2.0 mg/L (10-year FFP 83% vs. 70%, p = 0.001), which performed better than the 2.4 mg/L cutoff ("normal versus high"). In multivariate analysis, sβ2m > 2.0 mg/L was an independent adverse prognostic factor in the whole patient population. In multivariate overall survival analysis, sβ2m levels were predictive at 2.0 mg/L cutoff in the whole patient population and in advanced stages. Similarly, sβ2m > 2.0 mg/L independently predicted inferior HL-specific survival in the whole patient population. Our data suggest that higher sβ2m is an independent predictor of outcome in HL but the optimal cutoff lies within the normal limits (i.e., at 2.0 mg/L) in this predominantly young patient population, performing much better than a "normal versus high" cutoff set at 2.4 mg/L.

Metabolic parameters predict survival and toxicity in chimeric antigen receptor T-cell therapy-treated relapsed/refractory large B-cell lymphoma

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has revolutionized treatment for patients with relapsed/refractory large B-cell lymphoma (LBCL). However, data available concerning the impact of the prognostic value of quantitative 18F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) parameters on the CAR T-related outcomes and toxicities are limited. Therefore, we aimed to evaluate the predictive value of pre- and post-CAR T metabolic parameters on survival and toxicities following CAR T-cell therapy. Fifty-nine patients with PET/CT scans done pre-and post-CAR T infusion were retrospectively identified and analyzed in a single institution database of LBCL patients treated with commercial CD19-targeted CAR T-cell therapy. The median follow-up was 10.7 months [interquartile range (IQR): 2.6-25.5 months]. The overall response (complete response-CR and partial response) and CR rates post-CAR T were 76% (n = 45) and 53% (n = 31), respectively. On univariate analysis, low pre-CAR T total lesion glycolysis (TLG) and metabolic tumor volume (MTV) predicted improved overall response post-CAR T (OR = 4.7, p = 0.01, OR = 9.5, p = 0.03, respectively) and CR post-CAR T (OR = 12.4, p = 0.0004, OR = 10.9, p = 0.0001, respectively). High TLG pre-CAR T was correlated with cytokine release syndrome (CRS, OR = 3.25, p = 0.04). High MTV pre-CAR T was correlated with developing immune effector cell neurotoxicity syndrome (ICANS) events (OR = 4.3, p = 0.01), and high SUV pre-CAR T was associated with grade 3-4 neurological events (OR = 12, p = 0.01). High MTV/TLG/SUVmax post-CAR T were significantly associated with inferior Overall survival (OS). On multivariate analysis, high TLG pre-CAR T (HR = 2.4, p = 0.03), age ≥60 (HR = 2.7, p = 0.03), and bulky disease (≥5 cm) at the time of apheresis (HR = 2.5, p = 0.02) were identified to be independent prognostic factors for inferior PFS. High MTV post-CAR T was identified as the most prognostic factor associated with inferior OS.

Predictive value of Dmax and %ΔSUVmax of 18F-FDG PET/CT for the prognosis of patients with diffuse large B-cell lymphoma

PURPOSE

To investigate the prognosis value of a combined model based on 18F-fluoro-deoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) baseline and interim parameters in patients with diffuse large B-cell lymphoma (DLBCL).

METHODS

We retrospectively analyzed the PET metabolic parameters and clinical data of 154 DLBCL patients between December 2015 and October 2020. All of these patients underwent 18F-FDG PET/CT scan before treatment and after three or four courses of chemotherapy. The optimal cut-off values for quantitative variables were determined by the receiver operating characteristic (ROC) curve. The baseline and interim PET/CT parameters, which respectively included maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax) and total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), and clinical characteristics were analyzed by chi-squared test, Kaplan-Meier survival curve, and Cox regression analysis.

RESULTS

Of 154 patients, 35 exhibited disease progression or recurrence. ROC analysis revealed that baseline 18F-FDG PET/CT metabolic parameters, including maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax), along with interim 18F-FDG PET/CT metabolic parameters such as total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), were predictive of relapse or progression in DLBCL patients (P < 0.05). The chi-squared test showed that TMTV0, STMTV0, Dmax, SUVmax1, TMTV1, TTLG1, %ΔSUVmax, Deauville score, IPI, Ann Arbor stage, and LDH were associated with patient prognosis (P < 0.05). Multivariate Cox regression analysis showed that Dmax (P = 0.021) and %ΔSUVmax (P = 0.030) were independent predictors of prognosis in DLBCL patients. There were statistically significant differences in PFS among the three groups with high, intermediate, and low risk according to the combination model (P < 0.001). The combination model presented higher predictive efficacy than single indicators.

CONCLUSION

The combined model of baseline parameter Dmax and intermediate parameter %ΔSUVmax of 18F-FDG PET/CT improved the predictive efficacy of PFS and contributed to the risk stratification of patients, providing a reference for clinical individualization and precision treatment.

Metabolic PET/CT analysis of aggressive Non-Hodgkin lymphoma prior to Axicabtagene Ciloleucel CAR-T infusion: predictors of progressive disease, survival, and toxicity

PET/CT is used to evaluate relapsed/refractory non-Hodgkin lymphoma (NHL) prior to chimeric antigen receptor T-cell (CAR-T) infusion at two time points: pre-leukapheresis (pre-leuk) and pre-lymphodepletion chemotherapy (pre-LD). We hypothesized that changes in PET/CT between these time points predict outcomes after CAR-T. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), and other metrics were calculated from pre-leuk and pre-LD PET/CT scans in patients with NHL who received axicabtagene ciloleucel, and assessed for association with outcomes. Sixty-nine patients were analyzed. While single time point PET/CT characteristics were not associated with risk of PD or death, increases from pre-leuk to pre-LD in parenchymal MTV, nodal MTV, TLG of the largest lesion, and total number of lesions were associated with increased risk of death (p < 0.05 for all). LASSO analysis identified increasing extranodal MTV and increasing TLG of the largest lesion as strong predictors of death (AUC 0.74). Greater pre-LD total MTV was associated with higher risk of grade 3+ immune effector cell-associated neurotoxicity syndrome (ICANS) (p = 0.042). Increasing metabolic disease burden during CAR-T manufacturing is associated with increased risk of progression and death. A two variable risk score stratifies prognosis prior to CAR-T infusion and may inform risk-adapted strategies.

Cell-free DNA in large B-cell lymphoma: MRD and beyond

Large B-cell lymphomas (LBCLs) are a strikingly diverse set of diseases, including clinical, biological, and molecular heterogeneity. Despite a wealth of information resolving this heterogeneity in the research setting, applying molecular features routinely in the clinic remains challenging. The advent of circulating tumor DNA (ctDNA) liquid biopsies promises to unlock additional molecular information in the clinic, including mutational genotyping, molecular classification, and minimal residual disease detection. Here, we examine the technologies, applications, and studies exploring the utility of ctDNA in LBCLs.

Metabolic bulk volume predicts survival in a homogeneous cohort of stage II/III diffuse large B-cell lymphoma patients undergoing R-CHOP treatment

Purpose

Accurate risk stratification can improve lymphoma management, but current volumetric ¹⁸F-fluorodeoxyglucose (FDG) indicators require time-consuming segmentation of all lesions in the body. Herein, we investigated the prognostic values of readily obtainable metabolic bulk volume (MBV) and bulky lesion glycolysis (BLG) that measure the single largest lesion.

Methods

The study subjects were a homogeneous cohort of 242 newly diagnosed stage II or III diffuse large B-cell lymphoma (DLBCL) patients who underwent first-line R-CHOP treatment. Baseline PET/CT was retrospectively analyzed for maximum transverse diameter (MTD), total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), MBV, and BLG. Volumes were drawn using 30% SUVmax as threshold. Kaplan-Meier survival analysis and the Cox proportional hazards model assessed the ability to predict overall survival (OS) and progression-free survival (PFS).

Results

During a median follow-up period of 5.4 years (maximum of 12.7 years), events occurred in 85 patients, including progression, relapse, and death (65 deaths occurred at a median of 17.6 months). Receiver operating characteristic (ROC) analysis identified an optimal TMTV of 112 cm³, MBV of 88 cm³, TLG of 950, and BLG of 750 for discerning events. Patients with high MBV were more likely to have stage III disease; worse ECOG performance; higher IPI risk score; increased LDH; and high SUVmax, MTD, TMTV, TLG, and BLG. Kaplan-Meier survival analysis showed that high TMTV (p = 0.005 and < 0.001), MBV (both p < 0.001), TLG (p < 0.001 and 0.008), and BLG (p = 0.018 and 0.049) were associated with significantly worse OS and PFS. On Cox multivariate analysis, older age (> 60 years; HR, 2.74; 95% CI, 1.58-4.75; p < 0.001) and high MBV (HR, 2.74; 95% CI, 1.05-6.54; p = 0.023) were independent predictors of worse OS. Older age (hazard ratio [HR], 2.90; 95% CI, 1.74-4.82; p < 0.001) and high MBV (HR, 2.36; 95% CI, 1.15-6.54; p = 0.032) were also independent predictors of worse PFS. Furthermore, among subjects ≤60 years, high MBV remained the only significant independent predictor of worse OS (HR, 4.269; 95% CI, 1.03-17.76; p = 0.046) and PFS (HR, 6.047; 95% CI, 1.73-21.11; p = 0.005). Among subjects with stage III disease, only greater age (HR, 2.540; 95% CI, 1.22-5.30; p = 0.013) and high MBV (HR, 6.476; 95% CI, 1.20-31.9; p = 0.030) were significantly associated with worse OS, while greater age was the only independent predictor of worse PFS (HR, 6.145; 95% CI, 1.10-4.17; p = 0.024).

Conclusions

MBV easily obtained from the single largest lesion may provide a clinically useful FDG volumetric prognostic indicator in stage II/III DLBCL patients treated with R-CHOP.

Whole body MRI with Diffusion Weighted Imaging versus 18F-fluorodeoxyglucose-PET/CT in the staging of lymphomas

PURPOSE

To assess the diagnostic performance of Whole Body (WB)-MRI in comparison with 18F-Fluorodeoxyglucose-PET/CT (18F-FDG-PET/CT) in lymphoma staging and to assess whether quantitative metabolic parameters from 18F-FDG-PET/CT and Apparent Diffusion Coefficient (ADC) values are related.

MATERIALS AND METHODS

We prospectively enrolled patients with a histologically proven primary nodal lymphoma to  undergo 18F-FDG-PET/CT and WB-MRI, both performed within 15 days one from the other, either before starting treatment (baseline) or during treatment (interim). Positive and negative predictive values of WB-MRI for the identification of nodal and extra-nodal disease were measured. The agreement between WB-MRI and 18F-FDG-PET/CT for the identification of lesions and staging was assessed through Cohen's coefficient k and observed agreement. Quantitative parameters of nodal lesions derived from 18F-FDG-PET/CT and WB-MRI (ADC) were measured and the Pearson or Spearman correlation coefficient was used to assess the correlation between them. The specified level of significance was p ≤ 0.05.

RESULTS

Among the 91 identified patients, 8 refused to participate and 22 met exclusion criteria, thus images from 61 patients (37 men, mean age 30.7 years) were evaluated. The agreement between 18F-FDG-PET/CT and WB-MRI for the identification of nodal and extra-nodal lesions was 0.95 (95% CI 0.92 to 0.98) and 1.00 (95% CI NA), respectively; for staging it was 1.00 (95% CI NA). A strong negative correlation was found between ADCmean and SUVmean of nodal lesions in patients evaluated at baseline (Spearman coefficient r_s = - 0.61, p = 0.001).

CONCLUSION

WB-MRI has a good diagnostic performance for staging of patients with lymphoma in comparison with 18F-FDG-PET/CT and is a promising technique for the quantitative assessment of disease burden in these patients.

Liquid biopsy in hematological malignancies: current and future applications

The assessment of the cancer mutational profile is crucial for patient management, stratification, and therapeutic decisions. At present, in hematological malignancies with a solid mass, such as lymphomas, tumor genomic profiling is generally performed on the tissue biopsy, but the tumor may harbor genetic lesions that are unique to other anatomical compartments. The analysis of circulating tumor DNA (ctDNA) on the liquid biopsy is an emerging approach that allows genotyping and monitoring of the disease during therapy and follow-up. This review presents the different methods for ctDNA analysis and describes the application of liquid biopsy in different hematological malignancies. In diffuse large B-cell lymphoma (DLBCL) and Hodgkin lymphoma (HL), ctDNA analysis on the liquid biopsy recapitulates the mutational profile of the tissue biopsy and can identify mutations otherwise absent on the tissue biopsy. In addition, changes in the ctDNA amount after one or two courses of chemotherapy significantly predict patient outcomes. ctDNA analysis has also been tested in myeloid neoplasms with promising results. In addition to mutational analysis, liquid biopsy also carries potential future applications of ctDNA, including the analysis of ctDNA fragmentation and epigenetic patterns. On these grounds, several clinical trials aiming at incorporating ctDNA analysis for treatment tailoring are currently ongoing in hematological malignancies.

Prognostic parameters on baseline and interim [ 18 F]FDG-PET/computed tomography in diffuse large B-cell lymphoma patients

OBJECTIVE

2-[ 18 F]fluoro-2-deoxy- d -glucose PET/computed tomography ([ 18 F]FDG-PET/CT) is a widely used imaging method in the management of diffuse large B-cell lymphomas (DLBCL). Our aim was to investigate the prognostic performance of different PET biomarkers in a multicenter setting.

METHODS

We investigated baseline volumetric values [metabolic tumor volume (MTV) and total lesion glycolysis (TLG), also normalized for body weight] segmented with three different methods [>SUV4 (glob4); 41% isocontour (41pc), and a gradient-based lesion growing algorithm (grad)] and interim parameters [Deauville score, maximal standardized uptake value (ΔSUVmax), modified qPET, and ratio PET (rPET)] alongside clinical parameters (stage, revised International Prognostic Index), using 24-month progression-free survival as the clinical endpoint. Receiver operating characteristics analyses were performed to define optimal cutoff points for the continuous PET parameters.

RESULTS

A total of 107 diffuse large B-cell lymphoma patients were included (54 women; mean age: 53.7 years). MTV and TLG calculations showed good correlation among glob4, 41pc, and grad methods; however, optimal cutoff points were markedly different.Significantly different PFS was observed between low- and high-risk groups according to baseline MTV, body weight-adjusted (bwa) MTV, TLG, bwaTLG, as well as interim parameters Deauville score, ΔSUVmax, mqPET, and rPET. Univariate Cox regression analyses showed hazard ratios (HRs) lowest for bwaMTVglob4 (HR = 2.3) and highest for rPET (HR = 9.09). In a multivariate Cox-regression model, rPET was shown to be an independent predictor of PFS ( P  = 0.041; HR = 9.15). Combined analysis showed that ΔSUVmax positive patients with high MTV formed a group with distinctly poor PFS (35.3%).

CONCLUSION

Baseline MTV and TLG values and optimal cutoff points achieved with different segmentation methods varied markedly and showed a limited prognostic impact. Interim PET/CT parameters provided more accurate prognostic information with semiquantitative 'Deauville-like' parameters performing best in the present study.

Development and Validation of 18F-FDG PET/CT-Based Models for Predicting Successful Complete Cytoreduction During Primary Cytoreductive Surgery for Advanced Ovarian cancer

PURPOSE

The aim of this study was to develop an 18F-FDG PET/CT-based model to predict complete cytoreduction during primary cytoreductive surgery (CRS) for ovarian cancer (OC).

PATIENTS AND METHODS

We retrospectively identified patients with stage III-IV OC who underwent primary CRS between June 2013 and February 2020 at 2 tertiary centers. Patients from each hospital were assigned to training and test sets. The abdominal cavity was divided into 3 sections, and data for the PET/CT-derived parameters were collected through image analysis. Various prediction models were constructed by combining clinicopathologic characteristics and PET/CT-derived parameters. The performance of the model with the highest area under the receiver operating characteristic curve (AUC) was externally validated.

RESULTS

The training and test sets included 159 and 166 patients, respectively. The median age of patients in the test set was 55 years; 72.3% of them had stage III tumors, and 65.4% underwent complete cytoreduction. Metabolic tumor volume, total lesion glycolysis, and the number of metastatic lesions above the upper margin of the renal vein (area A) were selected among the PET/CT parameters. The best predictive multivariable model consisted of CA-125 (<750 or ≥750 IU/mL), number of metastatic lesions (<2 or ≥2), and metabolic tumor volume of area A, predicting complete cytoreduction with an AUC of 0.768. The model was validated using a test set. Its predictive performance yielded an AUC of 0.771.

CONCLUSIONS

We successfully developed and validated a preoperative model to predict complete cytoreduction in advanced OC. This model can facilitate patient selection for primary CRS in clinical practice.

FDG PET/CT Maximum Tumor Dissemination to Predict Recurrence in Patients with Diffuse Large B-Cell Lymphoma

Purpose

We investigated the prognostic value of maximum tumor dissemination (Dmax), the distance between malignant lesions that were farthest apart, as assessed by fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT), and other clinical factors in patients with diffuse large B-cell lymphoma (DLBCL).We investigated the prognostic value of maximum tumor dissemination (Dmax), the distance between malignant lesions that were farthest apart, as assessed by fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT), and other clinical factors in patients with diffuse large B-cell lymphoma (DLBCL).

Methods

Patients who underwent FDG PET/CT for initial staging and treatment response evaluation of DLBCL were reviewed retrospectively. Baseline Dmax, maximum standardized uptake value, total summation of all metabolic tumor volumes (tMTV), and total summation of all total lesion glycolysis (tTLG) were measured. The treatment response was evaluated at the interim and end of first-line treatment (EOT) using the Deauville score (DS). FDG PET/CT parameters and other clinical factors including sex, age, serum lactate dehydrogenase (LDH) level, stage, performance status, and the International Prognostic Index (IPI) were analyzed to identify factors prognostic of the time to progression (TTP) and disease-specific survival (DSS).

Results

A total of 63 patients were included. Univariate survival analysis identified Dmax (> 275 mm), tMTV (> 180 mL), tTLG (> 1300), interim DS (≥ 4), and EOT DS (≥ 4) as significant predictors of poor TTP. Serum LDH level (> 640 IU/L), IPI (≥ 4), tMTV (> 180 mL), tTLG (> 1300), interim DS (≥ 4), and EOT DS (≥ 4) were significant predictors of DSS. After multivariate survival analysis, Dmax (P = 0.008) and EOT DS (P = 0.005) were independent predictors of TTP. EOT DS was an independent predictor of DSS (P = 0.029).

Conclusions

Dmax at the time of diagnosis and the EOT response assessed by FDG PET/CT provide useful prognostic information additive to the IPI in patients with DLBCL.

Iterated cross validation method for prediction of survival in diffuse large B-cell lymphoma for small size dataset

Efforts have been made to improve the risk stratification model for patients with diffuse large B-cell lymphoma (DLBCL). This study aimed to evaluate the disease prognosis using machine learning models with iterated cross validation (CV) method. A total of 122 patients with pathologically confirmed DLBCL and receiving rituximab-containing chemotherapy were enrolled. Contributions of clinical, laboratory, and metabolic imaging parameters from fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scans to the prognosis were evaluated using five regression models, namely logistic regression, random forest, support vector classifier (SVC), deep neural network (DNN), and fuzzy neural network models. Binary classification predictions for 3-year progression free survival (PFS) and 3-year overall survival (OS) were conducted. The 10-iterated fivefold CV with shuffling process was conducted to predict the capability of learning machines. The median PFS and OS were 41.0 and 43.6 months, respectively. Two indicators were found to be independent predictors for prognosis: international prognostic index and total metabolic tumor volume (MTVsum) from FDG PET/CT. For PFS, SVC and DNN (both with accuracy 71%) have the best predictive results, of which outperformed other algorithms. For OS, the DNN has the best predictive result (accuracy 76%). Using clinical and metabolic parameters as input variables, the machine learning methods with iterated CV method add the predictive values for PFS and OS evaluation in DLBCL patients.

Evaluation of a convolution neural network for baseline total tumor metabolic volume on [18F]FDG PET in diffuse large B cell lymphoma

OBJECTIVES

New PET data-processing tools allow for automatic lesion selection and segmentation by a convolution neural network using artificial intelligence (AI) to obtain total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) routinely at the clinical workstation. Our objective was to evaluate an AI implemented in a new version of commercial software to verify reproducibility of results and time savings in a daily workflow.

METHODS

Using the software to obtain TMTV and TLG, two nuclear physicians applied five methods to retrospectively analyze data for 51 patients. Methods 1 and 2 were fully automated with exclusion of lesions ≤ 0.5 mL and ≤ 0.1 mL, respectively. Methods 3 and 4 were fully automated with physician review. Method 5 was semi-automated and used as reference. Time and number of clicks to complete the measurement were recorded for each method. Inter-instrument and inter-observer variation was assessed by the intra-class coefficient (ICC) and Bland-Altman plots.

RESULTS

Between methods 3 and 5, for the main user, the ICC was 0.99 for TMTV and 1.0 for TLG. Between the two users applying method 3, ICC was 0.97 for TMTV and 0.99 for TLG. Mean processing time (± standard deviation) was 20 s ± 9.0 for method 1, 178 s ± 125.7 for method 3, and 326 s ± 188.6 for method 5 (p < 0.05).

CONCLUSION

AI-enabled lesion detection software offers an automated, fast, reliable, and consistently performing tool for obtaining TMTV and TLG in a daily workflow.

KEY POINTS

• Our study shows that artificial intelligence lesion detection software is an automated, fast, reliable, and consistently performing tool for obtaining total metabolic tumor volume and total lesion glycolysis in a daily workflow.

Influence of the methodological aspects of the dichotomization of total metabolic tumor volume measured through baseline fluorine-18 fluorodeoxyglucose PET on survival prediction in lymphoma

OBJECTIVE

The total metabolic tumor volume (TMTV) measured from fluorine-18 fluorodeoxyglucose (18F-FDG) PET can be useful for determining the prognosis of patients with lymphoma. Stratifying patients into high- and low-TMTV risk groups requires a cutoff point, which is determined through the dichotomization method. This study investigated whether different TMTV dichotomization methods influenced survival prediction in patients with lymphoma.

METHODS

We retrospectively enrolled 129 patients with lymphoma who had undergone baseline 18F-FDG PET. TMTV was calculated using a fixed standardized uptake value threshold of 4.0. A total of six methods were employed to determine the optimal TMTV cutoff point using receiver-operating characteristic curve analyses, X-Tile bioinformatics software, and the Cutoff Finder web application. The prognostic performance of each method in survival prediction was examined.

RESULTS

The median (interquartile range) TMTV was 123 cm3 (21-335 cm3). The optimal TMTV cutoff values for predicting progression-free survival (PFS) and overall survival (OS) were in the range of 144-748 cm3. The cutoff points were used to dichotomize patients into two groups with distinct prognoses. All TMTV dichotomizations were significantly predictive of PFS and OS. The survival curves showed significant differences between the high- and low-TMTV groups. The C-indices of the survival models did not significantly differ in any of the dichotomizations.

CONCLUSION

The prognostic significance of TMTV was maintained regardless of the methodological aspects of dichotomization. However, the optimal TMTV cutoff point varied according to the chosen dichotomization method. Care should be taken when establishing an optimal TMTV cutoff point for clinical use.

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.

The application of machine learning to imaging in hematological oncology: A scoping review

Background

Here, we conducted a scoping review to (i) establish which machine learning (ML) methods have been applied to hematological malignancy imaging; (ii) establish how ML is being applied to hematological cancer radiology; and (iii) identify addressable research gaps.

Methods

The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews guidelines. The inclusion criteria were (i) pediatric and adult patients with suspected or confirmed hematological malignancy undergoing imaging (population); (ii) any study using ML techniques to derive models using radiological images to apply to the clinical management of these patients (concept); and (iii) original research articles conducted in any setting globally (context). Quality Assessment of Diagnostic Accuracy Studies 2 criteria were used to assess diagnostic and segmentation studies, while the Newcastle-Ottawa scale was used to assess the quality of observational studies.

Results

Of 53 eligible studies, 33 applied diverse ML techniques to diagnose hematological malignancies or to differentiate them from other diseases, especially discriminating gliomas from primary central nervous system lymphomas (n=18); 11 applied ML to segmentation tasks, while 9 applied ML to prognostication or predicting therapeutic responses, especially for diffuse large B-cell lymphoma. All studies reported discrimination statistics, but no study calculated calibration statistics. Every diagnostic/segmentation study had a high risk of bias due to their case-control design; many studies failed to provide adequate details of the reference standard; and only a few studies used independent validation.

Conclusion

To deliver validated ML-based models to radiologists managing hematological malignancies, future studies should (i) adhere to standardized, high-quality reporting guidelines such as the Checklist for Artificial Intelligence in Medical Imaging; (ii) validate models in independent cohorts; (ii) standardize volume segmentation methods for segmentation tasks; (iv) establish comprehensive prospective studies that include different tumor grades, comparisons with radiologists, optimal imaging modalities, sequences, and planes; (v) include side-by-side comparisons of different methods; and (vi) include low- and middle-income countries in multicentric studies to enhance generalizability and reduce inequity.

Development of scalable lymphatic system in the 4D XCAT phantom: Application to quantitative evaluation of lymphoma PET segmentations

BACKGROUND

Digital anthropomorphic phantoms, such as the 4D extended cardiac-torso (XCAT) phantom, are actively used to develop, optimize, and evaluate a variety of imaging applications, allowing for realistic patient modeling and knowledge of ground truth. The XCAT phantom defines the activity and attenuation for a simulated patient, which includes a complete set of organs, muscle, bone, and soft tissue, while also accounting for cardiac and respiratory motion. However, the XCAT phantom does not currently include the lymphatic system, critical for evaluating medical imaging tasks such as sentinel node detection, node density measurement, and radiation dosimetry.

PURPOSE

In this study, we aimed to develop a scalable lymphatic system in the XCAT phantom, to facilitate improved research of the lymphatic system in medical imaging. Using this scalable lymphatic system, we modeled the lymph node conglomerate pathology that is characteristically observed in primary mediastinal B-cell lymphoma (PMBCL). As an extended application, we evaluated positron emission tomography (PET) image quantification of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of these simulated lymphomas, though the phantoms may be applied to other imaging modalities and study design paradigms (e.g., image quality, detection).

METHODS

A template model for the lymphatic system was developed based on anatomical data from the Visible Human Project of the National Library of Medicine. The segmented nodes and vessels were fit with non-uniform rational basis spline surfaces, and multichannel large deformation diffeomorphic metric mapping was used to propagate the template to different XCAT anatomies. To model conglomerates observed in PMBCL, lymph nodes were enlarged, converged within the mediastinum, and tracer concentration was increased. We used the phantoms as inputs to a PET simulation tool, which generated images using ordered subsets expectation maximization reconstruction with 2-8 mm Gaussian filters. Fixed thresholding (FT) and gradient segmentation were used to determine MTV and TLG. Percent bias (%Bias) and coefficient of variation (COV) were computed as measures of accuracy and precision, respectively, for each MTV and TLG measurement.

RESULTS

Using the methodology described above, we introduced a scalable lymphatic system in the XCAT phantom, which allows for the radioactivity and attenuation ground truth to be generated in 116 ± 2.5 s using a 2.3 GHz processor. Within the Rhinoceros interface, lymph node anatomy and function were modified to create a cohort of 10 phantoms with lymph node conglomerates. Using the lymphoma phantoms to evaluate PET quantification of MTV, mean %Bias values were -9.3%, -41.3%, and 20.9%, while COV values were 4.08%, 7.6%, and 3.4% using 25% FT, 40% FT, and gradient segmentations, respectively. Comparatively for TLG, mean %Bias values were -27.4%, -45.8%, and -16.0%, while COV values were 1.9%, 5.7%, and 1.4%, for the 25% FT, 40% FT, and gradient segmentations, respectively.

CONCLUSIONS

In this work, we upgraded the XCAT phantom to include a lymphatic system, comprised of a network of 276 scalable lymph nodes and corresponding vessels. As an application, we created a cohort of phantoms with lymph node conglomerates to evaluate lymphoma quantification in PET imaging, which highlights an important application of this work.

Longitudinal Body Composition Changes Detected by [18F]FDG PET/CT during and after Chemotherapy and Their Prognostic Role in Elderly Hodgkin Lymphoma

The aim of this retrospective study was to investigate the longitudinal body changes in terms of muscle and adipose areas and their prognostic role in elderly (>65 years) patients affected by Hodgkin lymphoma (HL). Skeletal muscle area (SMA), skeletal muscle index (SMI), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), and total dispose tissue (TAT) were measured using the computed tomography (CT) of fluorine-18-fluorodeoxyglucose positron emission tomography/CT ([18F]FDG PET/CT) in 88 patients who undertook baseline, interim (after two cycles of chemotherapy), and end-of-treatment (after 6 cycles of chemotherapy) PET/CT scans. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured at pre-treatment PET/CT. Metabolic response applying Deauville score was evaluated at interim and end-of-treatment PET/CT. Survival curves, such as progression free survival (PFS) and overall survival (OS), were calculated for the whole population. Fifty-eight (66%) patients had sarcopenia at baseline and sarcopenia rate increased at interim scan with 68 (77%) cases and at end-of-treatment scan with 73 (83%) cases. Muscular areas (SMA and SMI) declined significantly during the treatment (p < 0.001), decreasing from baseline by 5% and 7% at interim and end-of-treatment evaluation, respectively. Instead, VAT, SAT, IMAT, and TAT increased significantly over this time (p < 0.001). Sarcopenia was significantly related with comprehensive geriatric assessment. PET/CT response at interim and end-of-treatment, MTV, TLG, and baseline sarcopenia were independent prognostic factors for PFS. Instead, metabolic response at interim and end-of-treatment PET, baseline sarcopenia, ΔSMI at interim, and ΔSMI at end-of-treatment for OS were independent prognostic factors.

TCR-Independent Metabolic Reprogramming Precedes Lymphoma-Driven Changes in T-cell Fate

Chronic T-cell receptor (TCR) signaling in the tumor microenvironment is known to promote T-cell dysfunction. However, we reasoned that poorly immunogenic tumors may also compromise T cells by impairing their metabolism. To address this, we assessed temporal changes in T-cell metabolism, fate, and function in models of B-cell lymphoma driven by Myc, a promoter of energetics and repressor of immunogenicity. Increases in lymphoma burden most significantly impaired CD4+ T-cell function and promoted regulatory T cell (Treg) and Th1-cell differentiation. Metabolomic analyses revealed early reprogramming of CD4+ T-cell metabolism, reduced glucose uptake, and impaired mitochondrial function, which preceded changes in T-cell fate. In contrast, B-cell lymphoma metabolism remained robust during tumor progression. Finally, mitochondrial functions were impaired in CD4+ and CD8+ T cells in lymphoma-transplanted OT-II and OT-I transgenic mice, respectively. These findings support a model, whereby early, TCR-independent, metabolic interactions with developing lymphomas limits T cell-mediated immune surveillance.

Prognostic value of lesion dissemination in doxorubicin, bleomycin, vinblastine, and dacarbazine-treated, interimPET-negative classical Hodgkin Lymphoma patients: A radio-genomic study

We evaluated the prognostic role of the largest distance between two lesions (Dmax), defined by positron emission tomography (PET) in a retrospective cohort of newly diagnosed classical Hodgkin Lymphoma (cHL) patients. We also explored the molecular bases underlying Dmax through a gene expression analysis of diagnostic biopsies. We included patients diagnosed with cHL from 2007 to 2020, initially treated with ABVD, with available baseline PET for review, and with at least two FDG avid lesions. Patients with available RNA from diagnostic biopsy were eligible for gene expression analysis. Dmax was deduced from the three-dimensional coordinates of the baseline metabolic tumor volume (MTV) and its effect on progression free survival (PFS) was evaluated. Gene expression profiles were correlated with Dmax and analyzed using CIBERSORTx algorithm to perform deconvolution. The study was conducted on 155 eligible cHL patients. Using its median value of 20 cm, Dmax was the only variable independently associated with PFS (HR = 2.70, 95% CI 1.1-6.63, pValue = 0.03) in multivariate analysis of PFS for all patients and for those with early complete metabolic response (iPET-). Among patients with iPET-low Dmax was associated with a 4-year PFS of 90% (95% CI 82.0-98.9) significantly better compared to high Dmax (4-year PFS 72.4%, 95% CI 61.9-84.6). From the analysis of gene expression profiles differences in Dmax were mostly associated with variations in the expression of microenvironmental components. In conclusion our results support tumor dissemination measured through Dmax as novel prognostic factor for cHL patients treated with ABVD.

The role of 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma after radioimmunotherapy using 131I-rituximab as consolidation therapy

Purpose

To evaluate the prognostic value of pretreatment ¹⁸F-FDG PET/CT after consolidation therapy of ¹³¹I-rituximab in patients with diffuse large B-cell lymphoma (DLBCL) who had acquired complete remission after receiving chemotherapy.

Methods

Patients who were diagnosed with DLBCL via histologic confirmation were retrospectively reviewed. All patients had achieved complete remission after 6 to 8 cycles of R-CHOP (rituximab, cyclophosphamide, vincristine, doxorubicin, and prednisolone) chemotherapy after which they underwent consolidation treatment with ¹³¹I-rituximab. ¹⁸F-FDG PET/CT scans were performed before R-CHOP for initial staging. The largest diameter of tumor, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained from pretreatment ¹⁸F-FDG PET/CT scans. Receiver-operating characteristic curves analysis was introduced for assessing the optimal criteria. Kaplan-Meier curve survival analysis was performed to evaluate both relapse free survival (RFS) and overall survival (OS).

Results

A total of 15 patients (12 males and 3 females) with a mean age of 56 (range, 30–73) years were enrolled. The median follow-up period of these patients was 73 months (range, 11–108 months). Four (27%) patients relapsed. Of them, three died during follow-up. Median values of the largest tumor size, highest SUVmax, MTV, and TLG were 5.3 cm (range, 2.0–16.4 cm), 20.2 (range, 11.1–67.4), 231.51 (range, 15–38.34), and 1277.95 (range, 238.37–10341.04), respectively. Patients with SUVmax less than or equal to 16.9 showed significantly worse RFS than patients with SUVmax greater than 16.9 (5-year RFS rate: 60% vs. 100%, p = 0.008). Patients with SUVmax less than or equal to 16.9 showed significantly worse OS than patients with SUVmax greater than 16.9 (5-year OS rate: 80% vs. 100% p = 0.042).

Conclusion

Higher SUVmax at pretreatment ¹⁸F-FDG PET/CT was associated with better relapse free survival and overall survival in DLBCL patients after consolidation therapy with ¹³¹I-rituximab. However, because this study has a small number of patients, a phase 3 study with a larger number of patients is needed for clinical application in the future.

18F-FDG PET/CT prognostic role in predicting response to salvage therapy in relapsed/refractory Hodgkin's lymphoma

PURPOSE

To evaluate the response predictors, both clinical and ¹⁸F-FDG PET/CT parameters, in Hodgkin's lymphoma (HL) patients diagnosed with refractory/relapsed disease who were planned to receive salvage therapy.

METHODS

In this retrospective study, all HL patients referred to our center between March 2015 and July 2021 were reviewed. Patients with refractory/relapsed disease who were candidates for salvage therapy were included. ¹⁸F-FDG PET/CT measurements at the time of diagnosis were extracted as the predictors, and the lesions' response at the end of the salvage therapy was considered the outcomes. The Kaplan-Meier method and multiple Cox regression were utilized to find the significant parameters to predict the time to reach the complete response. The statistical significance level was set at a two-sided p-value <0.05.

RESULTS

A total of 303 tumoral lesions from 64 patients were included. Regarding the factors associated with the response, B symptoms (p-value < 0.01), pathologic subtype (p-value < 0.001), and patient stage (p-value < 0.01) were the significant clinical parameters. In addition, SUVmax (p-value = 0.03), SUVmax/hepatic background SUVmax (p-value = 0.04), SUVmean (in all thresholds; 41% p-value = 0.02, 51% p-value = 0.04, 61% p-value = 0.01), and MTV (in all thresholds; 41% p-value = 0.04, 51% p-value = 0.04, 61% p-value = 0.05) were the significant parameters in the ¹⁸F-FDG PET/CT scans. At the median follow-up of 9 months, we found that pathologic subtype (p-value < 0.01), patient stage (p-value = 0.03), SUVmax (p-value = 0.02), SUVmax/hepatic background SUVmax (p-value = 0.03), SUVmean (in all thresholds; 41% p-value = 0.01, 51% p-value = 0.02, 61% p-value = 0.02), and MTV ≥ 41% (p-value = 0.02) were significant predictive factors. Multiple Cox regression showed the pathologic subtype (p-value = 0.02), SUVmax (p-value = 0.02), and MTV ≥ 41% (p-value = 0.04) were the most significant predictors.

CONCLUSION

Our study demonstrated that by knowing the histopathology of the lesions, the pre-treatment ¹⁸F-FDG PET/CT might be able to predict response after salvage therapy in the relapsed/refractory HL.

Staging and response assessment of lymphoma: a brief review of the Lugano classification and the role of FDG-PET/CT

The accurate assessment of initial disease status and therapeutic responses is critical to the optimal management of patients with lymphoma. Currently, staging and treatment response evaluation for lymphoma has been standardized into the Lugano classification. Lugano classification incorporates positron emission tomography (PET) into the existing response criteria, and response assessment using FDG-PET/CT has been proven to predict the prognosis in various lymphoma subtypes effectively. We will briefly review the current staging and response evaluation system and explore the role of functional imaging in the field of lymphoma.

Heart and bladder detection and segmentation on FDG PET/CT by deep learning

Purpose

Positron emission tomography (PET)/ computed tomography (CT) has been extensively used to quantify metabolically active tumors in various oncology indications. However, FDG-PET/CT often encounters false positives in tumor detection due to ¹⁸fluorodeoxyglucose (FDG) accumulation from the heart and bladder that often exhibit similar FDG uptake as tumors. Thus, it is necessary to eliminate this source of physiological noise. Major challenges for this task include: (1) large inter-patient variability in the appearance for the heart and bladder. (2) The size and shape of bladder or heart may appear different on PET and CT. (3) Tumors can be very close or connected to the heart or bladder.

Approach

A deep learning based approach is proposed to segment the heart and bladder on whole body PET/CT automatically. Two 3D U-Nets were developed separately to segment the heart and bladder, where each network receives the PET and CT as a multi-modal input. Data sets were obtained from retrospective clinical trials and include 575 PET/CT for heart segmentation and 538 for bladder segmentation.

Results

The models were evaluated on a test set from an independent trial and achieved a Dice Similarity Coefficient (DSC) of 0.96 for heart segmentation and 0.95 for bladder segmentation, Average Surface Distance (ASD) of 0.44 mm on heart and 0.90 mm on bladder.

Conclusions

This methodology could be a valuable component to the FDG-PET/CT data processing chain by removing FDG physiological noise associated with heart and/or bladder accumulation prior to image analysis by manual, semi- or automated tumor analysis methods.

Lesion-Based Radiomics Signature in Pretherapy 18F-FDG PET Predicts Treatment Response to Ibrutinib in Lymphoma

PURPOSE

The aim of this study was to develop a pretherapy PET/CT-based prediction model for treatment response to ibrutinib in lymphoma patients.

PATIENTS AND METHODS

One hundred sixty-nine lymphoma patients with 2441 lesions were studied retrospectively. All eligible lymphomas on pretherapy 18F-FDG PET images were contoured and segmented for radiomic analysis. Lesion- and patient-based responsiveness to ibrutinib was determined retrospectively using the Lugano classification. PET radiomic features were extracted. A radiomic model was built to predict ibrutinib response. The prognostic significance of the radiomic model was evaluated independently in a test cohort and compared with conventional PET metrics: SUVmax, metabolic tumor volume, and total lesion glycolysis.

RESULTS

The radiomic model had an area under the receiver operating characteristic curve (ROC AUC) of 0.860 (sensitivity, 92.9%, specificity, 81.4%; P < 0.001) for predicting response to ibrutinib, outperforming the SUVmax (ROC AUC, 0.519; P = 0.823), metabolic tumor volume (ROC AUC, 0.579; P = 0.412), total lesion glycolysis (ROC AUC, 0.576; P = 0.199), and a composite model built using all 3 (ROC AUC, 0.562; P = 0.046). The radiomic model increased the probability of accurately predicting ibrutinib-responsive lesions from 84.8% (pretest) to 96.5% (posttest). At the patient level, the model's performance (ROC AUC = 0.811; P = 0.007) was superior to that of conventional PET metrics. Furthermore, the radiomic model showed robustness when validated in treatment subgroups: first (ROC AUC, 0.916; P < 0.001) versus second or greater (ROC AUC, 0.842; P < 0.001) line of defense and single treatment (ROC AUC, 0.931; P < 0.001) versus multiple treatments (ROC AUC, 0.824; P < 0.001).

CONCLUSIONS

We developed and validated a pretherapy PET-based radiomic model to predict response to treatment with ibrutinib in a diverse cohort of lymphoma patients.

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.

Prognostic Impact of Total Lesion Glycolysis (TLG) from Preoperative 18F-FDG PET/CT in Stage II/III Colorectal Adenocarcinoma: Extending the Value of PET/CT for Resectable Disease

We investigated the prognostic role of metabolic parameters from preoperative ¹⁸F-FDG PET/CT in stage II/III colorectal adenocarcinoma. A total of 327 stage II/III colorectal adenocarcinoma patients who underwent curative resection were included. The maximal standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were analyzed for optimal cut-offs and their effect on DFS. Differences in DFS rates and hazard ratios for DFS between cut-offs were statistically significant in SUVmax, MTV2.5, MTV3, TLG 2.5, TLG3, and TLG30%. Factors significantly related to DFS in univariate Cox regression were age, sex, stage, preoperative CEA, SUVmax, MTV2.5, MTV3, TLG2.5, TLG3, and TLG30%. Age, sex, preoperative CEA, and TLG2.5 (p = 0.009) sustained statistically significant difference in multivariate analysis. The 1-, 3-, and 5-year DFS rates for TLG2.5 ≤ 448.5 were 98.1%, 79.6%, and 74.8%, significantly higher than 78.4%, 68.5%, and 61.1% of TLG2.5 > 448.5, respectively (p = 0.012). TLG, a parameter indicating both the metabolic activity and metabolic volume, was the strongest predictor independently associated with DFS, among several PET parameters with statistical significance. These results suggest the potential prognostic value of preoperative ¹⁸F-FDG PET/CT in stage II/III resectable colorectal cancer.

The Role of Pre-therapeutic 18F-FDG PET/CT in Pediatric Hemophagocytic Lymphohistiocytosis With Epstein-Barr Virus Infection

Objective

To evaluate the role of pre-therapeutic ¹⁸F-FDG PET/CT in pediatric hemophagocytic lymphohistiocytosis (HLH) with Epstein-Barr virus (EBV) infection.

Methods

This retrospective study included 29 HLH children (1–16 years) with EBV infection, who underwent pre-therapeutic ¹⁸F-FDG PET/CT from July 2018 to November 2020. Pathology results were considered as the reference standard. These patients were divided into two groups: EBV-induced malignancy-associated HLH (M-HLH, N = 9) and EBV-induced non-malignancy-associated HLH (NM-HLH, N = 20). The regions of interest (ROIs) of the liver, spleen (Sp), bone marrow (BM), lymph nodes (LN), hypermetabolic lesions, liver background (LiBG), and mediastinum (M) were drawn with software 3D-Slicer. The volumetric and metabolic parameters, including maximum standard uptake value (SUV_max), metabolic tumor volume, and total lesion glycolysis of these ROIs, clinical parameters, and laboratory parameters were compared between the two groups. The efficiency of the above parameters in predicting the treatment response and overall survival (OS) was analyzed.

Results

Receiver operating characteristic curve analysis indicated that SUV_max-lesions and SUV_max-LN/M (AUC = 0.822, 0.819, cut-off = 6.04, 5.74, respectively) performed better in differentiating M-HLH from NM-HLH. It had the best diagnostic performance when age was added with the SUV_max-LN/M (AUC = 0.933, sensitivity = 100%, specificity = 85.0%). The presence of extranodal hypermetabolic lesions in multiple organs indicated the M-HLH (P = 0.022). Older age, higher SUV_max-LN and SUV_max-lesions, and the presence of serous effusion were associated with poorer treatment response at the 2nd and 4th week (not reaching partial remission). Multivariate analysis showed that SUV_max-lesions > 7.66 and SUV_max-Sp/LiBG > 2.01 were independent prognostic factors for overall survival (P = 0.025, 0.036, respectively).

Conclusions

¹⁸F-FDG PET/CT could be a valuable technique for identifying the underlying malignancy and predicting prognosis in pediatric HLH with EBV infection. M-HLH could be considered when SUV_max-lesions > 6.04, SUV_max-LN/M > 5.74, and the presence of extranodal hypermetabolic lesions in multiple organs on ¹⁸F-FDG PET/CT. SUV_max-lesions and SUV_max-Sp/LiBG might be independent prognostic factors for OS.

Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions)

Malignant lymphomas are a family of heterogenous disorders caused by clonal proliferation of lymphocytes. 18F-FDG-PET has proven to provide essential information for accurate quantification of disease burden, treatment response evaluation, and prognostication. However, manual delineation of hypermetabolic lesions is often a time-consuming and impractical task. Applications of artificial intelligence (AI) may provide solutions to overcome this challenge. Beyond segmentation and detection of lesions, AI could enhance tumor characterization and heterogeneity quantification, as well as treatment response prediction and recurrence risk stratification. In this scoping review, we have systematically mapped and discussed the current applications of AI (such as detection, classification, segmentation as well as the prediction and prognostication) in lymphoma PET.

Pretherapy metabolic tumor volume associates with response to CD30 CAR T cells in Hodgkin lymphoma

High MTV immediately before lymphodepletion and CD30.CAR-T cell infusion is associated with shorter PFS.

High pretherapy MTV is associated with high circulating CD3⁺PD-1⁺ T cells after CD30.CAR-T infusion.

Our group has recently demonstrated that chimeric antigen receptor T-cell therapy targeting the CD30 antigen (CD30.CAR-T) is highly effective in patients with relapsed and refractory (r/r) classical Hodgkin lymphoma (cHL). Despite high rates of clinical response, relapses and progression were observed in a subset of patients. The objective of this study was to characterize clinical and correlative factors associated with progression-free survival (PFS) after CD30.CAR-T cell therapy. We evaluated correlatives in 27 patients with r/r cHL treated with lymphodepletion and CD30.CAR-T cells. With a median follow-up of 9.5 months, 17 patients (63%) progressed, with a median PFS of 352 days (95% confidence interval: 116-not reached), and 2 patients died (7%) with a median overall survival of not reached. High metabolic tumor volume (MTV, >60 mL) immediately before lymphodepletion and CD30.CAR-T cell infusion was associated with inferior PFS (log rank, P = .02), which persisted after adjusting for lymphodepletion and CAR-T dose (log rank, P = .01 and P = .006, respectively). In contrast, receiving bridging therapy, response to bridging therapy, CD30.CAR-T expansion/persistence, and percentage of CD3⁺PD-1⁺ lymphocytes over the first 6 weeks of therapy were not associated with differences in PFS. In summary, this study reports an association between high baseline MTV immediately before lymphodepletion and CD30.CAR-T cell infusion and worse PFS in patients with r/r cHL. This trial was registered at www.clinicaltrials.gov as #NCT02690545.

Total Lesion Glycolysis Improves Tumor Burden Evaluation and Risk Assessment at Diagnosis in Hodgkin Lymphoma

Hodgkin lymphoma (HL) is a hematological malignancy with an excellent prognosis. However, we still need to identify those patients that could experience failed standard frontline chemotherapy. Tumor burden evaluation and standard decisions are based on Ann Arbor (AA) staging, but this approach may be insufficient in predicting outcomes. We aim to study new ways to assess tumor burden through volume-based PET parameters to improve the risk assessment of HL patients. We retrospectively analyzed 101 patients with HL from two hospitals in the Balearic Islands between 2011 and 2018. Higher metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were significantly associated with a higher incidence of III-IV AA stages, B-symptoms, hypoalbuminemia, lymphopenia, and higher IPS. Standardized uptake value (SUVmax) was significantly related to AA stage and hypoalbuminemia. We found that TLG or the combination of SUVmax, TLG, and MTV significantly improved the risk assessment when compared to AA staging. We conclude that TLG is the best single PET/CT-related tumor-load parameter that significantly improves HL risk assessment when compared to AA staging. If confirmed in a larger and validated sample, this information could be used to modify standard frontline therapy and justifies the inclusion of TLG inside an HL prognostic score.

Value of Combined PET Imaging with [18F]FDG and [68Ga]Ga-PSMA-11 in mCRPC Patients with Worsening Disease during [177Lu]Lu-PSMA-617 RLT

Simple Summary

Prostate-specific membrane antigen (PSMA) is regularly overexpressed in prostate cancer cells. Radioligand therapy (RLT) targeting PSMA has shown impressive results in recent years in treatment of metastatic castration-resistant prostate cancer (mCRPC). In some patients, however, the disease worsens during PSMA-RLT. A proportion of these patients develop a type of metastasis that has intense glucose metabolism but missing or low PSMA expression; these metastases are referred to as ‘mismatch metastases’. We found that combined PET imaging using the radiolabeled glucose analog [¹⁸F]FDG and the PSMA radioligand [⁶⁸Ga]Ga-PSMA-11 is essential to identify patients with mismatch findings, which are associated with significantly worse outcome, especially if the mismatch is located in the liver or of high volume. Consequently, additional treatments or change to another treatment modality appears necessary.

Abstract

Despite the promising results of prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) in metastatic castration-resistant prostate cancer (mCRPC), some patients show worsening disease during PSMA-RLT. We investigated the value of combined [¹⁸F]FDG and [⁶⁸Ga]Ga-PSMA-11 PET imaging in this setting. In n = 29 mCRPC patients with worsening disease after a median of four cycles of [¹⁷⁷Lu]Lu-PSMA-617 RLT, combined [¹⁸F]FDG and [⁶⁸Ga]Ga-PSMA-11 PET imaging was performed to detect [¹⁸F]FDG-avid lesions with low or no PSMA expression (mismatch lesions). To evaluate prognostic implication of mismatch, survival analyses regarding presence, location, and [¹⁸F]FDG PET-derived parameters such as SUV_max, metabolic tumor volume (MTV_m), and total lesion glycolysis (TLG_m) of mismatch findings were performed. Seventeen patients (59%) showed at least one mismatch metastasis. From the time point of combined PET imaging, the median overall survival (OS) of patients with mismatch findings was significantly (p = 0.008) shorter than those without (3.3 vs. 6.1 mo). Patients with a high MTV_m revealed a significantly (p = 0.034) shorter OS of 2.6 mo than patients with low MTV_m (5.3 mo). Furthermore, patients with hepatic mismatch showed a significantly (p = 0.049) shorter OS than those without (2.9 vs. 5.3 mo). Difference in OS regarding SUV_max and TLG_m was not significant. In mCRPC patients with worsening disease during PSMA-RLT, combined [¹⁸F]FDG and [⁶⁸Ga]Ga-PSMA-11 PET imaging is essential to identify mismatch findings, as these are associated with poor outcomes requiring a change in therapy management.

Prognostic Impact of 18F-FDG PET/CT in Patients With Aggressive B-Cell Lymphoma Treated With Anti-CD19 Chimeric Antigen Receptor T Cells

PURPOSE OF THE REPORT

We aimed to evaluate the role of 18F-FDG PET/CT in predicting patient outcome following chimeric antigen receptor T (CAR T) cells infusion in aggressive B-cell lymphoma.

METHODS

18F-FDG PET/CT data before leukapheresis, before CAR T-cell infusion and 1 month (M1) after CAR T-cell infusion, from 72 patients were retrospectively analyzed. SUVmax, total lesion glycolysis (TLG), metabolic tumor volume (MTV), and parameters describing tumor kinetics were calculated for each 18F-FDG PET/CT performed. The aim was to evaluate the prognostic value of 18F-FDG PET/CT metabolic parameters for predicting progression-free survival (PFS) and overall survival (OS) following CAR T-cell therapy.

RESULTS

Regarding PFS, ∆MTVpre-CAR and ∆TLGpre-CAR were found to be more discriminating compared with metabolic parameters at preinfusion. Median PFS in patients with a ∆MTVpre-CAR of less than 300% was 6.8 months (95% confidence interval [CI], 2.8 months to not reached) compared with 2.8 months (95% CI, 0.9-3.0 months) for those with a value of 300% or greater (P = 0.004). Likewise, median PFS in patients with ∆TLGpre-CAR of less than 420% was 6.8 months (95% CI, 2.8 months to not reached) compared with 2.7 months (95% CI, 1.3-3.0 months) for those with a value of 420% or greater (P = 0.0148). Regarding OS, metabolic parameters at M1 were strongly associated with subsequent outcome. SUVmax at M1 with a cutoff value of 14 was the most predictive parameter in multivariate analysis, outweighing other clinicobiological variables (P < 0.0001).

CONCLUSIONS

Disease metabolic volume kinetics before infusion of CAR T cells seems to be superior to initial tumor bulk itself for predicting PFS. For OS, SUVmax at M1 might adequately segregate patients with different prognosis.

Prognostic value of baseline total metabolic tumour volume of 18F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma

Purpose

The aim of this study was to explore the prognostic value of baseline metabolic parameters of ¹⁸F-FDG PET/CT imaging in patients with angioimmunoblastic T-cell lymphoma (AITL).

Materials and methods

Fifty-six AITL patients (average age 64.0 ± 1.3 years) diagnosed pathologically from August 2009 to August 2019 were enrolled in this retrospective study. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), maximum standardized uptake value (SUVmax), and correlated clinical characteristics were collected and analysed. TMTV was computed with the 41% SUVmax threshold method. The chi-square test or Fisher’s exact probability method was used to compare clinical characteristics. Kaplan–Meier curves were used to describe progression-free survival (PFS) and overall survival (OS). The log-rank test was used to analyse the difference within groups. The statistically significant factors in the univariate regression analysis were incorporated into the Cox risk proportional regression model for multivariate survival analysis.

Results

The TMTV cut-off value was 514.6 cm³ from the ROC curve analysis. Forty (71.4%) patients progressed and 31 (55.4%) patients died within a median follow-up time of 19.1 (interquartile range 7.8–34.6) months. The 1-year and 3-year PFS rates were 42.9% and 30.1%, and the 3-year and 5-year OS rates were 45.9% and 34.4%, respectively. Univariate survival analysis showed that high TMTV and TLG may be the factors contributing to poor PFS and OS. Multivariate analysis showed that TMTV and prognostic index for T-cell lymphoma (PIT) were independent parameters for PFS and OS in AITL patients. TMTV, combined with PIT, may have better risk stratification performance than TMTV alone.

Conclusions

Baseline TMTV and PIT were independent prognostic predictors in AITL patients. The combination of TMTV and PIT can facilitate prognostic stratification and contribute to personalized therapy.

Prognostic impact of total metabolic tumor volume in large B-cell lymphoma patients receiving CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapy provides long-term remissions in patients with relapsed or refractory (R/R) large B-cell lymphoma (LBCL). Total metabolic tumor volume (TMTV) assessed by 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET) has a confirmed prognostic value in the setting of chemoimmunotherapy, but its predictive role with CAR T-cell therapy is not fully established. Thirty-five patients with R/R LBCL who received CAR T-cells were included in the study. TMTV and maximum standardized uptake value (SUVmax) were measured at baseline and 1-month after CAR T-cell infusion. Best response included 9 (26%) patients in complete metabolic response (CMR) and 16 (46%) in partial metabolic response (PMR). At a median follow-up of 7.6 months, median PFS and OS were 3.4 and 8.2 months, respectively. A high baseline TMTV (≥ 25 cm³) was associated with a lower PFS (median PFS, 2.3 vs. 8.9 months; HR = 3.44 [95% CI 1.18-10.1], p = 0.02). High baseline TMTV also showed a trend towards shorter OS (HR = 6.3 [95% CI 0.83-47.9], p = 0.08). Baseline SUVmax did not have a significant impact on efficacy endpoints. TMTV and SUVmax values showed no association with adverse events. Metabolic tumor burden parameters measured by 18FDG-PET before CAR T-cell infusion can identify LBCL patients who benefit most from this therapy.

Response to Treatment in IgG4-Related Disease Assessed by Quantitative PET/CT Scan

OBJECTIVE

The aim of this study was to assess disease activity by different PET/CT measurements in IgG4-related disease (IgG4-RD) flares and their correlation with the IgG4-RD responder index (IgG4-RI).

PATIENTS AND METHODS

Patients were retrospectively recruited from a single center in Barcelona, Spain. They all had IgG4-RD flares with an 18F-FDG PET/CT examination performed within the 2 first weeks of the flare onset and another one after at least 3 months of treatment between 2012 and 2018. Epidemiologic, clinical, laboratory, and therapeutic data were collected at baseline and at follow-up. Semiquantitative and volumetric measurements from PET/CT explorations were recorded. In addition, a 5-point visual scale was (adapted Deauville score) trialed. The IgG4-RI was used as the criterion standard to assess response before and after treatment.

RESULTS

Eighteen patients with a total of 23 flares were included. The median time to second PET/CT examination was 7 months. Remission (complete and partial) according to IgG4-RI was observed in 20 flares (87%). All PET/CT measurements (SUVmax and SUVmean, total lesion glycolysis, MTV, and adapted Deauville score) were statistically significantly lower on the follow-up evaluation, except for the size of the lesion. The correlation of all these parameters with the IgG4-RI was positive except for SUVmean and the size of the lesion.

CONCLUSIONS

Semiquantitative, volumetric, and visual parameters in PET/CT scans correlated with response to treatment assessed by IgG4-RI. Volumetric and visual items are less subject to variations and could be used to improve activity scores and treatment strategies.

High metabolic tumor volume is associated with decreased efficacy of axicabtagene ciloleucel in large B-cell lymphoma

High metabolic tumor volume (MTV) predicts worse outcomes in lymphoma treated with chemotherapy. However, it is unknown if this holds for patients treated with axicabtagene ciloleucel (axi-cel), an anti-CD19 targeted chimeric antigen receptor T-cell therapy. The primary objective of this retrospective study was to investigate the relationship between MTV and survival (overall survival [OS] and progression-free survival [PFS]) in patients with relapsed/refractory large B-cell lymphoma (LBCL) treated with axi-cel. Secondary objectives included finding the association of MTV with response rates and toxicity. The MTV values on baseline positron emission tomography of 96 patients were calculated via manual methodology using commercial software. Based on a median MTV cutoff value of 147.5 mL in the first cohort (n = 48), patients were divided into high and low MTV groups. Median follow-up for survivors was 24.98 months (range, 10.59-51.02 months). Patients with low MTV had significantly superior OS (hazard ratio [HR], 0.25; 95% confidence interval [CI], 0.10-0.66) and PFS (HR, 0.40; 95% CI, 0.18-0.89). Results were successfully validated in a second cohort of 48 patients with a median follow-up for survivors of 12.03 months (range, 0.89-25.74 months). Patients with low MTV were found to have superior OS (HR, 0.14; 95% CI, 0.05-0.42) and PFS (HR, 0.29; 95% CI, 0.12-0.69). In conclusion, baseline MTV is associated with OS and PFS in axi-cel recipients with LBCL.

AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients

BACKGROUND

[¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI's usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT.

METHODS

One hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots.

RESULTS

The AI-tool's performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R² = 0.74). Bias was 42 g and 95% limits of agreement ranged from - 736 to 819 g. Agreement was particularly high in smaller lesions.

CONCLUSIONS

The AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.

Prognostic superiority of International Prognostic Index over [18F]FDG PET/CT volumetric parameters in post-transplant lymphoproliferative disorder

Background

Post-transplant lymphoproliferative disorders (PTLDs) are a spectrum of hematological malignancies occurring after solid organ and hematopoietic stem cell transplantation. [¹⁸F]FDG PET/CT is routinely performed at PTLD diagnosis, allowing for both staging of the disease and quantification of volumetric parameters, such as whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). In this retrospective study, we aimed to determine the prognostic value of MTV and TLG in PTLD patients, together with other variables of interest, such as the International Prognostic Index (IPI), organ transplant type, EBV tumor status, time after transplant, albumin levels and PTLD morphology.

Results

A total of 88 patients were included. The 1-, 3-, 5- year overall survival rates were 67%, 58% and 43% respectively. Multivariable analysis indicated that a high IPI (HR: 1.56, 95% CI: 1.13–2.16) and an EBV-negative tumor (HR: 2.71, 95% CI: 1.38–5.32) were associated with poor overall survival. Patients with a kidney transplant had a longer overall survival than any other organ recipients (HR: 0.38 95% CI: 0.16–0.89). IPI was found to be the best predicting parameter of overall survival in our cohort. Whole-body MTV, TLG, time after transplant, hypoalbuminemia and PTLD morphology were not associated with overall survival.

Conclusion

[¹⁸F]FDG PET/CT whole-body volumetric quantitative parameters were not predictive of overall survival in PTLD. In our cohort, high IPI and an EBV-negative tumor were found to predictors of worse overall survival while kidney transplant patients had a longer overall survival compared to other organ transplant recipients

Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography

Introduction: Our aim was to evaluate the performance in clinical research and in clinical routine of a research prototype, called positron emission tomography (PET) Assisted Reporting System (PARS) (Siemens Healthineers) and based on a convolutional neural network (CNN), which is designed to detect suspected cancer sites in fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) PET/computed tomography (CT).

Method: We retrospectively studied two cohorts of patients. The first cohort consisted of research-based patients who underwent PET scans as part of the initial workup for diffuse large B-cell lymphoma (DLBCL). The second cohort consisted of patients who underwent PET scans as part of the evaluation of miscellaneous cancers in clinical routine. In both cohorts, we assessed the correlation between manually and automatically segmented total metabolic tumor volumes (TMTVs), and the overlap between both segmentations (Dice score). For the research cohort, we also compared the prognostic value for progression-free survival (PFS) and overall survival (OS) of manually and automatically obtained TMTVs.

Results: For the first cohort (research cohort), data from 119 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.65. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.68. Both TMTV results were predictive of PFS (hazard ratio: 2.1 and 3.3 for automatically based and manually based TMTVs, respectively) and OS (hazard ratio: 2.4 and 3.1 for automatically based and manually based TMTVs, respectively). For the second cohort (routine cohort), data from 430 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.48. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.61.

Conclusion: The TMTVs determined for the research cohort remain predictive of total and PFS for DLBCL. However, the segmentations and TMTVs determined automatically by the algorithm need to be verified and, sometimes, corrected to be similar to the manual segmentation.

Advanced-stage Hodgkin lymphoma: have effective therapy and modern imaging changed the significance of bulky disease?

The prognostic significance of bulky disease in advanced-stage Hodgkin lymphoma is an area of controversy. Early studies suggested that the presence of bulk was associated with an increased risk of disease relapse. The effect of bulk is less clear in more recent studies. The shift to response-adapted treatment regimens may obscure the prognostic significance of initially bulky disease, as patients with such disease have lower rates of complete metabolic response on early interim scans and thus are more likely to receive intensified chemotherapy. Various definitions of bulk have been used, further complicating interpretation of the available data. Advances in diagnostic imaging enable quantification of the three-dimensional lymphoma volume, which may ultimately become a new routine measure of bulky disease. This review aims to summarize the prognostic significance of bulky disease in advanced-stage HL, the influence of bulk on the choice of therapy, and the changing definition of bulk with advances in diagnostic imaging.

Comparison of clinical and PET-derived prognostic factors in patients with non-Hodgkin lymphoma: a special emphasis on bone marrow involvement

OBJECTIVE

In patients with non-Hodgkin lymphoma (NHL), we investigated F FDG PET/computed tomography (CT) parameters, clinical findings, laboratory parameters, and bone marrow involvement (BMI) status for predictive methods in progression-free survival (PFS) and overall survival (OS), and whether F FDG PET/CT could take the place of bone marrow biopsy (BMB).

METHODS

The performance of F FDG PET/CT (BMPET) was evaluated. The prognostic value of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), stage, international prognostic index (IPI) score, IPI risk, lactate dehydrogenase (LDH), B2 microglobulin, Ki67 proliferation index, and the presence of BMI was evaluated for OS and PFS. Kaplan-Meier curves were drawn for each designated cutoff value, and 5-year PFS and 7-year OS were evaluated using log-rank analysis.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of BMPET and BMB to identify BMI were 69, 100, 86.1, 80, 100%, and 81.6, 100, 92.5, 89, 100%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of BMPET in patients with Ki67- proliferation index >25% were all 100%. BMPET, IPI risk, MTV, and LDH were found to be independent prognostic predictors for PFS, whereas BMPET, SUVmax, and MTV for OS. Five-year PFS analysis estimated as follows: BMPET (+) = 22%, BMPET (-) = 80%, LDH ≤ 437 (U/L) = 86%, LDH > 437 (U/L) = 51%, MTV ≤ 56 (cm) = 87%, MTV > 56 (cm) = 49%, low IPI risk = 87%, intermediate IPI risk = 69%, high IPI risk = 25%. Seven-year OS analysis was found as: SUVmax ≤ 17.6 = 80%, SUVmax > 17.6 = 48%, MTV ≤ 56 (cm) = 84.4%, MTV > 56 (cm) = 45.8%, BMPET (-) = 72.5%, BMPET (+) = 42%.

CONCLUSION

In the Ki-67 proliferation index > 25% group, F FDG PET/CT was able to differentiate BMI independently from NHL subgroups. We recommend using this method with large patient groups. MTV and BMPET were independent prognostic indicators for OS and PFS and may help to determine high-risk patients.

Semi-Quantitative Characterization of Post-Transplant Lymphoproliferative Disorder Morphological Subtypes with [18F]FDG PET/CT

Background: Post-transplant lymphoproliferative disorder (PTLD) is a complication of organ transplantation classified according to the WHO as nondestructive, polymorphic, monomorphic, and classic Hodgkin Lymphoma subtypes. In this retrospective study, we investigated the potential of semi-quantitative 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) PET/computed tomography (CT)-based parameters to differentiate between the PTLD morphological subtypes. Methods: 96 patients with histopathologically confirmed PTLD and baseline [¹⁸F]FDG PET/CT between 2009 and 2019 were included. Extracted semi-quantitative measurements included: Maximum, peak, and mean standardized uptake value (SUV_max, SUV_peak, and SUV_mean). Results: Median SUVs were highest for monomorphic PTLD followed by polymorphic and nondestructive subtypes. The median SUV_peak at the biopsy site was significantly higher in monomorphic PTLD (17.8, interquartile range (IQR):16) than in polymorphic subtypes (9.8, IQR:13.4) and nondestructive (4.1, IQR:6.1) (p = 0.04 and p ≤ 0.01, respectively). An SUV_peak ≥ 24.8 was always indicative of a monomorphic PTLD in our dataset. Nevertheless, there was a considerable overlap in SUV across the different morphologies. Conclusion: The median SUV_peak at the biopsy site was significantly higher in monomorphic PTLD than polymorphic and nondestructive subtypes. However, due to significant SUV overlap across the different subtypes, these values may only serve as an indication of PTLD morphology, and SUV-based parameters cannot replace histopathological classification.