FDG-PET/CT in the management of lymphomas: current status and future directions

Mapping the research landscape of PET/CT in lymphoma: insights from a bibliometric analysis

Objective

This study provides a comprehensive bibliometric analysis of research trends in Positron Emission Tomography/Computed Tomography (PET/CT) applications for lymphoma, aiming to identify key contributors, emerging topics, and collaboration patterns within the field.

Methods

Data from the Web of Science Core Collection (2004-2024) were analyzed. Original articles and reviews in English on PET/CT in lymphoma staging, response assessment, or prognosis were included, while case reports, meeting abstracts, and editorials were excluded. Using CiteSpace, VOSviewer, and Bibliometrix R, we evaluated country/institutional contributions, co-citation networks, keyword trends, and employed linear regression for trend forecasting.

Results

A total of 2,962 papers related to PET/CT and lymphoma were published during the study period. The annual publication volume increased significantly, peaking in 2021 with 281 papers, followed by a decline to 260 in 2023, potentially linked to COVID-19-related research disruptions. The United States and China led in publication volume, contributing over 40% of global publications. Leading institutions included UNICANCER and Assistance Publique Hôpitaux de Paris. Influential authors such as Sally F. Barrington and Michel Meignan were identified. The European Journal of Nuclear Medicine and Molecular Imaging and the Journal of Nuclear Medicine were the top journals in this field. Key research themes included staging, response assessment, prognosis, and the role of PET/CT in personalized treatment approaches.

Conclusion

This bibliometric analysis highlights the significant growth and evolving trends in PET/CT research for lymphoma. The findings underscore the critical role of PET/CT in advancing precision medicine, informing future research directions, and optimizing clinical practices in lymphoma management.

The Role of Platelet to Lymphocyte Ratio (PLR) in Predicting Early Treatment Response in Diffuse Large B Cell Lymphoma

Background

Systemic inflammatory response in diffuse large B-cell lymphoma (DLBCL) is closely related to disease prognosis. Our aim is to determine the role of pretreatment platelet-to-lymphocyte ratio (PLR) in predicting early treatment response in DLBCL patients.

Methods

This retrospective study included 94 patients. The correlation of PLR at the time of diagnosis with early treatment response was evaluated.

Results

66 patients responded to treatment and 28 patients were unresponsive or partially responsive. In univariate analysis, age, eastern cooperative oncology group performance status (ECOG-PS), disease stage, extranodal involvement, neutrophil-to-lymphocyte ratio (NLR), PLR, hemoglobin, albumin, lymphocyte, platelet (HALP) score were found to predict response to treatment. Multivariate analysis revealed that PLR and ECOG-PS were independent predictors of early treatment response.

Conclusion

PLR can be used by clinicians as an effective, inexpensive inflammatory parameter supplementary to the IPI score to predict early treatment response to chemoimmunotherapy. Treatment of patients with DLBCL with high PLR at the time of diagnosis with more potent regimens may be a rational approach for patients to benefit more from treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12288-024-01839-2.

Development and Preclinical Evaluation of [64Cu]Cu-NOTA-ABDB6: A CD70 and Albumin Dual-Binding Tracer with Improved Pharmacokinetics

CD70 is an emerging biomarker for both solid tumors and hematologic malignancies, highlighting the urgent need for a molecular imaging tracer capable of visualizing CD70 with favorable pharmacokinetics. Methods: ABDB6 was prepared by fusing the albumin-binding domain ABD035 with the CD70-targeting single-domain antibody RCCB6, which we previously reported. The resulting ABDB6 was then conjugated to the bifunctional chelator p-SCN-NOTA and labeled with 64Cu to produce [64Cu]Cu-NOTA-ABDB6. Flow cytometry was used to screen 6 lymphoma cell lines with varying CD70 expression levels. Cell uptake and in vivo immuno-PET imaging studies were conducted to fully evaluate the pharmacokinetic properties and tumor-targeting efficacy of [64Cu]Cu-NOTA-ABDB6. An ABDB6 blocking study was performed to validate the targeting specificity of [64Cu]Cu-NOTA-ABDB6, followed by immunohistochemistry and fluorescent immunostaining studies to correlate tracer uptake with CD70 expression. Results: 64Cu labeling of ABDB6 achieved a high radiochemical yield and specific activity. Significant CD70 expression was observed in 5 lymphoma cell lines (TMD8, HBL1, OCI-LY10, LCL-EBV, and type III latency Burkitt lymphoma [BL] cells) but not in type I latency BL cells, which served as the negative control. [64Cu]Cu-NOTA-ABDB6 exhibited good affinity for CD70 protein at the nanomolar level (inhibitory concentration of 50%, 91.57 nM) and specificity in binding to human CD70. Immuno-PET imaging of [64Cu]Cu-NOTA-ABDB6 demonstrated excellent tumor uptake and retention in various CD70-positive lymphoma models (TMD8, type III latency BL, and LCL-EBV), with the highest tumor uptake values recorded as 24.67 ± 1.36, 18.02 ± 4.29, and 14.68 ± 1.20 percentage injected dose per gram of tissue (%ID/g) at 48 h after injection, respectively. These tumor uptake values were significantly higher than that of the CD70-negative type I latency BL tumor, which had an uptake of 3.59 ± 0.28 %ID/g at the same scanning time point (P < 0.05). In the TMD8 blocking group, tumor uptake was 5.99 ± 1.20 %ID/g at 48 h after injection, significantly lower than in the TMD8 control group (P < 0.01). Both biodistribution and histology results corroborated these imaging findings. Conclusion: [64Cu]Cu-NOTA-ABDB6 immuno-PET effectively visualized varying levels of CD70 in different lymphoma models. Its clinical potential may provide insights into CD70 expression in lymphoma patients.

Role of Total Body PET/CT in Inflammatory Disorders

Inflammatory disorders historically have been difficult to monitor with conventional PET imaging due to limitations including radiation exposure, lack of validated imaging biomarkers, low spatial resolution, and long acquisition durations. However, the recent development of long-axial field-of-view (LAFOV) PET/CT scanners may allow utilization of novel noninvasive biomarkers to diagnose, predict outcomes, and monitor therapeutic response of inflammatory conditions. LAFOV PET scanners can image most of the human body (if not the entire body) simultaneously in one bed position, with improved signal collection efficiency compared to conventional PET scanners. This allows for imaging with shorter acquisition durations, decreased injected radiotracer dose, prolonged uptake times, or a combination of any of these. In addition, LAFOV PET scanners enable whole-body dynamic imaging. Altogether, these intrinsically superior capabilities in assessing both local and systemic diseases, have allowed these scanners to make increasingly significant contributions to the assessment of inflammatory conditions. This review aims to further explore the role and benefits of LAFOV scanners for imaging various inflammatory conditions while addressing future developments and challenges faced by this technology.

The predictive power of 18F-FDG PET/CT two-lesions radiomics and conventional models in classical Hodgkin's Lymphoma: a comparative retrospectively-validated study

In a previous preliminary study, radiomic features from the largest and the hottest lesion in baseline 18F-FDG PET/CT (bPET/CT) of classical Hodgkin's Lymphoma (cHL) predicted early response-to-treatment and prognosis. Aim of this large retrospectively-validated study is to evaluate the predictive role of two-lesions radiomics in comparison with other clinical and conventional PET/CT models. cHL patients with bPET/CT between 2010 and 2020 were retrospectively included and randomized into training-validation sets. Target lesions were: Lesion_A, with largest axial diameter (Dmax); Lesion_B, with highest SUVmax. Total-metabolic-tumor-volume (TMTV) was calculated and 212 radiomic features were extracted. PET/CT features were harmonized using ComBat across two scanners. Outcomes were progression-free-survival (PFS) and Deauville Score at interim PET/CT (DS). For each outcome, three predictive models and their combinations were trained and validated: - radiomic model "R"; - conventional PET/CT model "P"; - clinical model "C". 197 patients were included (training = 118; validation = 79): 38/197 (19%) patients had adverse events and 42/193 (22%) had DS ≥ 4. In the training phase, only one radiomic feature was selected for PFS prediction in model "R" (Lesion_B F_cm.corr, C-index 66.9%). Best "C" model combined stage and IPS (C-index 74.8%), while optimal "P" model combined TMTV and Dmax (C-index 63.3%). After internal validation, "C", "C + R", "R + P" and "C + R + P" significantly predicted PFS. The best validated model was "C + R" (C-index 66.3%). No model was validated for DS prediction. In this large retrospectively-validated study, a combination of baseline 18F-FDG PET/CT two-lesions radiomics and other conventional models showed an added prognostic power in patients with cHL. As single models, conventional clinical parameters maintain their prognostic power, while radiomics or conventional PET/CT alone seem to be sub-optimal to predict survival.

Predominantly multiple focal non-cystic renal lesions: an imaging approach

Multiple non-cystic renal lesions are occasionally discovered during imaging for various reasons and poses a diagnostic challenge to the practicing radiologist. These lesions may appear as a primary or dominant imaging finding or may be an additional abnormality in the setting of multiorgan involvement. Awareness of the imaging appearance of the various entities presenting as renal lesions integrated with associated extrarenal imaging findings along with clinical information is crucial for a proper diagnostic approach and patient work-up. This review summarizes the most relevant causes of infectious, inflammatory, vascular, and neoplastic disorders presenting as predominantly multiple focal non-cystic lesions.

Clinical scoring systems, molecular subtypes and baseline [18F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous hematological malignancy resulting in a range of outcomes, and the early prediction of these outcomes has important implications for patient management. Clinical scoring systems provide the most commonly used prognostic evaluation criteria, and the value of genetic testing has also been confirmed by in-depth research on molecular typing. [18F]-fluorodeoxyglucose positron emission tomography / computed tomography ([18F]FDG PET/CT) is an invaluable tool for predicting DLBCL progression. Conventional baseline image-based parameters and machine learning models have been used in prognostic FDG PET/CT studies of DLBCL; however, numerous studies have shown that combinations of baseline clinical scoring systems, molecular subtypes, and parameters and models based on baseline FDG PET/CT image may provide better predictions of patient outcomes and aid clinical decision-making in patients with DLBCL.

Prominent tissue hemophagocytic lymphohistiocytosis obscuring primary cutaneous gamma/delta (γδ) T-cell lymphoma

Primary cutaneous gamma/delta (γδ) T-cell lymphoma (PCGDTCL) is a rare, aggressive malignant neoplasm of γδ T lymphocytes arising within the skin and subcutis. We present a challenging case of PCGDTCL diagnosed in a 35-year-old male soldier who presented with constitutional symptoms, pancytopenia, hemophagocytic lymphohistiocytosis (HLH), disseminated lymphadenopathy, and cutaneous lesions on his extremities and back following a deployment to Iraq and Syria. Histopathologic evaluation of an excisional biopsy showed that PCGDTCL can be focal, localized to the subcutaneous adipose tissue, and obscured by predominant HLH in the surrounding tissues. Pathologists should recognize that the diagnosis of PCGDTCL may be confounded by florid HLH and require multiple biopsies and a comprehensive immunohistochemical panel.

A Nomogram-Based Prognostic Model for Lymphoma Patients Initially Presenting with Fever of Unknown Origin

Background

Patients with lymphoma who present with fever of unknown origin (FUO) as an initial symptom lack specific clinical feature analysis, prognostic factor analysis, and existing prognostic models. We aim to create a prognostic model for these patients to improve prognosis and risk assessment.

Methods

A total of 555 lymphoma patients with FUO as initial symptom studied at Huadong Hospital affiliated with Fudan University. Univariable Cox regression identified outcome predictors, analyzed by LASSO Cox. Multifactorial Cox on screened coefficients determined independent prognostic factors and nomogram model. The validity of the nomogram was evaluated through bootstrap sampling, calibration curves for model calibration, time-dependent ROC curve analysis for discrimination assessment, and decision curve analysis for evaluating clinical usefulness. Further validation involved utilizing Kaplan-Meier curves and Log rank tests. Lastly, X-tile software determined the optimal cutoff point for the nomogram score by comparing it with the traditional International Prognostic Index (IPI) scoring system.

Results

The entire cohort was divided into a training cohort (n=388) and a validation cohort (n=167). These risk factors (cell pathologic type, performance status score, Ann Arbor staging, thrombocytopenia, and raised direct bilirubin) were used to construct a web-based dynamic survival rate calculator for lymphoma patients initially presenting with FUO. The lymphoma-specific nomogram demonstrated good consistency and efficacy in predicting the model's risk stratification. Compared to the IPI scoring system, the nomogram model had higher AUC values for different clinical endpoints. The new nomogram prognostic model showed better differentiation of risk groups compared to traditional IPI scoring.

Conclusion

Our study developed and validated a prognostic nomogram for lymphoma patients initially presenting with FUO, demonstrating robust predictive efficacy and risk stratification ability. Furthermore, we have successfully implemented this model into a web-based dynamic survival rate calculator.

Haemato-radiology: the role of the radiologist at MDT

Haemato-radiology represents a relatively newly emerging, vast, and complex area of diagnostic imaging. Its complexity arises from the multimodality nature of patient assessment, the multisystem presentation of haematological malignancies and their complications, and the volume of imaging required for diagnosis and follow-up of the fifth most common malignancy type in the United Kingdom. Decisive and accurate assessment of disease by radiologists is at the heart of the haemato-oncology multidisciplinary team (MDT) and therefore essential for providing optimal patient care. We hope to support radiologists leading the MDT by streamlining the vast information in this field, emphasizing the most recent, evidence-based guidelines, and internationally accepted criteria for reporting imaging of lymphoma and myeloma. We also cover the various disease and treatment complications frequently presented to the MDT.

Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using 18F-FDG PET/CT Imaging: Contribution of Artificial Intelligence and Radiomics Analysis

Lymphoma, encompassing a wide spectrum of immune system malignancies, presents significant complexities in its early detection, management, and prognosis assessment since it can mimic post-infectious/inflammatory diseases. The heterogeneous nature of lymphoma makes it challenging to definitively pinpoint valuable biomarkers for predicting tumor biology and selecting the most effective treatment strategies. Although molecular imaging modalities, such as positron emission tomography/computed tomography (PET/CT), specifically 18F-FDG PET/CT, hold significant importance in the diagnosis of lymphoma, prognostication, and assessment of treatment response, they still face significant challenges. Over the past few years, radiomics and artificial intelligence (AI) have surfaced as valuable tools for detecting subtle features within medical images that may not be easily discerned by visual assessment. The rapid expansion of AI and its application in medicine/radiomics is opening up new opportunities in the nuclear medicine field. Radiomics and AI capabilities seem to hold promise across various clinical scenarios related to lymphoma. Nevertheless, the need for more extensive prospective trials is evident to substantiate their reliability and standardize their applications. This review aims to provide a comprehensive perspective on the current literature regarding the application of AI and radiomics applied/extracted on/from 18F-FDG PET/CT in the management of lymphoma patients.

Evaluating 64 Cu-DOTA-rituximab as a PET agent in patients with B-cell lymphoma: a head-to-head comparison with 18 F-fluorodeoxyglucose PET/computed tomography

BACKGROUND

This study aimed to evaluate the biodistribution of 64 Cu-DOTA-rituximab and its diagnostic feasibility for lymphoma using CD20-targeted 64 Cu-DOTA-rituximab PET/computed tomography (PET/CT).

METHODS

A prospective study involving six patients diagnosed with lymphoma was conducted between January 2022 and January 2023. These patients underwent 18 F-fluorodeoxyglucose ( 18 F-FDG) and 64 Cu-DOTA-rituximab PET/CT scans. 64 Cu-DOTA-rituximab PET/CT images were acquired at 1, 24, and 48 h after administering 64 Cu-DOTA-rituximab to assess the biodistribution and dosimetry over time. The observed lymph nodes were categorized into specific regions, including cervical and supraclavicular, axillary and infraclavicular, mediastinal, hilar, abdominal paraaortic and retroperitoneal, iliac, mesenteric, and inguinal regions, to compare the diagnostic ability of 18 F-FDG and 64 Cu-DOTA-rituximab PET/CT in detecting lymphoma lesions. Furthermore, the tumor-to-background ratio was calculated and compared with the maximum standardized uptake (SUV max ) of the tumors and the mean standardized uptake (SUV mean ) of normal organs. Internal radiation dosimetry was determined using the OLINDA/EXM software.

RESULTS

64 Cu-DOTA-rituximab uptake in lymph nodes associated with lymphoma progressively increased from 1 to 48 h after injection. In contrast, 64 Cu-DOTA-rituximab uptake in normal organs, such as blood, lung, kidney, bladder, muscle, bone, and brain, decreased over time, whereas it increased in the liver and spleen. When it comes to the comparison between 64 Cu-DOTA-rituximab and 18 F-FDG, the SUV max of tumors was higher on 64 Cu-DOTA-rituximab PET/CT (18.1 ± 8.3) than on 18 F-FDG PET/CT (5.2 ± 1.5). Additionally, the tumor-to-background ratio, measured using the SUV mean of normal muscles, was higher on 64 Cu-DOTA-rituximab PET/CT (55.7 ± 31.0) than on 18 F-FDG PET/CT (8.6 ± 2.8). No adverse events related to 64 Cu-DOTA-rituximab injection were reported.

CONCLUSION

The results of this study demonstrate the feasibility of using 64 Cu-DOTA-rituximab PET/CT to evaluate the CD20 expression. The increased 64 Cu-DOTA-rituximab uptake in lymph nodes associated with tumors, higher SUV max , and tumor-to-muscle ratios observed with 64 Cu-DOTA-rituximab PET/CT compared with 18 F-FDG PET/CT, highlight the diagnostic potential of this imaging modality.

Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome

PURPOSE

Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.

METHODS

[18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score.

RESULTS

Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).

CONCLUSIONS

Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline 18F-FDG PET/CT of Lymphoma Patients: A Milestone Toward Clinical Implementation

Total metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker. Methods: Sixty baseline 18F-FDG PET/CT scans were identified with a range of disease distributions (20 follicular, 20 Hodgkin, and 20 diffuse large B-cell lymphoma). TMTV was measured by 12 nuclear medicine experts, each analyzing 20 cases split across subtypes, with each case processed by 3-4 readers. LIFEx or ACCURATE software was chosen according to reader preference. Analysis was performed stepwise: TMTV1 with automated preselection of lesions using an SUV of at least 4 and a volume of at least 3 cm3 with single-click removal of physiologic uptake; TMTV2 with additional removal of reactive bone marrow and spleen with single clicks; TMTV3 with manual editing to remove other physiologic uptake, if required; and TMTV4 with optional addition of lesions using mouse clicks with an SUV of at least 4 (no volume threshold). Results: The final TMTV (TMTV4) ranged from 8 to 2,288 cm3, showing excellent agreement among all readers in 87% of cases (52/60) with a difference of less than 10% or less than 10 cm3 In 70% of the cases, TMTV4 equaled TMTV1, requiring no additional reader interaction. Differences in the TMTV4 were exclusively related to reader interpretation of lesion inclusion or physiologic high-uptake region removal, not to the choice of software. For 5 cases, large TMTV differences (>25%) were due to disagreement about inclusion of diffuse splenic uptake. Conclusion: The proposed segmentation method enabled highly reproducible TMTV measurements, with minimal reader interaction in 70% of the patients. The inclusion or exclusion of diffuse splenic uptake requires definition of specific criteria according to lymphoma subtype. The publicly available proposed benchmark allows comparison of study results and could serve as a reference to test improvements using other segmentation approaches.

Advances in biology, diagnosis and treatment of DLBCL

Diffuse large B-cell lymphoma (DLBCL), with approximately 150,000 new cases worldwide each year, represent nearly 30% of all cases of non-Hodgkin lymphoma (NHL) and are phenotypically and genetically heterogeneous. A gene-expression profile (GEP) has identified at least three major subtypes of DLBCL, each of which has distinct clinical, biological, and genetic features: activated B-cell (ABC)-like DLBCL, germinal-center B-cell (GCB)-like DLBCL, and unclassified. Different origins are associated with different responses to chemotherapy and targeted agents. Despite DLBCL being a highly heterogeneous disease, more than 60% of patients with DLBCL can be cured after using rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) to inhibit the growth of cancer cells while targeting the CD20 receptor. In recent decades, the improvement of diagnostic levels has led to a refinement classification of DLBCL and the development of new therapeutic approaches. The objective of this review was to summarize the latest studies examining genetic lesions and therapies for DLBCL.

Feasibility of a deep-inspiration breath-hold [18F]AlF-NOTA-LM3 PET/CT imaging on upper-abdominal lesions in NET patients: in comparison with respiratory-gated PET/CT

PURPOSES

To explore the clinical feasibility and efficacy of a deep inspiration breath-hold (BH) PET/CT using [18F]AlF-NOTA-LM3 on upper abdominal lesions in patients with neuroendocrine tumors (NETs).

METHODS

Twenty-three patients underwent a free-breath (FB) whole-body PET/CT, including a 10 min/bed scan for the upper abdomen with a vital signal monitoring for respiratory gating (RG) followed by a 20-second BH PET/CT covering the same axial range. For the upper abdomen bed, the following PET series was reconstructed: a 2-min FB PET; RG PET (6 bins); a 20-second and 15-second BH PET (BH_15 and BH_20). Semi-quantitative analysis was performed to compare liver SUVmean, lesion SUVmax, MTV, its percentage difference and target-to-background ratio (TBR) between both BH PET and RG PET images. Subgroup analysis considered lesion location, MTV and SUVmax. A 5-point Likert scale was used to perform visual analysis and any missed or additional lesions were identified compared with RG PET.

RESULTS

Quantitative analysis on overall lesions (n = 78) revealed higher SUVmax and TBR, and smaller MTV for both BH PET compared to FB and RG PET, with lesion location-specific variations. Neither significant difference was observed in all metrics between RG and FB PET in larger lesions, nor in MTV in lower-uptake lesions. However, both BH PET significantly enhanced these measurements. In the visual analysis, both BH PET showed noninferior performance to RG PET, and were evaluated clinically acceptable. Additional and missed lesions were observed in FB and both BH PET compared with RG PET, but didn't alter the clinical management. The BH_15 PET showed comparable performance to BH_20 PET in any comparison.

CONCLUSION

The BH PET/CT using [18F]AlF-NOTA-LM3 is effective in detecting upper abdominal lesions, offering more accurate quantitative measurements. Using a novel PET/CT scanner, a 15-second BH PET can provide comparable and superior performance to RG PET, indicating potential feasibility in clinical routines.

Minimal residual disease detection in lymphoma: methods, procedures and clinical significance

Lymphoma is a highly heterogeneous lymphohematopoietic tumor. As our understanding of the biological and pathological characteristics of lymphoma improves, we are identifying an increasing number of lymphoma subtypes. Genotyping has enhanced our ability to diagnose, treat, and monitor the prognosis of lymphoma. Despite significant improvements in treatment effectiveness, traditional methods for assessing disease response and monitoring prognosis are imperfect, and there is no significant improvement in overall remission rates for lymphoma patients. Minimal Residual Disease (MRD) is often indicative of refractory disease or early relapse. For lymphoma patients, personalized MRD monitoring techniques offer an efficient means to estimate disease remission levels, predict early relapse risk, and assess the effectiveness of new drug regimens. In this review, we delve into the MRD procedures in lymphoma, including sample selection and requirements, detection methods and their limitations and advantages, result interpretation. Besides, we also introduce the clinical applications of MRD detection in lymphoma.

Two Cases of Synchronous Hodgkin Lymphoma and Papillary Thyroid Carcinoma in 18 F-FDG PET/CT

ABSTRACT

The concurrence of Hodgkin lymphoma and papillary thyroid carcinoma is a rare clinical event. Two women presented with a painless mass in the neck that was suspected malignancy by ultrasonography. Both cases shown in the 18 F-FDG PET/CT images demonstrated multiple foci of increased FDG uptake in the neck, mimicking thyroid carcinoma with contralateral cervical lymph node metastases. Unexpectedly, the postoperative pathologies confirmed the thyroid lesion of papillary carcinoma and contralateral cervical lymph nodes of classical Hodgkin lymphoma.

Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy characterized by varied responses to treatment and prognoses. Understanding the metabolic characteristics driving DLBCL progression is crucial for developing personalized therapies.

METHODS

This study utilized multiple omics technologies including single-cell transcriptomics (n = 5), bulk transcriptomics (n = 966), spatial transcriptomics (n = 10), immunohistochemistry (n = 34), multiple immunofluorescence (n = 20) and to elucidate the metabolic features of highly malignant DLBCL cells and tumor-associated macrophages (TAMs), along with their associated tumor microenvironment. Metabolic pathway analysis facilitated by scMetabolism, and integrated analysis via hdWGCNA, identified glycolysis genes correlating with malignancy, and the prognostic value of glycolysis genes (STMN1, ENO1, PKM, and CDK1) and TAMs were verified.

RESULTS

High-glycolysis malignant DLBCL tissues exhibited an immunosuppressive microenvironment characterized by abundant IFN_TAMs (CD68+CXCL10+PD-L1+) and diminished CD8+ T cell infiltration. Glycolysis genes were positively correlated with malignancy degree. IFN_TAMs exhibited high glycolysis activity and closely communicating with high-malignancy DLBCL cells identified within datasets. The glycolysis score, evaluated by seven genes, emerged as an independent prognostic factor (HR = 1.796, 95% CI: 1.077-2.995, p = 0.025 and HR = 2.631, 95% CI: 1.207-5.735, p = 0.015) along with IFN_TAMs were positively correlated with poor survival (p < 0.05) in DLBCL. Immunohistochemical validation of glycolysis markers (STMN1, ENO1, PKM, and CDK1) and multiple immunofluorescence validation of IFN_TAMs underscored their prognostic value (p < 0.05) in DLBCL.

CONCLUSIONS

This study underscores the significance of glycolysis in tumor progression and modulation of the immune microenvironment. The identified glycolysis genes and IFN_TAMs represent potential prognostic markers and therapeutic targets in DLBCL.

Meta-analysis on the efficacy of allogeneic hematopoietic stem cell transplantation to treat malignant lymphoma

The goal of the study involved the comparison of clinical efficacy of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and autologous hematopoietic stem cell transplantation (auto-HSCT) in the treatment of malignant lymphoma (ML). The effectiveness of allo-HSCT versus auto-HSCT in the treatment of ML was compared by searching EMBASE, PubMed, Web of Science, and the Cochrane Library for relevant studies. The confidence intervals (CI) and odds ratio (OR) of the article's outcomes were described by a forest plot. Finally, 972 patients in seven articles were included. Overall survival (OS) did not differ significantly between allo-HSCT and auto-HSCT groups (OR  =  0.87, 95% CI: 0.66-1.14, P  =  0.31). Furthermore, there was no significant difference in adverse reactions (AR) between the two groups (OR  =  1.35, 95% CI: 0.81-2.24, P  =  0.25). We observed a significant difference in progression-free survival (PFS) between the two groups (OR  =  4.14, 95% CI: 2.93-5.35, P < 0.01). There was no evidence of publication bias in this meta-analysis. The incidence of OS and AR differ significantly between allo-HSCT and auto-HSCT, but the PFS was longer in ML patients who received allo-HSCT.

The Diagnostic Performance of 2-[18F]FDG PET/CT in Identifying Richter Transformation in Chronic Lymphocytic Leukemia: An Updated Systematic Review and Bivariate Meta-Analysis

Richter transformation is a rare phenomenon characterized by the transformation of cell chronic lymphocytic leukemia (CLL) into a more aggressive lymphoma variant. The early identification of CLLs with a high risk of RT is fundamental. In this field, 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) has been shown to be a non-invasive and promising tool, but apparently, unclear data seem to be present in the literature. This systematic review and bivariate meta-analysis aimed to investigate the diagnostic performance of 2-[18F]FDG PET/CT and its parameters in predicting RT. Between 2006 and 2024, 15 studies were published on this topic, including 1593 CLL patients. Among semiquantitative variables, SUVmax was the most investigated, and the best threshold derived for detecting RT was five. With this cut-off value, a pooled sensitivity of 86.8% (95% CI: 78.5-93.3), a pooled specificity of 48.1% (95% CI: 27-69.9), a pooled negative predictive value of 90.5% (95% CI: 88.4-92.4), a pooled negative likelihood ratio of 0.35 (95% CI: 0.17-0.70), a pooled positive likelihood ratio of 1.8 (95% CI: 1.3-2.4), and a pooled diagnostic odds ratio of 6.7 (3.5-12.5) were obtained. With a higher cut-off (SUVmax = 10), the specificity increased while the sensitivity reduced. The other metabolic features, like metabolic tumor volume, total lesion glycolysis, and radiomic features, were only marginally investigated with controversial evidence.

Real-World Challenges of Managing Diffuse Large B-Cell Lymphoma in a Developing Country

PURPOSE

To highlight challenges and cancer care disparities in patients of diffuse large B-cell lymphoma management in resource-constrained settings.

MATERIALS AND METHODS

This multicenter retrospective study included 738 patients from 12 public and private sector hematology-oncology centers across Pakistan. Patients were divided into limited-resource and enhanced-resource settings as per national diffuse large B-cell lymphoma (DLBCL) guidelines.

RESULTS

The median age at diagnosis was 47 years (range, 14-89). Male:female ratio was 2.5:1. Majority of the patients (69.3%) were treated in limited-resource settings. Computed tomography was used as a staging modality in 442 (60%) patients. Limited-stage DLBCL was present in 13.5% of patients, while 86.3% had advanced-stage disease at diagnosis. First-line regimens included rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone in 56% and cyclophosphamide, doxorubicin, vincristine, prednisone in 34% of patients, while 10% of patients received palliative regimens upfront. Of evaluable data, complete remission was documented in 299 (74.4%) patients, 39 (9.8%) had partial response and 63 (13.5%) had progressive disease. Disease-free survival (DFS) and overall survival (OS) status were not available for 345 (46.8%) patients at the time of data collection. Overall study cohort had a median follow-up of 2.2 years with a median OS of 3.6 years (95% CI, 3.1 to 4.1), median DFS of 3.1 years (95% CI, 2.6 to 3.6), and a 5-year OS of 40% and DFS of 36%.

CONCLUSION

Patients from low- and middle-income countries present at an earlier age and have more advanced disease. Patients were frequently lost to follow-up, and record keeping was inadequate more so in patients treated in limited-resource settings. There is a need to establish a national lymphoma registry, improve record keeping, and standardize treatments to ensure improvement in treatment outcomes.

Progression of Myocardial 18F-FDG Uptake in a Patient with Cardiotoxicity

The objective of this case report was to present the progression of chemotherapy-induced cardiotoxicity in a patient with lymphoma, highlighting the importance of myocardial fluor-18-fluorodeoxyglucose (18F-FDG) uptake by positron emission tomography coupled with computed tomography (PET/CT). 43-year-old female patient with uterine lymphoma, who underwent hysterectomy followed by three chemotherapy regimens and radiotherapy. The patient had episodes of acute heart failure two years after chemotherapy. Echocardiogram revealed a reduction in left ventricular ejection fraction (LVEF). A retrospective analysis of 18F-FDG PET/CT showed an increase in myocardial uptake in all tests performed during oncologic treatment. Despite disease remission, the patient developed heart failure with reduced LVEF. During chemotherapy, there was a diffuse, significant increase in myocardial 18F-FDG uptake, which preceded the decrease in myocardial performance and seemed to reflect metabolic changes in cardiomyocytes, related to cardiotoxicity. Would an analysis of myocardial 18F-FDG uptake yield a different cardiac outcome in this patient? This question is relevant, considering that other patients may benefit from the use of PET as an early marker of cardiotoxicity. Imaging tests are essential in the follow-up of patients at risk of cardiotoxicity. Although echocardiography remains the main imaging test in the diagnosis of cardiotoxicity, 18F-FDG PET/CT may be a powerful tool for the early diagnosis of this condition.

Prognostic value of the peripheral blood lymphocyte/monocyte ratio combined with 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma

OBJECTIVE

To explore the prognostic value of the peripheral blood lymphocyte/monocyte ratio (LMR) combined with 18F-FDG PET/CT for diffuse large B-cell lymphoma (DLBCL).

METHODS

The clinical data of 203 patients with primary DLBCL who were hospitalized to the First People's Hospital of Lianyungang between January 2017 and December 2022 were retrospectively analyzed. Before and after three courses of treatment, PET/CT was performed on forty DLBCL patients. The subject operating characteristic (ROC) curve has been employed to determine the most effective LMR cutoff points. According to the criteria for assessing the efficacy of Lugano lymphoma, the PET/CT findings after 3 courses of treatment were specified as complete remission (CR), partial remission (PR), stable disease (SD) and disease progression (PD). The CR group, PR+SD group, and PD group were the three groups created from the four outcomes. Results were analyzed using the Cox proportional risk model, the Kaplan-Meier method (K-M), and the log-rank test.

RESULTS

An optimal cutoff point of 3.00 for the LMR in 203 patients was determined by the SPSS 26 software ROC curve. When LMR≥3.00, the 1-year, 3-year, and 5-year OS (Overall Survival) rates are 98%, 88%, and 64% respectively, and the PFS (Progression-free Survival) rates are 90%, 75%, and 56% respectively. When LMR <3.00, the 1-year, 3-year, and 5-year OS rates are 96%, 72%, and 28% respectively, and the PFS rates are 83%, 60%, and 28% respectively. A lower LMR was substantially related with shorter OS, and PFS, according to a K-M survival analysis (P<0.005). LMR<3.00 was an independent predictor of OS, based on a multifactorial Cox analysis (P=0.037). K-M survival analysis of the 18F-FDG PET/CT results of 40 patients revealed that both OS and PFS were statistically significant (P<0.001). Patients were separated into 3 groups combining LMR and 18F-FDG PET/CT: PET/CT CR patients with LMR≥3.00, PET/CT PD patients with LMR<3.00, and others. The Kaplan-Meier analysis revealed that there were significant differences in OS and PFS for each of the three groups (P<0.001). ROC curves showed that the area under the curve (AUC) of the combined testing of the two was 0.735, and the combined testing of the two was better compared to testing alone (PET/CT AUC=0.535, LMR AUC=0.567). This indicates that combining both PET/CT and LMR is a favorable prediction for DLBCL.

CONCLUSION

A decreased LMR at initial diagnosis suggests an unfavorable prognosis for DLBCL patients; For patients with DLBCL, combining 18F-FDG PET/CT and the LMR has a better predictive value.

Emerging Role of [18F]FLT PET/CT in Lymphoid Malignancies: A Review of Clinical Results

Fluorine-18 fluorodeoxyglucose ([18F]FDG) is nowadays the leading positron emission tomography (PET) tracer for routine clinical work-ups in hematological malignancies; however, it is limited by false positive findings. Notably, false positives can occur in inflammatory and infective cases or in necrotic tumors that are infiltrated by macrophages and other inflammatory cells. In this context, 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT) has been shown to be a promising imaging biomarker of hematological malignant cell proliferation. In this review, a total of 15 papers were reviewed to collect literature data regarding the clinical application of [18F]FLT PET/CT in hematological malignancies. This imaging modality seems to be a suitable tool for noninvasive assessment of tumor grading, also showing a correlation with Ki-67 immunostaining. Moreover, [18F]FLT PET/CT demonstrated high sensitivity in detecting aggressive lymphoma lesions, especially when applying a standardized uptake value (SUV) cutoff of 3. At baseline, the potential of [18F]FLT imaging as a predictive tool is demonstrated by the low tracer uptake in patients with a complete response. However, its use is limited in evaluating bone diseases due to its high physiological uptake in bone marrow. Interim [18F]FLT PET/CT (iFLT) has the potential to identify high-risk patients with greater precision than [18F]FDG PET/CT, optimizing risk-adapted therapy strategies. Moreover, [18F]FLT uptake showed a greater ability to differentiate tumor from inflammation compared to [18F]FDG, allowing the reduction of false-positive findings and making the first one a more selective tracer. Finally, FLT emerges as a superior independent predictor of PFS and OS compared to FDG and ensures a reliable early response assessment with greater accuracy and predictive value.

Comparative effectiveness of standard vs. AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging: a multi-institutional reader study evaluation

Background

Fluorine-18 fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) is widely used for staging high-grade lymphoma, with the time to evaluate such studies varying depending on the complexity of the case. Integrating artificial intelligence (AI) within the reporting workflow has the potential to improve quality and efficiency. The aims of the present study were to evaluate the influence of an integrated research prototype segmentation tool implemented within diagnostic PET/CT reading software on the speed and quality of reporting with variable levels of experience, and to assess the effect of the AI-assisted workflow on reader confidence and whether this tool influenced reporting behaviour.

Methods

Nine blinded reporters (three trainees, three junior consultants and three senior consultants) from three UK centres participated in a two-part reader study. A total of 15 lymphoma staging PET/CT scans were evaluated twice: first, using a standard PET/CT reporting workflow; then, after a 6-week gap, with AI assistance incorporating pre-segmentation of disease sites within the reading software. An even split of PET/CT segmentations with gold standard (GS), false-positive (FP) over-contour or false-negative (FN) under-contour were provided. The read duration was calculated using file logs, while the report quality was independently assessed by two radiologists with >15 years of experience. Confidence in AI assistance and identification of disease was assessed via online questionnaires for each case.

Results

There was a significant decrease in time between non-AI and AI-assisted reads (median 15.0 vs. 13.3 min, p < 0.001). Sub-analysis confirmed this was true for both junior (14.5 vs. 12.7 min, p = 0.03) and senior consultants (15.1 vs. 12.2 min, p = 0.03) but not for trainees (18.1 vs. 18.0 min, p = 0.2). There was no significant difference between report quality between reads. AI assistance provided a significant increase in confidence of disease identification (p < 0.001). This held true when splitting the data into FN, GS and FP. In 19/88 cases, participants did not identify either FP (31.8%) or FN (11.4%) segmentations. This was significantly greater for trainees (13/30, 43.3%) than for junior (3/28, 10.7%, p = 0.05) and senior consultants (3/30, 10.0%, p = 0.05).

Conclusions

The study findings indicate that an AI-assisted workflow achieves comparable performance to humans, demonstrating a marginal enhancement in reporting speed. Less experienced readers were more influenced by segmentation errors. An AI-assisted PET/CT reading workflow has the potential to increase reporting efficiency without adversely affecting quality, which could reduce costs and report turnaround times. These preliminary findings need to be confirmed in larger studies.

68Ga-FAPI-04 Positron Emission Tomography Distinguishes Malignancy From 18F-FDG-Avid Colorectal Lesions

PURPOSE

Lesions with a high uptake of 18F-fluorodeoxyglucose (18F-FDG) on positron emission tomography-computed tomography (PET-CT) can be benign and malignant. New radiotracers, such as the gallium 68 (68Ga)-labeled fibroblast activation protein inhibitor 4 (FAPI-04), could be used to diagnose colorectal carcinoma. This study aimed to evaluate the efficacy of 68Ga-FAPI-04 PET in differentiating benign from malignant 18F-FDG-avid colorectal lesions.

METHODS AND MATERIALS

An azoxymethane/dextran sodium sulfate (AOM/DSS)-induced rat colorectal tumor model was developed. Double-tracer 68Ga-FAPI-04 and 18F-FDG PET-CT were applied in the rat model and 22 patients. The PET-CT data were analyzed with enteroscopy, histopathologic observations, immunohistochemistry (IHC) staining, and radioautography results. One hundred seventy-two patients with pathologically confirmed colorectal lesions were enrolled in FAP IHC staining.

RESULTS

We found that 68Ga-FAPI-04 PET-CT imaging accurately distinguished the malignant from benign inflammatory lesions in an AOM/DSS-induced rat colorectal tumor model. Of 22 patients with gastric cancer but without colorectal carcinoma, 8 had 18F-FDG uptake in the colorectum, but 68Ga-FAPI-04 PET was negative in these sites. An inflammatory lesion or adenoma did not interfere with 68Ga-FAPI-04 PET imaging. Among the 18F-FDG-avid colorectal lesions, 80 of 94 pathologically malignant lesions (85.1%) were FAP-positive, and only 16 of the 78 premalignant or benign lesions (20.5%) had a weak 68Ga-FAPI-04 uptake.

CONCLUSIONS

68Ga-FAPI-04 PET-CT could be used to distinguish between benign and malignant 18F-FDG-avid colorectal lesions.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

 Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

 The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

 AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

  · Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures

BACKGROUND

There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

METHODS

After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism.

RESULTS

The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism.

CONCLUSION

This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures

Background

There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

Methods

After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism.

Results

The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a “Walktrap” algorithm, the community map indicated that the “apoptosis, metabolism, chemotherapy” (Centrality = 12, Density = 6), “lymphoma, pet/ct, prognosis” (Centrality = 11, Density = 1), and “genotoxicity, mutagenicity” (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism.

Conclusion

This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

A proper protocol for routine 18F-FDG uEXPLORER total-body PET/CT scans

BACKGROUND

Conventional clinical PET scanners typically have an axial field of view (AFOV) of 15-30 cm, resulting in limited coverage and relatively low photon detection efficiency. Taking advantage of the development of long-axial PET/CT, the uEXPLORER PET/CT scanner with an axial coverage of 194 cm increases the effective count rate by approximately 40 times compared to that of conventional PET scanners. Ordered subset expectation maximization (OSEM) is the most widely used iterative algorithm in PET. The major drawback of OSEM is that the iteration process must be stopped before convergence to avoid image degradation due to excessive noise. A new Bayesian penalized-likelihood iterative PET reconstruction, named HYPER iterative, was developed and is now available on the uEXPLORER total-body PET/CT, which incorporates a noise control component by using a penalty function in each iteration and finds the maximum likelihood solution through repeated iterations. To date, its impact on lesion visibility in patients with a full injected dose or half injected dose is unclear. The goal of this study was to determine a proper protocol for routine 18F-FDG uEXPLORER total-body PET/CT scans.

RESULTS

The uEXPLORER total-body PET/CT images reconstructed using both OSEM and HYPER iterative algorithms of 20 tumour patients were retrospectively reviewed. The quality of the 5 min PET image was excellent (score 5) for all of the dose and reconstruction methods. Using the HYPER iterative method, the PET images reached excellent quality at 1 min with full-dose PET and at 2 min with half-dose PET. The PET image reached a similar excellent quality at 2 min with a full dose and at 3 min with a half dose using OSEM. The noise in the OSEM reconstruction was higher than that in the HYPER iterative. Compared to OSEM, the HYPER iterative had a slightly higher SUVmax and TBR of the lesions for large positive lesions (≥ 2 cm) (SUVmax: up to 9.03% higher in full dose and up to 12.52% higher in half dose; TBR: up to 8.69% higher in full dose and up to 23.39% higher in half dose). For small positive lesions (≤ 10 mm), the HYPER iterative had an obviously higher SUVmax and TBR of the lesions (SUVmax: up to 45.21% higher in full dose and up to 74.96% higher in half dose; TBR: up to 44.91% higher in full dose and up to 93.73% higher in half dose).

CONCLUSIONS

A 1 min scan with a full dose and a 2 min scan with a half dose are optimal for clinical diagnosis using the HYPER iterative and 2 min and 3 min for OSEM. For quantification of the small lesions, HYPER iterative reconstruction is preferred.

Differential diagnosis of lymphoma with 18F-FDG PET/CT in patients with fever of unknown origin accompanied by lymphadenopathy

PURPOSE

To investigate the value of 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the differential diagnosis of lymphoma in patients with fever of unknown origin (FUO) accompanied by lymphadenopathy and to develop a simple scoring system to distinguish lymphoma from other etiologies.

METHODS

A prospective study was conducted on patients with classic FUO accompanied by lymphadenopathy. After standard diagnostic procedures, including PET/CT scan and lymph-node biopsy, 163 patients were enrolled and divided into lymphoma and benign groups according to the etiology. The diagnostic utility of PET/CT imaging was evaluated, and beneficial parameters that could improve diagnostic effectiveness were identified.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PET/CT in diagnosing lymphoma in patients with FUO accompanied by lymphadenopathy were 81.0, 47.6, 59.3, and 72.7%, respectively. The lymphoma prediction model combining high SUVmax of the "hottest" lesion, high SUVmax of the retroperitoneal lymph nodes, old age, low platelet count, and low ESR had an area under the curve of 0.93 (0.89-0.97), a sensitivity of 84.8%, a specificity of 92.9%, a PPV of 91.8%, and an NPV of 86.7%. There was a lower probability of lymphoma for patients with a score < 4 points.

CONCLUSIONS

PET/CT scans show moderate sensitivity and low specificity in diagnosing lymphoma in patients with FUO accompanied by lymphadenopathy. The scoring system based on PET/CT and clinical parameters performs well in differentiating lymphoma and benign causes and can be used as a reliable noninvasive tool.

REGISTRATION NUMBER

This study on FUO was registered on http://www.

CLINICALTRIALS

gov on January 14, 2014, with registration number NCT02035670.

The Utility of Interim Positron Emission Tomography Imaging to Inform Adaptive Radiotherapy for Head and Neck Squamous Cell Carcinoma

ABSTRACT

In this article, as part of this special issue on biomarkers of early response, we review the current evidence to support the use of positron emission tomography (PET) imaging during chemoradiation therapy to inform biologically adaptive radiotherapy for head and neck squamous cell carcinoma. We review literature covering this topic spanning nearly 3 decades, including the use of various radiotracers and discoveries of novel predictive PET biomarkers. Through understanding how observational trials have informed current interventional clinical trials, we hope that this review will encourage researchers and clinicians to incorporate PET response criteria in new trial designs to advance biologically optimized radiotherapy.

Correlation of mean apparent diffusion coefficient (ADC) and maximal standard uptake value (SUVmax) evaluated by diffusion-weighted MRI and 18F-FDG-PET/CT in children with Hodgkin lymphoma: a feasibility study

BACKGROUND

The objective was to analyse if magnetic resonance imaging (MRI) can act as a non-radiation exposure surrogate for (18)F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in children with histologically confirmed Hodgkin lymphoma (HL) before treatment. This was done by analysing a potential correlation between apparent diffusion coefficient (ADC) in MRI and the maximum standardized uptake value (SUVmax) in FDG-PET/CT.

PATIENTS AND METHODS

Seventeen patients (six female, eleven male, median age: 16 years, range: 12-20 years) with histologically confirmed HL were retrospectively analysed. The patients underwent both MRI and (18)F-FDG PET/CT before the start of treatment. (18)F-FDG PET/CT data and correlating ADC maps in MRI were collected. For each HL-lesion two readers independently evaluated the SUVmax and correlating meanADC.

RESULTS

The seventeen patients had a total of 72 evaluable lesions of HL and there was no significant difference in the number of lesions between male and female patients (median male: 15, range: 12-19 years, median female: 17 range: 12-18 years, p = 0.021). The mean duration between MRI and PET/CT was 5.9 ± 5.3 days. The inter-reader agreement as assessed by the intraclass correlation coefficient (ICC) was excellent (ICC = 0.98, 95% CI: 0.97-0.99). The correlated SUVmax and meanADC of all 17 patients (ROIs n = 72) showed a strong negative correlation of -0.75 (95% CI: -0.84, - -0.63, p = 0.001). Analysis revealed a difference in the correlations of the examination fields. The correlated SUVmax and meanADC showed a strong correlation at neck and thoracal examinations (neck: -0.83, 95% CI: -0.93, - -0.63, p < 0.0001, thoracal: -0.82, 95% CI: -0.91, - -0.64, p < 0.0001) and a fair correlation at abdominal examinations of -0.62 (95% CI: -0.83, - -0.28, p = 0.001).

CONCLUSIONS

SUVmax and meanADC showed a strong negative correlation in paediatric HL lesions. The assessment seemed robust according to inter-reader agreements. Our results suggest that ADC maps and meanADC have the potential to replace PET/CT in the analysis of disease activity in paediatric Hodgkin lymphoma patients. This may help reduce the number of PET/CT examinations and decrease radiation exposure to children.

PET/CT in Non-Hodgkin Lymphoma: An Update

Non-Hodgkin lymphomas represents a heterogeneous group of lymphoproliferative disorders characterized by different clinical courses, varying from indolent to highly aggressive. ¹⁸F-FDG-PET/CT is the current state-of-the-art diagnostic imaging, for the staging, restaging and evaluation of response to treatment in lymphomas with avidity for ¹⁸F-FDG, despite it is not routinely recommended for surveillance. PET-based response criteria (using five-point Deauville Score) are nowadays uniformly applied in FDG-avid lymphomas. In this review, a comprehensive overview of the role of ¹⁸F-FDG-PET in Non-Hodgkin lymphomas is provided, at each relevant point of patient management, particularly focusing on recent advances on diffuse large B-cell lymphoma and follicular lymphoma, with brief updates also on other histotypes (such as marginal zone, mantle cell, primary mediastinal- B cell lymphoma and T cell lymphoma). PET-derived semiquantitative factors useful for patient stratification and prognostication and emerging radiomics research are also presented.

Survival Prediction Using Transformer-Based Categorical Feature Representation in the Treatment of Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a common and aggressive subtype of lymphoma, and accurate survival prediction is crucial for treatment decisions. This study aims to develop a robust survival prediction strategy to integrate various risk factors effectively, including clinical risk factors and Deauville scores in positron-emission tomography/computed tomography at different treatment stages using a deep-learning-based approach. We conduct a multi-institutional study on 604 DLBCL patients' clinical data and validate the model on 220 patients from an independent institution. We propose a survival prediction model using transformer architecture and a categorical-feature-embedding technique that can handle high-dimensional and categorical data. Comparison with deep-learning survival models such as DeepSurv, CoxTime, and CoxCC based on the concordance index (C-index) and the mean absolute error (MAE) demonstrates that the categorical features obtained using transformers improved the MAE and the C-index. The proposed model outperforms the best-performing existing method by approximately 185 days in terms of the MAE for survival time estimation on the testing set. Using the Deauville score obtained during treatment resulted in a 0.02 improvement in the C-index and a 53.71-day improvement in the MAE, highlighting its prognostic importance. Our deep-learning model could improve survival prediction accuracy and treatment personalization for DLBCL patients.

A Phase I Dose-escalation Study of AZD3965, an Oral Monocarboxylate Transporter 1 Inhibitor, in Patients with Advanced Cancer

PURPOSE

Inhibition of monocarboxylate transporter (MCT) 1-mediated lactate transport may have cytostatic and/or cytotoxic effects on tumor cells. We report results from the dose-escalation part of a first-in-human trial of AZD3965, a first-in-class MCT1 inhibitor, in advanced cancer.

PATIENTS AND METHODS

This multicentre, phase I, dose-escalation and dose-expansion trial enrolled patients with advanced solid tumors or lymphoma and no standard therapy options. Exclusion criteria included history of retinal and/or cardiac disease, due to MCT1 expression in the eye and heart. Patients received daily oral AZD3965 according to a 3+3 then rolling six design. Primary objectives were to assess safety and determine the MTD and/or recommended phase II dose (RP2D). Secondary objectives for dose escalation included measurement of pharmacokinetic and pharmacodynamic activity. Exploratory biomarkers included tumor expression of MCT1 and MCT4, functional imaging of biological impact, and metabolomics.

RESULTS

During dose escalation, 40 patients received AZD3965 at 5-30 mg once daily or 10 or 15 mg twice daily. Treatment-emergent adverse events were primarily grade 1 and/or 2, most commonly electroretinogram changes (retinopathy), fatigue, anorexia, and constipation. Seven patients receiving ≥20 mg daily experienced dose-limiting toxicities (DLT): grade 3 cardiac troponin rise (n = 1), asymptomatic ocular DLTs (n = 5), and grade 3 acidosis (n = 1). Plasma pharmacokinetics demonstrated attainment of target concentrations; pharmacodynamic measurements indicated on-target activity.

CONCLUSIONS

AZD3965 is tolerated at doses that produce target engagement. DLTs were on-target and primarily dose-dependent, asymptomatic, reversible ocular changes. An RP2D of 10 mg twice daily was established for use in dose expansion in cancers that generally express high MCT1/low MCT4).

Anthracycline cardiotoxicity: current methods of diagnosis and possible role of 18F-FDG PET/CT as a new biomarker

Despite advances in chemotherapy, the drugs used in cancer treatment remain rather harmful to the cardiovascular system, causing structural and functional cardiotoxic changes. Positron-emission tomography associated with computed tomography (PET/CT) has emerged like a promising technique in the early diagnosis of these adverse drug effects as the myocardial tissue uptake of fluorodeoxyglucose labeled with fluorine-18 (¹⁸F-FDG), a glucose analog, is increased after their use. Among these drugs, anthracyclines are the most frequently associated with cardiotoxicity because they promote heart damage through DNA breaks, and induction of an oxidative, proinflammatory, and toxic environment. This review aimed to present the scientific evidence available so far regarding the use of ¹⁸F-FDG PET/CT as an early biomarker of anthracycline-related cardiotoxicity. Thus, it discusses the physiological basis for its uptake, hypotheses to justify its increase in the myocardium affected by anthracyclines, importance of ¹⁸F-FDG PET/CT findings for cardio-oncology, and primary challenges of incorporating this technique in standard clinical oncology practice.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

· Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

CITATION FORMAT

· Feuerecker B, Heimer M, Geyer T et al. Artificial Intelligence in Oncological Hybrid Imaging. Fortschr Röntgenstr 2023; 195: 105 - 114.

A glycolysis-related gene signatures in diffuse large B-Cell lymphoma predicts prognosis and tumor immune microenvironment

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which that highly aggressive and heterogeneous. Glycolysis has been implicated in the regulation of tumor microenvironment (TME) and development. In this study, we aimed to establish a glycolysis-related prognostic model for the risk stratification, prognosis prediction, and immune landscape evaluation in patients with DLBCL. Methods: Three independent datasets GSE181063, GSE10846, and GSE53786 containing gene expression profiles and clinical data were downloaded from the Gene Expression Omnibus (GEO) database. The glycolysis-related prognostic model was developed with Cox and Least Absolute Shrinkage and Selector Operation (LASSO) regression and validated. A nomogram integrating clinical factors and glycolytic risk scores was constructed. The composition of the TME was analyzed with the ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA). Results: A glycolytic risk model containing eight genes was developed. The area under the receiver operating characteristic (ROC) curve (AUC) for the 1-, 3-, and 5-year was 0.718, 0.695, and 0.688, respectively. Patients in the high-risk group had significantly lower immune scores, elevated tumor purity, and poorer survival compared with those in the low-risk group. The nomogram constructed based on glycolytic risk score, age, Eastern Cooperative Oncology Group performance status (ECOG-PS), use of rituximab, and cell of origin (COO) displayed better prediction performance compared with the International Prognostic Index (IPI) in DLBCL. The glycolytic risk score was negatively correlated with the infiltration level of activated CD8 T cells, activated dendritic cells, natural killer cells, and macrophages and immune checkpoint molecules including PD-L2, CTLA4, TIM-3, TIGIT, and B7-H3. Conclusion: These results suggested that the glycolytic risk model could accurately and stably predict the prognosis of patients with DLBCL and might unearth the possible explanation for the glycolysis-related poor prognosis.

Development and validation of a nomogram to predict overall survival and cancer-specific survival in patients with primary intracranial malignant lymphoma: A Retrospective study based on the SEER database

Introduction

Primary intracranial malignant lymphoma (PIML) is a rare form of lymphoma that most often occurs in the brain and has an extremely low 5-year survival rate. Although chemotherapy and radiotherapy are widely used in the clinical management of PIML, the choice of treatment regimen and the actual circumstances of patients remain challenges when assessing survival rates in different patients.

Methods

Considering this, we obtained clinical treatment and survival information from the Surveillance, Epidemiology, and End Results database (SEER) on patients with lymphoma, the primary site of which was the brain, and performed statistical analyses of the demographic characteristics. Survival analyses were performed using the Kaplan-Meier method, and univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors.

Result

We identified age, pathology, the Ann Arbor stage, and treatment as the risk factors affecting patient prognosis. The areas under the curve (AUCs) for overall survival at 1, 3, and 5 years were 0.8, 0.818, and 0.81, respectively. The AUCs for cancer-specific survival at 1, 3, and 5 years were 0.8, 0.79, and 0.79. The prediction ability in the development and verification cohorts was in good agreement with the actual values, while we plotted the clinical decision curves for the model, suggesting that the nomogram can provide benefits for clinical decision-making.

Conclusion

Our model provides a prognostic guide for patients with PIML and a reliable basis for clinicians.

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.

Can positron emission tomography–computed tomography-based three target lesions' total lesion glycolysis predict therapeutic response in Hodgkin Lymphoma?

Background

Universally maximum standardized uptake value (SUVmax) and lactate dehydrogenase (LDH) are used as tools for response assessment in Hodgkin Lymphoma (HL) patients. Our objectives are to evaluate the predictive potential and response assessment of total lesion glycolysis (TLG) and metabolic tumor volume (MTV)—maximum three target lesions—as another alternatives and to investigate the correlation between TLG and MTV with LDH.

Results

Both initial SUVmax and TLG were significantly associated with early patient response (p value 0.03, 0.047, respectively). An optimal threshold for SUVmax and TLG less than or equal 19.52, and 158.6, respectively, correlated with better therapeutic response. Initial LDH was moderately correlated with initial values of TLG (rs = 0.4, p value 0.01), MTV (rs = 0.44, p value 0.01) and SUVmax (rs = 0.42, p value 0.01).

Conclusion

TLG in correlation with LDH can be significant prognostic factors of therapeutic response in HL. They can be used for the identification of a subset of HL patients with a better outcome.

PET-CT in Clinical Adult Oncology: I. Hematologic Malignancies

PET-CT is an advanced imaging modality with many oncologic applications, including staging, assessment of response to therapy, restaging and evaluation of suspected recurrence. The goal of this 6-part series of review articles is to provide practical information to providers and imaging professionals regarding the best use of PET-CT for the more common adult malignancies. In the first article of this series, hematologic malignancies are addressed. The classification of these malignancies will be outlined, with the disclaimer that the classification of lymphomas is constantly evolving. Critical applications, potential pitfalls, and nuances of PET-CT imaging in hematologic malignancies and imaging features of the major categories of these tumors are addressed. Issues of clinical importance that must be reported by the imaging professionals are outlined. The focus of this article is on [¹⁸F] fluorodeoxyglucose (FDG), rather that research tracers or those requiring a local cyclotron. This information will serve as a resource for the appropriate role and limitations of PET-CT in the clinical management of patients with hematological malignancy for health care professionals caring for adult patients with hematologic malignancies. It also serves as a practical guide for imaging providers, including radiologists, nuclear medicine physicians and their trainees.

Multimodality Imaging of Benign Primary Cardiac Tumor

Primary cardiac tumors (PCTs) are rare, with benign PCTs being relatively common in approximately 75% of all PCTs. Benign PCTs are usually asymptomatic, and they are found incidentally by imaging. Even if patients present with symptoms, they are usually nonspecific. Before the application of imaging modalities to the heart, our understanding of these tumors is limited to case reports and autopsy studies. The advent and improvement of various imaging technologies have enabled the non-invasive evaluation of benign PCTs. Although echocardiography is the most commonly used imaging examination, it is not the best method to describe the histological characteristics of tumors. At present, cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) are often used to assess benign PCTs providing detailed information on anatomical and tissue features. In fact, each imaging modality has its own advantages and disadvantages, multimodality imaging uses two or more imaging types to provide valuable complementary information. With the widespread use of multimodality imaging, these techniques play an indispensable role in the management of patients with benign PCTs by providing useful diagnostic and prognostic information to guide treatment. This article reviews the multimodality imaging characterizations of common benign PCTs.

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.

Disease severity and status in Stevens–Johnson syndrome and toxic epidermal necrolysis: Key knowledge gaps and research needs

Stevens–Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) are on a spectrum of cutaneous drug reactions characterized by pan-epidermal necrosis with SJS affecting < 10% of body surface area (BSA), TEN > 30%, and SJS/TEN overlap between 10 and 30%. Severity-of-illness score for toxic epidermal necrolysis (SCORTEN) is a validated tool to predict mortality rates based on age, heart rate, BSA, malignancy and serum urea, bicarbonate, and glucose. Despite improved understanding, SJS/TEN mortality remains constant and therapeutic interventions are not universally accepted for a number of reasons, including rarity of SJS/TEN; inconsistent definition of cases, disease severity, and endpoints in studies; low efficacy of interventions; and variations in treatment protocols. Apart from mortality, none of the other endpoints used to evaluate interventions, including duration of hospitalization, is sufficiently standardized to be reproducible across cases and treatment centers. Some of the gaps in SJS/TEN research can be narrowed through international collaboration to harmonize research endpoints. A case is made for an urgent international collaborative effort to develop consensus on definitions of endpoints such as disease status, progression, cessation, and complete re-epithelialization in interventional studies. The deficiencies of using BSA as the sole determinant of SJS/TEN severity, excluding internal organ involvement and extension of skin necrosis beyond the epidermis, are discussed and the role these factors play on time to healing and mortality beyond the acute stage is highlighted. The potential role of artificial intelligence, biomarkers, and PET/CT scan with radiolabeled glucose as markers of disease status, activity, and therapeutic response is also discussed.

Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma

Objectives

Relapse occurs in ~20% of patients with classical Hodgkin lymphoma (cHL) despite treatment adaption based on 2-deoxy-2-[¹⁸F]fluoro-d-glucose positron emission tomography/computed tomography response. The objective was to evaluate pre-treatment FDG PET/CT–derived machine learning (ML) models for predicting outcome in patients with cHL.

Methods

All cHL patients undergoing pre-treatment PET/CT at our institution between 2008 and 2018 were retrospectively identified. A 1.5 × mean liver standardised uptake value (SUV) and a fixed 4.0 SUV threshold were used to segment PET/CT data. Feature extraction was performed using PyRadiomics with ComBat harmonisation. Training (80%) and test (20%) cohorts stratified around 2-year event-free survival (EFS), age, sex, ethnicity and disease stage were defined. Seven ML models were trained and hyperparameters tuned using stratified 5-fold cross-validation. Area under the curve (AUC) from receiver operator characteristic analysis was used to assess performance.

Results

A total of 289 patients (153 males), median age 36 (range 16–88 years), were included. There was no significant difference between training (n = 231) and test cohorts (n = 58) (p value > 0.05). A ridge regression model using a 1.5 × mean liver SUV segmentation had the highest performance, with mean training, validation and test AUCs of 0.82 ± 0.002, 0.79 ± 0.01 and 0.81 ± 0.12. However, there was no significant difference between a logistic model derived from metabolic tumour volume and clinical features or the highest performing radiomic model.

Conclusions

Outcome prediction using pre-treatment FDG PET/CT–derived ML models is feasible in cHL patients. Further work is needed to determine optimum predictive thresholds for clinical use.

Key points

• A fixed threshold segmentation method led to more robust radiomic features.

• A radiomic-based model for predicting 2-year event-free survival in classical Hodgkin lymphoma patients is feasible.

• A predictive model based on ridge regression was the best performing model on our dataset.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-09039-0.

Use of 18F-FDG-PET/CT in differential diagnosis of primary central nervous system lymphoma and high-grade gliomas: A meta-analysis

Background

Primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) appear similar under imaging. However, since the two tumors vary in their treatment methods, their differential diagnosis is crucial. The use of 18F-fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG-PET/CT) imaging to effectively distinguish between the two tumors is not clear; therefore, a meta-analysis was carried out to determine its effectiveness.

Materials and methods

The databases PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, China Science, and Technology Journal Database (CQVIP) were exhaustively searched using stringent inclusion and exclusion criteria to select high-quality literature. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) was used for the qualitative assessment of the included literature. The bivariate effect model was used to combine statistics such as sensitivity (SEN) and specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) [95% confidence intervals (CI)], plot summary receiver operating characteristic (SROC) curve, and calculate the area under the curve (AUC) value. Sensitivity analysis was used to evaluate the stability of the results, and Deek's test was used to assess publication bias. Meta-regression and subgroup analysis was used to determine the sources of heterogeneity.

Results

A total of nine studies were included in this study. For differential diagnosis of PCNSL and HGG, the combined SEN was 0.91 (95% CI: 0.80–0.96; I² = 46.73%), combined SPE was 0.88 (95% CI: 0.82–0.93; I² = 56.30%), the combined PLR was 7.83 (95% CI: 4.96–12.37; I² = 15.57%), combined NLR was 0.10 (95% CI: 0.05–0.23; I² = 31.99%), combined DOR was 77.36 (95% CI: 32.74–182.77; I² = 70.70%). The AUC of SROC was 0.95 (95% CI: 0.93–0.97). No publication bias was found and the sample size and different parameters were the primary reason for heterogeneity.

Conclusion

The 18F-FDG-PET/CT imaging technique has a high diagnostic accuracy in the differential diagnosis of PNCSL and HGG. Patients suspected to have the above two tumors are suggested to be examined by 18F-FDG-PET / CT to help in the clinical distinction and further treatment modalities.