Baseline SUVmax of 18F-FDG PET-CT indicates prognosis of extranodal natural killer/T-cell lymphoma

Differentiation of cancer of unknown primary and lymphoma in head and neck metastatic poorly differentiated cancer using 18 F-FDG PET/CT tumor metabolic heterogeneity index

OBJECTIVE

To explore the value of 18 F-FDG PET/CT tumor metabolic heterogeneity index (HI) and establish and validate a nomogram model for distinguishing head and neck cancer of unknown primary (HNCUP) from lymphoma with head and neck metastatic poorly differentiated cancer.

METHODS

This retrospective analysis was conducted on 1242 patients with cervical metastatic poorly differentiated cancer. 108 patients, who were clinically and pathologically confirmed as HNCUP or lymphoma, were finally enrolled. Two independent sample t-tests and χ 2 test were used to compare the clinical and imaging features. Binary logistic regression was used to screen for independent predictive factors.

RESULTS

Among the 108 patients), 65 patients were diagnosed with HNCUP and 43 were lymphoma. Gender ( P  = 0.001), SUV max ( P  < 0.001), SUV mean ( P  < 0.001), TLG ( P  = 0.012), and HI ( P  < 0.001) had statistical significance in distinguishing HNCUP and lymphoma. Female ( OR  = 4.546, P  = 0.003) and patients with HI ≥ 2.37 ( OR  = 3.461, P  = 0.047) were more likely to be diagnosed as lymphoma.

CONCLUSION

For patients with cervical metastatic poorly differentiated cancer, gender and HI were independent predictors of pathological type. For such patients, clinical attention should be paid to avoid misdiagnosing lymphoma as HNCUP, which may delay treatment.

Preoperative 18F-FDG PET/CT in Patients with Presumed Localized Colon Cancer: A Prospective Study with Long-Term Follow-Up

We analyzed whether preoperative 18F-FDG PET/CT adds to conventional primary staging in patients with presumed non-metastatic colonic cancer (CC). The prognostic role of 18F-FDG uptake in the primary tumor was evaluated after a mean follow-up of 15 years. Patients with a new diagnosis of presumed localized CC were prospectively enrolled and underwent presurgical 18F-FDG PET/CT. For each colon lesion, SUVmax, SUVpeak, TLG, and MTV were assessed and tested as prognostic factors. Forty-eight patients were included. Post-surgery pathology identified a total of 103 colon lesions, including 58 invasive adenocarcinomas, 4 in situ adenocarcinomas, 3 adenomas with high-grade dysplasia, and 38 adenomas with low-grade dysplasia. Per lesion sensitivity, specificity, positive (PPVs) and negative predictive values (NPVs) for colonic primary tumor detection were 78%, 97%, 98%, and 73% for conventional workup, and 94%, 87%, 92%, and 89% for 18F-FDG PET/CT. Only sensitivity was significantly different between 18F-FDG PET/CT and conventional workup. PET detected an additional ten pathological colonic lesions in seven patients. SUVmax, SUVpeak, and TLG showed significant differences between invasive adenocarcinomas, in situ adenocarcinomas, and high-grade dysplasia compared to low-grade dysplasia. There was a statistically significant difference between pT1-pT2 and pT3-pT4 adenocarcinomas. On patient-based analysis, sensitivity, specificity, PPV, and NPV for nodal staging were 22%, 84%, 44%, and 65% for CECT, and 33%, 90%, 67%, and 70% for 18F-FDG PET/CT, without a statistically significant difference. PET/CT also identified unknown metastatic spread and one synchronous lung cancer in four patients. Overall, 18F-FDG PETCT had an additional diagnostic value in 11 out of 48 patients (23%). 18F-FDG uptake of the primary tumor did not predict nodal or distant metastases. The difference in disease-free survival categorized by median SUVmax, SUVpeak, TLG, and MTV was not significant. Finally, preoperative 18F-FDG PET/CT is valuable in detecting potential colon lesions not visualized by conventional workups, especially in cases of incomplete colonoscopy. It effectively highlights distant metastases but exhibits limitations for N staging. Mainly due to the relatively small sample size, the quantitative analysis of 18F-FDG uptake in the primary tumor did not reveal any association with recurrence or disease-free survival, adding no significant prognostic information.

Radioimmunotherapy with 131 I-rituximab for patients with relapsed or refractory follicular or mantle cell lymphoma

AIM

This study aimed to evaluate the safety and efficacy of 131 I-rituximab in patients with relapsed or refractory follicular or mantle cell lymphoma.

METHODS

Twenty-four patients with relapsed or refractory follicular or mantle cell lymphoma were administered unlabeled rituximab (70 mg) immediately before receiving a therapeutic dose of 131 I-rituximab. Contrast-enhanced 18F-fluorodeoxyglucose positron emission tomography/computed tomography was used a month later to assess tumor response.

RESULTS

This study enrolled 24 patients between June 2012 and 2022. Depending on how they responded to radioimmunotherapy (RIT), 131 I-rituximab was administered one to five times. Of the 24 patients, 9 achieved complete response after RIT and 8 achieved partial response. The median progression-free and overall survival was 5.9 and 37.9 months, respectively. During the follow-up period of 64.2 months, three patients were diagnosed with a secondary malignancy. Among treatment-related adverse events, hematologic toxicities were common, and grade 3-4 thrombocytopenia and neutropenia were reported in 66.6% of cases.

CONCLUSION

131 I-rituximab has an effective and favorable safety profile in patients with relapsed or refractory follicular lymphoma and mantle cell lymphoma. This suggests that RIT may also be considered a treatment option for patients with relapsed or refractory follicular lymphoma and mantle cell lymphoma.

Diagnostic and prognostic value of pretreatment PET/CT in extranodal natural killer/T-cell lymphoma: a retrospective multicenter study

PURPOSE

The objective of this research was to assess the utility of positron emission tomography combined with computed tomography (PET/CT) to detect bone marrow invasion (BMI) and the predictive value of PET/CT in extranodal natural killer/T-cell lymphoma (ENKTL) patients.

PATIENTS AND METHODS

This multicentre study enrolled ENKTL patients who underwent pretherapy PET/CT and bone marrow biopsy (BMB). The specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) of PET/CT and BMB for BMI were evaluated. Multivariate analysis was used to identify predictive parameters for constructing a nomogram.

RESULTS

Seven hundred and forty-eight patients were identified from four hospitals, with eighty (10.7%) having focal skeletal lesions on PET/CT and fifty (6.7%) having positive BMB. When BMB is considered as the gold standard, the specificity, sensitivity, PPV, and NPV of PET/CT for diagnosing BMI were found to be 93.8%, 74.0%, 46.3%, and 98.1%, respectively. PET/CT-positive individuals showed significantly worse OS than PET/CT-negative patients in the subgroup of BMB-negative cases. The nomogram model created according to the significant risk factors from multivariate analysis performed well in predicting survival probability.

CONCLUSION

PET/CT offers a superior degree of precision for determining BMI in ENKTL. A nomogram model including the parameters of PET/CT can predict survival probability and may help in applying appropriate personalized therapy.

Baseline 18F-FDG PET/CT Radiomics in Classical Hodgkin's Lymphoma: The Predictive Role of the Largest and the Hottest Lesions

This study investigated the predictive role of baseline 18F-FDG PET/CT (bPET/CT) radiomics from two distinct target lesions in patients with classical Hodgkin's lymphoma (cHL). cHL patients examined with bPET/CT and interim PET/CT between 2010 and 2019 were retrospectively included. Two bPET/CT target lesions were selected for radiomic feature extraction: Lesion_A, with the largest axial diameter, and Lesion_B, with the highest SUVmax. Deauville score at interim PET/CT (DS) and 24-month progression-free-survival (PFS) were recorded. Mann-Whitney test identified the most promising image features (p < 0.05) from both lesions with regards to DS and PFS; all possible radiomic bivariate models were then built through a logistic regression analysis and trained/tested with a cross-fold validation test. The best bivariate models were selected based on their mean area under curve (mAUC). A total of 227 cHL patients were included. The best models for DS prediction had 0.78 ± 0.05 maximum mAUC, with a predominant contribution of Lesion_A features to the combinations. The best models for 24-month PFS prediction reached 0.74 ± 0.12 mAUC and mainly depended on Lesion_B features. bFDG-PET/CT radiomic features from the largest and hottest lesions in patients with cHL may provide relevant information in terms of early response-to-treatment and prognosis, thus representing an earlier and stronger decision-making support for therapeutic strategies. External validations of the proposed model are planned.

Enhancement of 18F-Fluorodeoxyglucose PET Image Quality by Deep-Learning-Based Image Reconstruction Using Advanced Intelligent Clear-IQ Engine in Semiconductor-Based PET/CT Scanners

Deep learning (DL) image quality improvement has been studied for application to ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). It is unclear, however, whether DL can increase the quality of images obtained with semiconductor-based PET/CT scanners. This study aimed to compare the quality of semiconductor-based PET/CT scanner images obtained by DL-based technology and conventional OSEM image with Gaussian postfilter. For DL-based data processing implementation, we used Advanced Intelligent Clear-IQ Engine (AiCE, Canon Medical Systems, Tochigi, Japan) and for OSEM images, Gaussian postfilter of 3 mm FWHM is used. Thirty patients who underwent semiconductor-based PET/CT scanner imaging between May 6, 2021, and May 19, 2021, were enrolled. We compared AiCE images and OSEM images and scored them for delineation, image noise, and overall image quality. We also measured standardized uptake values (SUVs) in tumors and healthy tissues and compared them between AiCE and OSEM. AiCE images scored significantly higher than OSEM images for delineation, image noise, and overall image quality. The Fleiss kappa value for the interobserver agreement was 0.57. Among the 21 SUV measurements in healthy organs, 11 (52.4%) measurements were significantly different between AiCE and OSEM images. More pathological lesions were detected in AiCE images as compared with OSEM images, with AiCE images showing higher SUVs for pathological lesions than OSEM images. AiCE can improve the quality of images acquired with semiconductor-based PET/CT scanners, including the noise level, contrast, and tumor detection capability.

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.

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.