The reproducibility of MTV and TLG of soft tissue tumors calculated by FDG-PET: Comparison between the lower limit by the fixed value SUV 2.5 and that value by 30% of SUVmax

Predictability of combining Technetium-99m-galactosyl human serum albumin single-photon emission computed tomography/computed tomography and indocyanine green clearance test for posthepatectomy liver failure

PURPOSE

To evaluate the predictive ability of combining Technetium-99m-galactosyl human serum albumin (99mTc‑GSA) single-photon emission computed tomography (SPECT)/computed tomography (CT) volume and plasma clearance rate of indocyanine green (ICGK) for posthepatectomy liver failure (PHLF).

MATERIALS AND METHODS

Fifty patients who underwent 99mTc-GSA scintigraphy as a preoperative examination for segmentectomy or more from July 2021 to June 2023 were evaluated prospectively. Patients were divided into two groups according to the presence or absence of posthepatectomy liver failure (PHLF). Total functional liver volume (t-FLV) and remnant FLV (r-FLV) were measured from 99mTc-GSA SPECT/CT image. Future liver remnant ICGK (ICGK-F) was calculated by ICGK and remnant liver volume from CT. Area under the curve (AUC) of ICGK-F, r-FLV, r-FLV/t-FLV, ICGK × r-FLV, ICGK × r-FLV/t-FLV was calculated to evaluate predictive ability of each parameter for PHLF.

RESULTS

PHLF was occurred in 7 patients. AUC of ICGK × r-FLV was significantly higher than that of ICGK-F (0.99; 95% confidence interval [CI]: 0.96-1 vs 0.82; 95%CI: 0.64-0.96; p = 0.036). There was no significant difference between the AUC of r-FLV, r-FLV/t-FLV, ICGK × r-FLV/t-FLV and that of ICGK-F, respectively.

CONCLUSION

The combination of 99mTc‑GSA SPECT/CT volume and ICGK can predict PHLF more accurately than ICGK-F.

Generative AI and large language models in nuclear medicine: current status and future prospects

This review explores the potential applications of Large Language Models (LLMs) in nuclear medicine, especially nuclear medicine examinations such as PET and SPECT, reviewing recent advancements in both fields. Despite the rapid adoption of LLMs in various medical specialties, their integration into nuclear medicine has not yet been sufficiently explored. We first discuss the latest developments in nuclear medicine, including new radiopharmaceuticals, imaging techniques, and clinical applications. We then analyze how LLMs are being utilized in radiology, particularly in report generation, image interpretation, and medical education. We highlight the potential of LLMs to enhance nuclear medicine practices, such as improving report structuring, assisting in diagnosis, and facilitating research. However, challenges remain, including the need for improved reliability, explainability, and bias reduction in LLMs. The review also addresses the ethical considerations and potential limitations of AI in healthcare. In conclusion, LLMs have significant potential to transform existing frameworks in nuclear medicine, making it a critical area for future research and development.

Correlation between 18F-FDG PET-derived parameters and quantitative pathological characteristics of soft tissue sarcoma

Background

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has been widely used for evaluating patients with soft tissue sarcoma (STS). However, uncertainties and overlap among individuals may be observed, and the relevance of these findings remains to be further explored. The present study was aimed at investigating the correlation between PET metabolic parameters and quantitative pathological characteristics in STS.

Methods

We retrospectively collected 39 patients with STS who underwent 18F-FDG PET/computed tomography (CT) examination before treatment. Metabolic parameters including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and intratumoral FDG uptake heterogeneity (IFH) were measured. Histological grading was performed according to the French Federation of Cancer Centers grading system. Continuous staining of tissue sections and digital quantitative analysis methods were used, the characteristics of tumor nucleated cells were observed through hematoxylin-eosin staining, and the expression of CD163, CD68, CD8, and CD4 in tumor tissues was determined by immunohistochemistry (IHC), then the correlation between FDG metabolic parameters and the above quantitative pathological characteristics in patients with STS were evaluated.

Results

The SUVmax of 18F-FDG PET/CT in STS was positively correlated with the total nuclear area (r=0.355, P=0.027). SUVmax was also positively correlated with the expression levels of CD163, CD68, CD8, and CD4 (r=0.582, 0.485, 0.343, and 0.324, with P<0.001, 0.002, 0.032, and 0.044, respectively), but was not significantly correlated with cell count and mean nuclear area (all P>0.05). However, MTV, TLG, and IFH were not significantly correlated with the above quantitative pathological characteristics. Further multivariate logistic regression analysis indicated that only CD163 expression and histological grade were independently correlated with SUVmax. Moreover, SUVmax remained positively correlated with CD163 expression in the low-grade STS (r=0.820, P=0.001) and high-grade STS groups (r=0.430, P=0.028).

Conclusions

18F-FDG uptake was positively correlated with the quantitative pathological features of soft tissue tumors. SUVmax may be a meaningful method reflecting the level of M2 macrophage infiltration and may provide additional valuable information for preclinical evaluation of STS.

From FDG and beyond: the evolving potential of nuclear medicine

The radiopharmaceutical 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) has been dominantly used in positron emission tomography (PET) scans for over 20 years, and due to its vast utility its applications have expanded and are continuing to expand into oncology, neurology, cardiology, and infectious/inflammatory diseases. More recently, the addition of artificial intelligence (AI) has enhanced nuclear medicine diagnosis and imaging with FDG-PET, and new radiopharmaceuticals such as prostate-specific membrane antigen (PSMA) and fibroblast activation protein inhibitor (FAPI) have emerged. Nuclear medicine therapy using agents such as [177Lu]-dotatate surpasses conventional treatments in terms of efficacy and side effects. This article reviews recently established evidence of FDG and non-FDG drugs and anticipates the future trajectory of nuclear medicine.

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

Purpose

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

Methods

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

Results

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

Conclusions

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