We evaluated the prognostic role of the largest distance between two lesions (Dmax), defined by positron emission tomography (PET) in a retrospective cohort of newly diagnosed classical Hodgkin ...Lymphoma (cHL) patients. We also explored the molecular bases underlying Dmax through a gene expression analysis of diagnostic biopsies. We included patients diagnosed with cHL from 2007 to 2020, initially treated with ABVD, with available baseline PET for review, and with at least two FDG avid lesions. Patients with available RNA from diagnostic biopsy were eligible for gene expression analysis. Dmax was deduced from the three‐dimensional coordinates of the baseline metabolic tumor volume (MTV) and its effect on progression free survival (PFS) was evaluated. Gene expression profiles were correlated with Dmax and analyzed using CIBERSORTx algorithm to perform deconvolution. The study was conducted on 155 eligible cHL patients. Using its median value of 20 cm, Dmax was the only variable independently associated with PFS (HR = 2.70, 95% CI 1.1–6.63, pValue = 0.03) in multivariate analysis of PFS for all patients and for those with early complete metabolic response (iPET‐). Among patients with iPET‐low Dmax was associated with a 4‐year PFS of 90% (95% CI 82.0–98.9) significantly better compared to high Dmax (4‐year PFS 72.4%, 95% CI 61.9–84.6). From the analysis of gene expression profiles differences in Dmax were mostly associated with variations in the expression of microenvironmental components. In conclusion our results support tumor dissemination measured through Dmax as novel prognostic factor for cHL patients treated with ABVD.
Total metabolic tumor volume (TMTV) and tumor dissemination (Dmax) calculated from baseline 18F-FDG PET/CT images are prognostic biomarkers in diffuse large B-cell lymphoma (DLBCL) patients. Yet, ...their automated calculation remains challenging. The purpose of this study was to investigate whether TMTV and Dmax features could be replaced by surrogate features automatically calculated using an artificial intelligence (AI) algorithm from only 2 maximum-intensity projections (MIPs) of the whole-body 18F-FDG PET images. Methods: Two cohorts of DLBCL patients from the REMARC (NCT01122472) and LNH073B (NCT00498043) trials were retrospectively analyzed. Experts delineated lymphoma lesions from the baseline whole-body 18F-FDG PET/CT images, from which TMTV and Dmax were measured. Coronal and sagittal MIP images and associated 2-dimensional reference lesion masks were calculated. An AI algorithm was trained on the REMARC MIP data to segment lymphoma regions. The AI algorithm was then used to estimate surrogate TMTV (sTMTV) and surrogate Dmax (sDmax) on both datasets. The ability of the original and surrogate TMTV and Dmax to stratify patients was compared. Results: Three hundred eighty-two patients (mean age ± SD, 62.1 y ± 13.4 y; 207 men) were evaluated. sTMTV was highly correlated with TMTV for REMARC and LNH073B datasets (Spearman r = 0.878 and 0.752, respectively), and so were sDmax and Dmax (r = 0.709 and 0.714, respectively). The hazard ratios for progression free survival of volume and MIP-based features derived using AI were similar, for example, TMTV: 11.24 (95% CI: 2.10–46.20), sTMTV: 11.81 (95% CI: 3.29–31.77), and Dmax: 9.0 (95% CI: 2.53–23.63), sDmax: 12.49 (95% CI: 3.42–34.50). Conclusion: Surrogate TMTV and Dmax calculated from only 2 PET MIP images are prognostic biomarkers in DLBCL patients and can be automatically estimated using an AI algorithm.
Total metabolic tumor volume (TMTV) and tumor dissemination (Dmax) calculated from baseline
F-FDG PET/CT images are prognostic biomarkers in diffuse large B-cell lymphoma (DLBCL) patients. Yet, their ...automated calculation remains challenging. The purpose of this study was to investigate whether TMTV and Dmax features could be replaced by surrogate features automatically calculated using an artificial intelligence (AI) algorithm from only 2 maximum-intensity projections (MIPs) of the whole-body
F-FDG PET images.
Two cohorts of DLBCL patients from the REMARC (NCT01122472) and LNH073B (NCT00498043) trials were retrospectively analyzed. Experts delineated lymphoma lesions from the baseline whole-body
F-FDG PET/CT images, from which TMTV and Dmax were measured. Coronal and sagittal MIP images and associated 2-dimensional reference lesion masks were calculated. An AI algorithm was trained on the REMARC MIP data to segment lymphoma regions. The AI algorithm was then used to estimate surrogate TMTV (sTMTV) and surrogate Dmax (sDmax) on both datasets. The ability of the original and surrogate TMTV and Dmax to stratify patients was compared.
Three hundred eighty-two patients (mean age ± SD, 62.1 y ± 13.4 y; 207 men) were evaluated. sTMTV was highly correlated with TMTV for REMARC and LNH073B datasets (Spearman
= 0.878 and 0.752, respectively), and so were sDmax and Dmax (
= 0.709 and 0.714, respectively). The hazard ratios for progression free survival of volume and MIP-based features derived using AI were similar, for example, TMTV: 11.24 (95% CI: 2.10-46.20), sTMTV: 11.81 (95% CI: 3.29-31.77), and Dmax: 9.0 (95% CI: 2.53-23.63), sDmax: 12.49 (95% CI: 3.42-34.50).
Surrogate TMTV and Dmax calculated from only 2 PET MIP images are prognostic biomarkers in DLBCL patients and can be automatically estimated using an AI algorithm.
Baseline
FFDG PET/CT radiomic features can improve the survival prediction in patients with diffuse large B-cell lymphoma (DLBCL). The purpose of this study was to investigate whether characterizing ...tumor locations relative to the spleen location in baseline
FFDG PET/CT images predicts survival in patients with DLBCL and improves the predictive value of total metabolic tumor volume (TMTV) and age-adjusted international prognostic index (IPI).
This retrospective study included 301 DLBCL patients from the REMARC (NCT01122472) cohort. Physicians delineated the tumor regions, whereas the spleen was automatically segmented using an open-access artificial intelligence algorithm. We systematically measured the distance between the centroid of the spleen and all other lesions, defining the SD of these distances as the lesion spread (SpreadSpleen). We calculated the maximum distance between the spleen and another lesion (Dspleen) for each patient and normalized it with the body surface area, resulting in standardized Dspleen (sDspleen). The predictive value of each PET/CT feature for progression-free survival (PFS) and overall survival (OS) was evaluated through univariate and multivariate time-dependent Cox models and Kaplan-Meier analysis.
In total, 282 patients (mean age, 68.33 ± 5.41 y; 164 men) were evaluated. The artificial intelligence algorithm successfully segmented the spleen in 96% of the patients. SpreadSpleen, Dspleen, and sDspleen were correlated neither with TMTV (Pearson ρ < 0.23) nor with IPI (Pearson ρ < 0.15). When median values were used as the cutoff, SpreadSpleen, Dspleen, and sDspleen all significantly classified patients into 2 risk groups for PFS and OS (
< 0.001). They complemented TMTV and IPI to classify the patients into 3 risk groups for PFS and OS (
< 0.001). Integrating SpreadSpleen, Dspleen, or sDspleen into a Cox model on the basis of TMTV, IPI, and TMTV combined with IPI significantly improved the concordance index for PFS and OS (
< 0.05).
Baseline PET/CT features that characterize tumor spread and dissemination relative to the spleen strongly predicted survival in patients with DLBCL. Integrating these features with TMTV and IPI further improved survival prediction.
The therapeutic field of in utero transplantation of stem cells, into human fetuses, has developed since 1988 with the hope of improved probability of engraftment and tolerance, due to immune ...immaturity of the host. Fifteen years later, it is possible to evaluate the results that we and others have obtained in the treatment of several fetal diseases. Seven fetal patients have been treated in Lyon: In 2 cases, pregnancy termination was induced by the in utero injection; in the 5 other cases, engraftment was obtained and repeatedly documented with presence of donor HLA antigens and/or Y chromosome in recipients. In the 2 patients with combined immunodeficiency disease, a sustained reconstitution of immunity was obtained as a result of the transplant but other complications occurred thereafter. In patients with thalassemia major, Niemann-Pick disease or hemophilia, a very partial and very transitory benefit was only obtained. Approximately 33 other patients with immunodeficiencies, hemoglobinopathies or inborn errors of metabolism have been treated worldwide, over the last 13 years, with a comparable method, using parental or fetal stem cells transplanted in utero. Successful treatment has usually been recorded in immunodeficiencies, and insufficient results have been obtained in the other cases. This form of treatment can therefore be recommended after prenatal diagnosis of combined immunodeficiency but additional research is required to improve the degree of engraftment, the lack of resistance of the host and the 'space' available for hematopoiesis in the other conditions.
