Romidepsin Plus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone Versus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone in Patients With Previously Untreated Peripheral T-Cell Lymphoma: Final Analysis of the Ro-CHOP Trial.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.The primary analysis of the Ro-CHOP phase III randomized controlled trial (ClinicalTrials.gov identifier: NCT01796002) established that romidepsin (Ro) plus cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) did not yield an increased efficacy compared with CHOP alone as first-line treatment of peripheral T-cell lymphoma. We report the planned final analysis 5 years after the last patient enrolled. With a median follow-up of 6 years, median progression-free survival (PFS) was 12.0 months compared with 10.2 months (hazard ratio [HR], 0.79 [95% CI, 0.62 to 1.005]; P = .054), while median overall survival was 62.2 months (35.7-86.6 months) and 43.8 months (30.1-70.2 months; HR, 0.88 [95% CI, 0.68 to 1.14]; P = .324) in the Ro-CHOP and CHOP arms, respectively. In an exploratory analysis, the median PFS in the centrally reviewed follicular helper T-cell lymphoma subgroup was significantly longer in the Ro-CHOP arm (19.5 v 10.6 months, HR, 0.703 [95% CI, 0.502 to 0.985]; P = .039). Second-line treatments were given to 251 patients with a median PFS2 and OS2 after relapse or progression of 3.3 months and 11.5 months, respectively. Within the limits of highly heterogeneous second-line treatments, no specific regimen seemed to provide superior disease control. However, a potential benefit was observed with brentuximab vedotin in association with chemotherapy even after excluding anaplastic large-cell lymphoma subtype or after adjusting for histology and international prognostic index in a multivariate model (HR for PFS, 0.431 [95% CI, 0.238 to 0.779]; P = .005).

Outcome on Mesenteric Mass Response of Small-Intestinal Neuroendocrine Tumors Treated by 177Lu-DOTATATE Peptide Receptor Radionuclide Therapy: The MesenLuth Study, a National Study from the French Group of Endocrine Tumors and Endocan-RENATEN Network.

A mesenteric mass (MM), characterized by fibrotic reaction, is present in most small-intestinal neuroendocrine tumors (SI-NETs). 177Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) has shown its efficacy in patients with progressive SI-NETs. However, because of specific tissue characteristics of desmoplastic MMs, we hypothesize that these lesions may be refractory to 177Lu-DOTATATE PRRT. Methods: From the national French Groupe d'étude des Tumeurs Endocrines database, we identified patients with an advanced SI-NET and a MM (≥2 cm with a retractile aspect) of a SI-NET treated by at least 1 course of 177Lu-DOTATATE PRRT. The primary endpoint was a MM objective response rate (ORR) of less than 5%. Secondary endpoints were metabolic response, MM-related safety, and clinical response, as well as MM progression-free survival (PFS) and non-MM PFS. Results: In total, 52 patients were included. The MM ORR was 4% (n = 2), and the non-MM ORR was 8% (n = 4). No patient had a MM metabolic response, and the non-MM metabolic response rate was 12% (n = 6). Among the 26 patients with baseline MM-related symptoms, 46% had a clinical response. Four patients presented with gastrointestinal complications during PRRT. The median MM-related PFS was not reached, and the non-MM PFS was 50.3 mo (95% CI, 38.2-61.7 mo). Conclusion: This study confirms that 177Lu-DOTATATE PRRT does not lead to morphologic response on MMs (ORR < 5%). However, it allows MM stability, with few MM-related side effects, and has a relevant impact on MM-related symptoms.

Tumor Location Relative to the Spleen Is a Prognostic Factor in Lymphoma Patients: A Demonstration from the REMARC Trial.

Baseline [18F]FDG 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 [18F]FDG 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). Methods: 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. Results: 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 (P < 0.001). They complemented TMTV and IPI to classify the patients into 3 risk groups for PFS and OS (P < 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 (P < 0.05). Conclusion: 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.

Pharmacokinetics/Pharmacodynamics of Dabrafenib and Trametinib for Redifferentiation and Treatment of Radioactive Iodine-Resistant Mutated Advanced Differentiated Thyroid Cancer.

Background: BRAF and MEK inhibitors are cornerstones of the redifferentiation strategy in metastatic radioactive iodine (RAI)-resistant mutant thyroid cancers. We explored the exposure-toxicity relationship for dose-limiting toxicity (DLT) onset in patients treated with dabrafenib and/or trametinib and investigated whether plasma exposure was associated with RAI reuptake. Methods: We conducted a retrospective monocentric study in which we reviewed the electronic medical records of patients treated in our institution with a tumor redifferentiation strategy, for whom plasma concentration of dabrafenib, its active metabolite hydroxy-dabrafenib, and trametinib was measured. Trough concentrations (Cminpred) and total plasma drug exposure (area under the curve, AUC) of dabrafenib (AUCDAB), hydroxy-dabrafenib (AUCOHD), and trametinib (AUCTRA) were estimated. Results: Of the 22 patients treated in a redifferentiation strategy between March 2014 and December 2021, 15 were included in this study. A dabrafenib- or trametinib-related DLT was experienced by 8 (62%) and 9 (64%) patients, respectively. Patients who experienced a trametinib-related DLT exhibited a significantly higher last AUCTRA than the average AUCTRA of patients who had no DLT (390, IQR: 67 vs. 215, IQR: 91 ng/mL·h-1, respectively; p = 0.008). Patients who experienced a dabrafenib-related DLT had a higher AUCDAB than observed in other patients (9265 ng/mL·h-1 vs. 6953 ng/mL·h-1, respectively; p = 0.09). No clinical and demographical characteristic was associated with the DLT onset. Overall, 9 of 15 (60%) patients demonstrated tumor redifferentiation. Patients in whom RAI reuptake was achieved had significant lower AUCDAB (6990 ng/mL·h-1 vs. 9764 ng/mL·h-1, p = 0.014; respectively) compared with patients who did not. Moreover, the relative exposure ratio of AUCOHD/DAB was significantly higher in patients who achieved RAI reuptake (1.11 vs. 0.71, respectively; p = 0.0047). Conclusions: Our data suggest a relationship between DLT onset and trametinib plasma exposure, as well as an association between achievement of RAI reuptake and dabrafenib plasma exposure (AUC and ratio of AUCOHD/DAB). These data imply that the use of plasma drug monitoring could be helpful in guiding clinical practice in redifferentiation treatment.

Personalised therapy in follicular lymphoma - is the dial turning?

Follicular lymphoma is the most common indolent lymphoma accounting for approximately 20%-25% of all new non-Hodgkin lymphoma diagnoses in western countries. Whilst outcomes are mostly favorable, the spectrum of clinical phenotypes includes high-risk groups with significantly inferior outcomes. This review discusses recent updates in risk stratification and treatment approaches from upfront treatment for limited and advanced stage follicular lymphoma to the growing options for relapsed, refractory disease with perspectives on how to approach this from a personalized lens. Notable gaps remain on how one can precisely and prospectively select optimal treatment for patients based on varying risks, with an anticipation that an increased understanding of the biology of these different phenotypes and increasing refinement of imaging- and biomarker-based tools will, in time, allow these gaps to be closed.

[Well-differentiated neuroendocrine tumors of the digestive tract: Focus on pancreatic neuroendocrine tumors]. / Tumeurs neuroendocrines digestives bien différenciées: focus sur les tumeurs pancréatiques.

Pancreatic neuroendocrine tumors are rare tumors showing a rising incidence. They are well-differentiated tumors, classified by grade according to their Ki67 index value (grade 1 to 3). Pancreatic neuroendocrine tumors are mainly sporadic tumors but about 10% arise within endocrine tumor syndromes such as multiple endocrine neoplasia type 1. They can be responsible for functional syndromes or non-specific clinical symptoms depending on tumor extension. However, there is also an increase of incidental diagnoses of nonfunctional pancreatic neuroendocrine tumors with the widespread use of high-quality imaging techniques. About 50 % of pancreatic neuroendocrine tumors are diagnosed at a metastatic stage, with metastases often located in the liver. Chromogranin A, CT-scan and often an abdominal MRI, and functional imaging should be performed for tumor staging and follow-up. Imaging with PET/CT with 68Ga-labeled somatostatin analogues has the highest sensitivity for the diagnosis of pancreatic neuroendocrine tumors, while 18fluorodeoxyglucose PET/CT can sometimes be useful. Overall, they are rather indolent tumors with prolonged survival. Surgery is the recommended treatment in the localized setting, with the exception of small<2cm nonfunctional tumors that can be monitored with imaging techniques. For advanced tumors, there are several available treatments such as somatostatine analogues, chemotherapy, targeted therapies (sunitinib, everolimus), locoregional ablative therapies and Peptide Receptor Radiolabelled Therapy. The treatment strategy will depend on the initial tumor staging, tumor grade, aggressiveness and patient's choice.

Positive Correlation Between 18 F-FDG Uptake and Tumor-Proliferating Antigen Ki-67 Expression in Adrenocortical Carcinomas.

PURPOSE OF THE REPORT: Adrenocortical carcinoma (ACC) is an extremely rare endocrine malignancy, which cannot always be diagnosed during conventional radiology and hormonal investigations. 18 F-FDG PET could help predict malignancy, but more data are necessary to support future guidelines. METHODS: A cohort of 63 patients with histologically proven ACC (n = 55) or metastatic ACC with steroid oversecretion (n = 8) was assembled. All patients underwent an 18 F-FDG PET, and the SUV max and the adrenal-to-liver SUV max ratio were calculated. The 18 F-FDG PET parameters were compared with clinical, pathological, and outcome data. RESULTS: Fifty-six of 63 patients (89%) had an ACC with an adrenal-to-liver SUV max ratio >1.45, which was a previously defined cutoff value to predict malignancy with 100% sensitivity. Seven ACCs (11%) had a lower uptake (adrenal-to-liver SUV max <1.45), most of them with a proliferation marker Ki-67 expression level <10%. A positive correlation between 18 F-FDG PET parameters (SUV max and adrenal-to-liver SUV max ratio) and tumor size, ENSAT (European Network for the Study of Adrenal Tumors) staging, total Weiss score, and the Ki-67 was found. The strong correlation between SUV max and Ki-67 ( r = 0.47, P = 0.0009) suggests a relationship between 18 F-FDG uptake levels and tumor proliferation. No statistically significant associations between outcome parameters (progression-free or overall survival) and 18 F-FDG PET parameters were found. CONCLUSIONS: This large cohort study shows that most cases of ACC demonstrate high 18 F-FDG uptake. However, the positive correlation observed between SUV max and Ki-67 expression levels seems to explain the possibility of identifying some ACC with a low or inexistent 18 F-FDG uptake. These findings have practical implications for the management of patients with an adrenal mass.

Artificial intelligence in adrenal imaging: A critical review of current applications.

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps from detection to analysis does not exist yet, multiple AI algorithms have been developed and tested with encouraging results. However, AI in this setting is still at an early stage. In this regard, most published studies about AI in adrenal gland imaging report preliminary results that do not have yet daily applications in clinical practice. In this review, recent developments and current results of AI in the field of adrenal imaging are presented. Limitations and future perspectives of AI are discussed.

A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma.

Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools use factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse before initial treatment. A model associating 2 risk factors, total metabolic tumor volume (TMTV) >220 cm3 (determined by fluorine-18 fluorodeoxyglucose positron emission tomography coupled with computed tomography) and performance status (PS) ≥2, identified as prognostic in 301 older patients in the REMARC trial (#NCT01122472), was validated in 2174 patients of all ages treated in 2 clinical trials, PETAL (Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas; N = 510) and GOYA (N = 1315), and in real-world clinics (N = 349) across Europe and the United States. Three risk categories, low (no factors), intermediate (1 risk factor), and high (2 risk factors), significantly discriminated outcome in most of the series. Patients with 2 risk factors had worse outcomes than patients with no risk factors in the PETAL, GOYA, and real-world series. Patients with intermediate risk also had significantly worse outcomes than patients with no risk factors. The TMTV/Eastern Cooperative Oncology Group-PS combination outperformed the International Prognostic Index with a positive C-index for progression-free survival and overall survival in most series. The combination of high TMTV > 220 cm3 and ECOG-PS ≥ 2 is a simple clinical model to identify aggressive LBCL risk categories before treatment. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL the patients likely to benefit the most or not at all from therapy.

18F-FDG PET Maximum-Intensity Projections and Artificial Intelligence: A Win-Win Combination to Easily Measure Prognostic Biomarkers in DLBCL Patients.

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.

High-risk stage IIB Hodgkin lymphoma treated in the H10 and AHL2011 trials: total metabolic tumor volume is a useful risk factor to stratify patients at baseline.

Stage IIB Hodgkin lymphoma (HL) patients, with a mediastinum-to-thorax (M/T) ratio of ≥0.33 or extranodal localization have a poor prognosis and are treated either as limited or advanced stage. We compared these two approaches in patients included in two randomized phase III trials enrolling previously untreated early (H10) or advanced stage HL (AHL2011). We included HL patients with Ann-Arbor stage IIB with M/T ≥0.33 or extranodal involvement enrolled in the H10 or AHL2011 trials with available positron emission tomography at baseline (PET0) and after two cycles of chemotherapy (PET2). Baseline total metabolic tumor volume (TMTV) was calculated using the 41% SUVmax method. PET2 response assessment used the Deauville score. One hundred and fourty-eight patients were eligible, including 83 enrolled in the AHL2011 trial and 65 in the H10 trial. The median TMTV value was 155.5 mL (range, 8.3-782.9 mL), 165.6 mL in AHL2011 and 147 mL in H10. PET2 positivity rates were 16.9% (n=14) and 9.2% (n=6) in AHL2011 and H10 patients, respectively. With a median follow-up of 4.1 years (95% confidence interval [CI]: 3.9-4.4), overall 4-year PFS was 88.0%, 87.0% in AHL2011 and 89.2% in H10. In univariate and mutivariate analyses, baseline TMTV and PET2 response influenced significantly progression-free survival (hazard ratio [HR]=4.94, HR=3.49 respectively). Notably, among the 16 patients who relapsed, 13 (81%) had a baseline TMTV baseline ≥155 mL. Upfront ABVD plus radiation therapy or upfront escBEACOPP without radiotherapy provide similar patient's outcome in high-risk stage IIB HL. TMTV is useful to stratify these patients at baseline.

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

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

Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas.

The total metabolic tumor volume (TMTV) is a new prognostic factor in lymphomas that could benefit from automation with deep learning convolutional neural networks (CNN). Manual TMTV segmentations of 1218 baseline 18FDG-PET/CT have been used for training. A 3D V-NET model has been trained to generate segmentations with soft dice loss. Ground truth segmentation has been generated using a combination of different thresholds (TMTVprob), applied to the manual region of interest (Otsu, relative 41% and SUV 2.5 and 4 cutoffs). In total, 407 and 405 PET/CT were used for test and validation datasets, respectively. The training was completed in 93 h. In comparison with the TMTVprob, mean dice reached 0.84 in the training set, 0.84 in the validation set and 0.76 in the test set. The median dice scores for each TMTV methodology were 0.77, 0.70 and 0.90 for 41%, 2.5 and 4 cutoff, respectively. Differences in the median TMTV between manual and predicted TMTV were 32, 147 and 5 mL. Spearman's correlations between manual and predicted TMTV were 0.92, 0.95 and 0.98. This generic deep learning model to compute TMTV in lymphomas can drastically reduce computation time of TMTV.

Redifferentiating Effect of Larotrectinib in NTRK-Rearranged Advanced Radioactive-Iodine Refractory Thyroid Cancer.

Metastatic thyroid cancers may dedifferentiate and become radioactive-iodine (RAI) resistant. A redifferentiating effect can be observed with inhibitors of the mitogen-activated protein kinase pathway in thyroid cancers with point mutation in oncogenes. This effect allows RAI reuptake that may lead to a therapeutic effect different from the antitumoral effect of the inhibitor. The potential redifferentiating effect of inhibitors targeting oncogenic fusion-genes was suggested by one adult and one pediatric patient using larotrectinib in NTRK-rearranged tumors. We report on three consecutive adult patients with metastatic RAI-resistant NTRK-rearranged thyroid cancer who received larotrectinib for disease progression and for whom the redifferentiating effect was examined. Larotrectinib-induced RAI reuptake in all or part of the metastatic disease for two patients and no reuptake was noted for the other patient. We demonstrate that redifferentiation of NTRK-rearranged RAI-resistant thyroid cancer with larotrectinib may exist but does not occur in all patients.

Adrenal Mass Characterization in the Era of Quantitative Imaging: State of the Art.

Detection and characterization of adrenal lesions have evolved during the past two decades. Although the role of imaging in adrenal lesions associated with hormonal secretion is usually straightforward, characterization of non-functioning adrenal lesions may be challenging to confidently identify those that need to be resected. Although many adrenal lesions can be readily diagnosed when they display typical imaging features, the diagnosis may be challenging for atypical lesions. Computed tomography (CT) remains the cornerstone of adrenal imaging, but other morphological or functional modalities can be used in combination to reach a diagnosis and avoid useless biopsy or surgery. Early- and delayed-phase contrast-enhanced CT images are essential for diagnosing lipid-poor adenoma. Ongoing studies are evaluating the capabilities of dual-energy CT to provide valid virtual non-contrast attenuation and iodine density measurements from contrast-enhanced examinations. Adrenal lesions with attenuation values between 10 and 30 Hounsfield units (HU) on unenhanced CT can be characterized by MRI when iodinated contrast material injection cannot be performed. 18F-FDG PET/CT helps differentiate between atypical benign and malignant adrenal lesions, with the adrenal-to-liver maximum standardized uptake value ratio being the most discriminative variable. Recent studies evaluating the capabilities of radiomics and artificial intelligence have shown encouraging results.

18F-fluorocholine PET/CT and conventional imaging in primary hyperparathyroidism.

PURPOSE: The purpose of this study was to assess the diagnostic capabilities of preoperative conventional imaging (99mTc-MIBI scintigraphy, cervical ultrasonography [CUS]) and 18F-fluorocholine PET/CT (FCH PET/CT) in the detection of hyperfunctioning parathyroid gland in patients with primary hyperparathyroidism (PHPT) used alone or as a single imaging set. MATERIALS AND METHODS: A total of 51 consecutive patients (6 men, 45 women; mean age, 62 ± 11.6 [SD] years; age range: 28-86 years) with biochemically confirmed PHPT who underwent CUS, single-tracer dual phase 99mTc-MIBI scintigraphy and FCH PET/CT were retrospectively included. 99mTc-MIBI scintigraphy were performed immediately after CUS and interpreted by the same operators. FCH PET/CT examinations were interpreted independently by two nuclear medicine physicians. An additional reading session integrating the three imaging modalities read in consensus as a combined imaging set was performed. RESULTS: At surgery, 74 lesions were removed (32 parathyroid adenomas, 38 parathyroid hyperplasia and 4 subnormal glands). Thirty-six patients (71%) had single-gland disease and 15 patients (29%) had multiglandular disease at histopathological analysis. On a patient basis, sensitivity and accuracy of FCH PET/CT, CUS and 99mTc-MIBI scintigraphy for the detection of abnormal parathyroid glands were 76% (95% CI: 63-87%) and 76% (95% CI: 63-87%), 71% (95% CI: 56-83%) and 71% (95% CI: 56-83%), 33% (95% CI: 21-48%) and 33% (95% CI: 21-48%), respectively. The sensitivity of the combined imaging set was 94% (95% CI: 84-99%) and greater than the sensitivity of each individual imaging technique (P ≤ 0.001 for all). CONCLUSION: Our results suggest that CUS, 99mTc-MIBI scintigraphy and FCH PET/CT interpreted as a single imaging set could be the ideal practice to precisely localize parathyroid lesion in patients with PHPT before surgery.

A Guide to ComBat Harmonization of Imaging Biomarkers in Multicenter Studies.

The impact of PET image acquisition and reconstruction parameters on SUV measurements or radiomic feature values is widely documented. This scanner effect is detrimental to the design and validation of predictive or prognostic models and limits the use of large multicenter cohorts. To reduce the impact of this scanner effect, the ComBat method has been proposed and is now used in various contexts. The purpose of this article is to explain and illustrate the use of ComBat based on practical examples. We also give examples in which the ComBat assumptions are not met and, thus, in which ComBat should not be used.