The gut microbiome has been shown to influence the response of tumors to anti-PD-1 (programmed cell death-1) immunotherapy in preclinical mouse models and observational patient cohorts. However, ...modulation of gut microbiota in cancer patients has not been investigated in clinical trials. In this study, we performed a phase 1 clinical trial to assess the safety and feasibility of fecal microbiota transplantation (FMT) and reinduction of anti-PD-1 immunotherapy in 10 patients with anti-PD-1-refractory metastatic melanoma. We observed clinical responses in three patients, including two partial responses and one complete response. Notably, treatment with FMT was associated with favorable changes in immune cell infiltrates and gene expression profiles in both the gut lamina propria and the tumor microenvironment. These early findings have implications for modulating the gut microbiota in cancer treatment.
Ipsilateral avid axillary lymph node uptake at FDG PET/CT persists in 29% (49 of 169) of patients between 7 to 10 weeks after the second dose of the mRNA-based BNT162b2 COVID-19 vaccination.
Immune checkpoint inhibitors have introduced a new and heterogeneous class of immune-related adverse effects, with the endocrine system being a predominant target for autoimmunity. Autoimmune ...hypothalamic-pituitary-adrenal axis (HPA) diseases induced by checkpoint inhibitors are being increasingly recognized. We aimed to characterize the spectrum of checkpoint associated hypothalamic-pituitary-adrenal axis endocrinopathies.
A retrospective cohort study of a tertiary cancer center.
Patients were characterized for HPA axis abnormalities based on clinical and pituitary axes evaluation. The risk for developing HPA endocrinopathies was compared by log- rank test, by the time since checkpoint inhibitors initiation. Additionally, the risk for developing HPA endocrinopathies after adjusting for covariates was assessed using multivariable logistic regression analysis.
Among 1615 patients, fourteen (0.87%) patients developed isolated adrecocorticotrophic hormone deficiency (IAD), six (0.37%) - hypophysitis and no case of adrenalitis was identified. IAD presented with mild and non-specific symptoms, mainly asthenia. In multivariable analysis, exposure to both PD-1/PD-L1 and Ipilimumab and female gender were associated with an increased odds ratio (OR) for developing IAD (6.98 95% CI 2.38–20.47, p < .001 and 3.67 95% CI 1.13–11.84, p = .03), respectively.
IAD, a rare disease before the immunotherapy era, has become a predominant checkpoint related HPA axis autoimmune injury. Despite its life threatening potential, IAD may be missed due to its subtle presentation. Patients exposed to Ipilimumab and PD-1/PD-L1 in combination or sequentially and women have an increased risk for developing IAD.
Goal
PET is a relatively noisy process compared to other imaging modalities, and sparsity of acquisition data leads to noise in the images. Recent work has focused on machine learning techniques to ...improve PET images, and this study investigates a deep learning approach to improve the quality of reconstructed image volumes through denoising by a 3D convolution neural network. Potential improvements were evaluated within a clinical context by physician performance in a reading task.
Methods
A wide range of controlled noise levels was emulated from a set of chest PET data in patients with lung cancer, and a convolutional neural network was trained to denoise the reconstructed images using the full-count reconstructions as the ground truth. The benefits, over conventional Gaussian smoothing, were quantified across all noise levels by observer performance in an image ranking and lesion detection task.
Results
The CNN-denoised images were generally ranked by the physicians equal to or better than the Gaussian-smoothed images for all count levels, with the largest effects observed in the lowest-count image sets. For the CNN-denoised images, overall lesion contrast recovery was 60% and 90% at the 1 and 20 million count levels, respectively. Notwithstanding the reduced lesion contrast recovery in noisy data, the CNN-denoised images also yielded better lesion detectability in low count levels. For example, at 1 million true counts, the average true positive detection rate was around 40% for the CNN-denoised images and 30% for the smoothed images.
Conclusion
Significant improvements were found for CNN-denoising for very noisy images, and to some degree for all noise levels. The technique presented here offered however limited benefit for detection performance for images at the count levels routinely encountered in the clinic.
Objectives
To evaluate if radiomics with machine learning can differentiate between F-18-fluorodeoxyglucose (FDG)-avid breast cancer metastatic lymphadenopathy and FDG-avid COVID-19 mRNA ...vaccine–related axillary lymphadenopathy.
Materials and methods
We retrospectively analyzed FDG-positive, pathology-proven, metastatic axillary lymph nodes in 53 breast cancer patients who had PET/CT for follow-up or staging, and FDG-positive axillary lymph nodes in 46 patients who were vaccinated with the COVID-19 mRNA vaccine. Radiomics features (110 features classified into 7 groups) were extracted from all segmented lymph nodes. Analysis was performed on PET, CT, and combined PET/CT inputs. Lymph nodes were randomly assigned to a training (
n
= 132) and validation cohort (
n
= 33) by 5-fold cross-validation. K-nearest neighbors (KNN) and random forest (RF) machine learning models were used. Performance was evaluated using an area under the receiver-operator characteristic curve (AUC-ROC) score.
Results
Axillary lymph nodes from breast cancer patients (
n
= 85) and COVID-19-vaccinated individuals (
n
= 80) were analyzed. Analysis of first-order features showed statistically significant differences (
p
< 0.05) in all combined PET/CT features, most PET features, and half of the CT features. The KNN model showed the best performance score for combined PET/CT and PET input with 0.98 (± 0.03) and 0.88 (± 0.07) validation AUC, and 96% (± 4%) and 85% (± 9%) validation accuracy, respectively. The RF model showed the best result for CT input with 0.96 (± 0.04) validation AUC and 90% (± 6%) validation accuracy.
Conclusion
Radiomics features can differentiate between FDG-avid breast cancer metastatic and FDG-avid COVID-19 vaccine–related axillary lymphadenopathy. Such a model may have a role in differentiating benign nodes from malignant ones.
Key Points
• Patients who were vaccinated with the COVID-19 mRNA vaccine have shown FDG-avid reactive axillary lymph nodes in PET-CT scans.
• We evaluated if radiomics and machine learning can distinguish between FDG-avid metastatic axillary lymphadenopathy in breast cancer patients and FDG-avid reactive axillary lymph nodes.
• Combined PET and CT radiomics data showed good test AUC (0.98) for distinguishing between metastatic axillary lymphadenopathy and post-COVID-19 vaccine–associated axillary lymphadenopathy. Therefore, the use of radiomics may have a role in differentiating between benign from malignant FDG-avid nodes.
Objective
To investigate the patterns of breast cancer-related and lactation-related
18
F-FDG uptake in breasts of lactating patients with pregnancy-associated breast cancer (PABC) and without breast ...cancer.
Methods
18
F-FDG-PET/CT datasets of 16 lactating patients with PABC and 16 non-breast cancer lactating patients (controls) were retrospectively evaluated. Uptake was assessed in the tumor and non-affected lactating tissue of the PABC group, and in healthy lactating breasts of the control group, using maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), and breast-SUVmax/liver-SUVmean ratio. Statistical tests were used to evaluate differences and correlations between the groups.
Results
Physiological uptake in non-breast cancer lactating patients’ breasts was characteristically high regardless of active malignancy status other than breast cancer (SUVmax = 5.0 ± 1.7,
n
= 32 breasts). Uptake correlated highly between the two breasts (
r
= 0.61,
p
= 0.01), but was not correlated with age or lactation duration (
p
= 0.24 and
p
= 0.61, respectively). Among PABC patients, the tumors demonstrated high
18
F-FDG uptake (SUVmax = 7.8 ± 7.2,
n
= 16), which was 326–643% higher than the mostly low physiological FDG uptake observed in the non-affected lactating parenchyma of these patients (SUVmax = 2.1 ± 1.1). Overall,
18
F-FDG uptake in lactating breasts of PABC patients was significantly decreased by 59% (
p
< 0.0001) compared with that of lactating controls without breast cancer.
Conclusion
18
F-FDG uptake in lactating tissue of PABC patients is markedly lower compared with the characteristically high physiological uptake among lactating patients without breast cancer. Consequently, breast tumors visualized by
18
F-FDG uptake in PET/CT were comfortably depicted on top of the background
18
F-FDG uptake in lactating tissue of PABC patients.
Key Points
• FDG uptake in the breast is characteristically high among lactating patients regardless of the presence of an active malignancy other than breast cancer.
• FDG uptake in non-affected lactating breast tissue is significantly lower among PABC patients compared with that in lactating women who do not have breast cancer.
•
In pregnancy-associated breast cancer patients,
18
F-FDG uptake is markedly increased in the breast tumor compared with uptake in the non-affected lactating tissue, enabling its prompt visualization on PET/CT.
Immune-checkpoint inhibitor (ICI)-related diarrhea is attributed to inflammatory colitis, with no other drug-related differential diagnosis. Here, we investigated the occurrence of pancreatic atrophy ...(PA) in ICI-treated cancer patients and its correlation to exocrine pancreatic insufficiency (EPI). Metastatic melanoma, non-small cell lung carcinoma, and head and neck squamous cell carcinoma patients (
= 403) treated with anti-PD-1 (
= 356) or anti-CTLA-4 (
= 47) were divided into a case group (radiologic evidence of PA); control group matched by age, gender, and previous lines of treatment; and colitis group (ICI-induced colitis). Quantitative pancreatic volumetry was used for calculation of the decrease in pancreatic volume over time (atrophy rate). Thirty-one patients (7.7%) developed PA compared with 41 matched controls (
= 0.006). Four patients developed EPI, all from the anti-PD-1-treated group, which resolved with oral enzyme supplementation. The atrophy rate did not correlate with EPI (
= 0.87). EPI-related diarrhea presented at a median of 9 months, whereas the diarrhea of anti-PD-1-induced colitis patients (
= 22) was presented at a median of 2 months (
= 0.029). ICI-induced PA is irreversible and can result in EPI. EPI should be suspected in cases of late-onset steroid-resistant diarrhea with features of steatorrhea and treated with oral enzyme supplements.
Purpose
To assess whether
18
F-DCFPyL PET/multiparametric (mp)MR contributes to the diagnosis of clinically significant (cs) prostate cancer (PCa) compared to mpMR in patients with suspicion of PCa, ...or patients being considered for focal ablative therapies (FT).
Patients and methods
This ethics review board–approved, prospective study included 55 men with suspicion of PCa and negative systematic biopsies or clinically discordant low-risk PCa (
n
= 21) or those being considered for FT (
n
= 34) who received
18
F-DCFPyL PET/mpMR. Each modality, PET, mpMR, and PET/MR (using the PROMISE classification), was assessed independently. All suspicious lesions underwent PET/MR-ultrasound fusion biopsies.
Results
There were 45/55 patients (81.8%) that had histologically proven PCa and 41/55 (74.5%) were diagnosed with csPCa. Overall, 61/114 lesions (53.5%) identified on any modality were malignant; 49/61 lesions (80.3%) were csPCa. On lesion-level analysis, for detection of csPCa, the sensitivity of PET was higher than that of mpMR and PET/MR (86% vs 67% and 69%
p
= 0.027 and 0.041, respectively), but at a lower specificity (32% vs 85% and 86%, respectively
p
< 0.001). The performance of MR and PET/MR was comparable. For identification of csPCa in PI-RADS ≥ 3 lesions, the AUC (95% CI) for PET, mpMR, and PET/MR was 0.75 (0.65–0.86), 0.69 (0.56–0.82), and 0.78 (0.67–0.89), respectively. The AUC for PET/MR was significantly larger than that of mpMR (
p
= 0.04).
Conclusion
PSMA PET detects more csPCa than mpMR, but at low specificity. The performance PET/MR is better than mpMR for detection of csPCa in PI-RADS ≥ 3 lesions.
Clinical registration
NCT 03149861
The aim of the study is to evaluate the prognostic value of a joint evaluation of PET and CT radiomics combined with standard clinical parameters in patients with HL.
Overall, 88 patients (42 female ...and 46 male) with a median age of 43.3 (range 21-85 years) were included. Textural analysis of the PET/CT images was performed using freely available software (LIFE X). 65 radiomic features (RF) were evaluated. Univariate and multivariate models were used to determine the value of clinical characteristics and FDG PET/CT radiomics in outcome prediction. In addition, a binary logistic regression model was used to determine potential predictors for radiotherapy treatment and odds ratios (OR), with 95% confidence intervals (CI) reported. Features relevant to survival outcomes were assessed using Cox proportional hazards to calculate hazard ratios with 95% CI.
albumin (
= 0.034) + ALP (
= 0.028) + CT radiomic feature GLRLM GLNU mean (
= 0.012) (Area under the curve (AUC): 95% CI (86.9; 100.0)-Brier score: 3.9, 95% CI (0.1; 7.8) remained significant independent predictors for PFS outcome. PET-SHAPE Sphericity (
= 0.033); CT grey-level zone length matrix with high gray-level zone emphasis (GLZLM SZHGE mean (
= 0.028)); PARAMS XSpatial Resampling (
= 0.0091) as well as hemoglobin results (
= 0.016) remained as independent factors in the final model for a binary outcome as predictors of the need for radiotherapy (AUC = 0.79).
We evaluated the value of baseline clinical parameters as well as combined PET and CT radiomics in HL patients for survival and the prediction of the need for radiotherapy treatment. We found that different combinations of all three factors/features were independently predictive of the here evaluated endpoints.
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