Introduction: Several reports have shown that radiomic feature values are affected by the acquisition and reconstruction parameters, thus hampering multicenter studies. We propose a method to standardize features measured from Positron Emission Tomography (PET) images obtained using different imaging protocols to remove the center effect while preserving patient-specific effects. Methods: Pre-treatment ¹⁸F-FDG-PET images of patients with breast cancer were included. In Department A, 63 patients were scanned using a Gemini Time-Of-Flight-PET/Computed-Tomography scanner including 16 triple-negative lesions (TN). In Department B, 74 patients underwent a PET on a GE Discovery 690 Scanner including 15 TN lesions. PET images from Department A were also smoothed using a Gaussian filter to mimic data from a third Department called Department A-S. The primary tumor was segmented to get a tumor volume of interest (VOI) and a spherical VOI was also set in healthy liver tissue. Three Standardized Uptake Values (SUVs) and 6 textural features were computed in all VOI using LIFEx software. A harmonization method, ComBat, initially described for genomic data, was used to estimate the department effect based on the observed feature values. Feature distributions in each department were compared before and after harmonization. Results: In healthy liver tissue, the feature distributions were significantly different for 4 out of 9 features between Departments A and B, and for 6 out of 9 between Departments A and A-S (p0.1). The same trend was observed in tumors with a realignment of feature values between the departments after ComBat. Identification of TN lesions was largely enhanced after harmonization when the cut-off values were determined on data from one department and applied to data from the other department. Conclusion: ComBat is efficient at removing the multicenter effect for textural features and SUVs. The method is easy to use, retains biological variations not related to a center effect, and does not require any feature recalculation. Such a harmonization allows for multicenter studies, external validation of radiomic models or cut-off values, and should facilitate the use of radiomic models in clinical practice.

Concurrent chemoradiotherapy (CRT) with blockade of the PD-1 pathway may enhance immune-mediated tumor control through increased phagocytosis, cell death, and antigen presentation. The NiCOL phase 1 trial (NCT03298893) is designed to determine the safety/tolerance profile and the recommended phase-II dose of nivolumab with and following concurrent CRT in 16 women with locally advanced cervical cancer. Secondary endpoints include objective response rate (ORR), progression free survival (PFS), disease free survival, and immune correlates of response. Three patients experience grade 3 dose-limiting toxicities. The pre-specified endpoints are met, and overall response rate is 93.8% [95%CI: 69.8–99.8%] with a 2-year PFS of 75% [95% CI: 56.5–99.5%]. Compared to patients with progressive disease (PD), progression-free (PF) subjects show a brisker stromal immune infiltrate, higher proximity of tumor-infiltrating CD3⁺ T cells to PD-L1⁺ tumor cells and of FOXP3⁺ T cells to proliferating CD11c⁺ myeloid cells. PF show higher baseline levels of PD-1 and ICOS-L on tumor-infiltrating EMRA CD4⁺ T cells and tumor-associated macrophages, respectively; PD instead, display enhanced PD-L1 expression on TAMs, higher peripheral frequencies of proliferating Tregs at baseline and higher PD-1 levels at week 6 post-treatment initiation on CD4 and CD8 T cell subsets. Concomitant nivolumab plus definitive CRT is safe and associated with encouraging PFS rates. Further validation in the subset of locally advanced cervical cancer displaying pre-existing, adaptive immune activation is warranted.

HER2 (Human Epidermal Growth Factor Receptor 2)-positive breast cancer is characterized by amplification of the HER2 gene and is associated with more aggressive tumor growth, increased risk of metastasis, and poorer prognosis when compared to other subtypes of breast cancer. HER2 expression is therefore a critical tumor feature that can be used to diagnose and treat breast cancer. Moving forward, advances in HER2 in vivo imaging, involving the use of techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT), may allow for a greater role for HER2 status in guiding the management of breast cancer patients. This will apply both to patients who are HER2-positive and those who have limited-to-minimal immunohistochemical HER2 expression (HER2-low), with imaging ultimately helping clinicians determine the size and location of tumors. Additionally, PET and SPECT could help evaluate effectiveness of HER2-targeted therapies, such as trastuzumab or pertuzumab for HER2-positive cancers, and specially modified antibody drug conjugates (ADC), such as trastuzumab-deruxtecan, for HER2-low variants. This review will explore the current and future role of HER2 imaging in personalizing the care of patients diagnosed with breast cancer.

The aim of this prospective study was to assess the predictive value of ¹⁸F-FDG PET/CT imaging for pathologic response to neoadjuvant chemotherapy (NACT) and outcome in inflammatory breast cancer (IBC) patients. Methods: Twenty-three consecutive patients (51 y ± 12.7) with newly diagnosed IBC, assessed by PET/CT at baseline (PET1), after the third course of NACT (PET2), and before surgery (PET3), were included. The patients were divided into 2 groups according to pathologic response as assessed by the Sataloff classification: pathologic complete response for complete responders (stage TA and NA or NB) and non–pathologic complete response for noncomplete responders (not stage A for tumor or not stage NA or NB for lymph nodes). In addition to maximum standardized uptake value (SUV_max) measurements, a global breast metabolic tumor volume (MTV) was delineated using a semiautomatic segmentation method. Changes in SUV_max and MTV between PET1 and PET2 (ΔSUV1–2; ΔMTV1–2) and PET1 and PET3 (ΔSUV1–3; ΔMTV1–3) were measured. Results: Mean SUV_max on PET1, PET2, and PET3 did not statistically differ between the 2 pathologic response groups. On receiver-operating-characteristic analysis, a 72% cutoff for ΔSUV1–3 provided the best performance to predict residual disease, with sensitivity, specificity, and accuracy of 61%, 80%, and 65%, respectively. On univariate analysis, the 72% cutoff for ΔSUV1–3 was the best predictor of distant metastasis-free survival (P = 0.05). On multivariate analysis, the 72% cutoff for ΔSUV1–3 was an independent predictor of distant metastasis-free survival (P = 0.01). Conclusion: Our results emphasize the good predictive value of change in SUV_max between baseline and before surgery to assess pathologic response and survival in IBC patients undergoing NACT.