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Efficacy of the human epidermal growth factor receptor (HER)2-targeting trastuzumab emtansine (T-DM1) in breast cancer (BC) relies on HER2 status determined by immunohistochemistry or fluorescence in-situ hybridization. Heterogeneity in HER2 expression, however, generates interest in “whole-body” assessment of HER2 status using molecular imaging. We evaluated the role of HER2-targeted molecular imaging in detecting HER2-positive BC lesions and patients unlikely to respond to T-DM1. Patients underwent zirconium-89 (89Zr) trastuzumab (HER2) PET/CT and [18F]-2-fluoro-2-deoxy-D-glucose (FDG) PET/CT before T-DM1 initiation. Based on 89Zr-trastuzumab uptake, lesions were visually classified as HER2-positive (visible/high uptake) or HER2-negative (background/close to background activity). According to proportion of FDG-avid tumor load showing 89Zr-trastuzumab uptake (entire/dominant part or minor/no part), patients were classified as HER2-positive and HER2-negative, respectively. Out of 265 measurable lesions, 93 (35%) were HER2-negative, distributed among 42 of the 90 included patients. Of these, 18 (19%) lesions belonging to 11 patients responded anatomically (>30% decrease in axial diameter from baseline) after three T-DM1 cycles, resulting in an 81% negative predictive value (NPV) of the HER2 PET/CT. In combination with early metabolic response assessment on FDG PET/CT performed before the second T-DM1 cycle, NPVs of 91% and 100% were reached in predicting lesion-based and patient-based (RECIST1.1) response, respectively. Therefore, HER2 PET/CT, alone or in combination with early FDG PET/CT, can successfully identify BC lesions and patients with a low probability of clinical benefit from T-DM1.

Background Percutaneous endoscopic gastrostomy (PEG) is often used to provide nutritional support in locally advanced head and neck cancer patients undergoing multimodality treatment. However, there is little published data on the impact of prophylactic versus reactive PEG. PEG placement may affect swallowing-related physiology, function, and quality of life. The Swall PEG study is a randomized controlled phase III trial testing the impact of prophylactic versus reactive PEG on patient-reported outcomes in terms of swallowing and quality of life in oropharyngeal cancer patients. Methods Patients with locally advanced oropharyngeal cancer receiving chemo-radiotherapy will be randomized to either the prophylactic or reactive PEG tube group. Randomization will be stratified by human papillomavirus (HPV) status and unilateral versus bilateral positive neck lymph nodes. The primary objective of the study is the patient’s reported outcome in terms of swallowing (MD Anderson Dysphagia Inventory (MDADI)) at 6 months. Secondary objectives include health-related quality of life, dosimetric parameters associated with patient-reported outcomes, chemo-radiation toxicities, PEG tube placement complications, the impact of nutritional status on survival and toxicity outcomes, loco-regional control, overall survival, the impact of HPV and tobacco smoking on survival outcomes and toxicities, and the cost-effectiveness of each treatment strategy. Discussion Findings from this study will enhance clinical evidence regarding nutritional management in oropharyngeal cancer patients treated by concurrent chemo-radiation. Trial registration ClinicalTrials.gov NCT04019548, study protocol version 2.0_08/08/2019. Registered on 15 July 2019

Purpose Sampling perfection with application-optimized contrasts by using different flip angle evolutions (SPACE) is a black-blood 3D T1-weighted (T1w) magnetic resonance imaging (MRI) sequence that has shown robust performance for brain metastases detection. However, this could generate false positive results due to suboptimal blood signal suppression. For that reason, SPACE is used in our institution alongside a non-black-blood T1w sequence: volumetric interpolated breath-hold examination (VIBE). Our study aims to (i) evaluate the diagnostic accuracy of SPACE compared to its use in combination with VIBE, (ii) investigate the effect of radiologist’s experience in the sequence’s performance, and (iii) analyze causes of discordants results. Methods Four hundred seventy-three 3T MRI scans were retrospectively analyzed following a monocentric study design. Two studies were formed: one including SPACE alone and one combining both sequences (SPACE + VIBE, the reference). An experienced neuroradiologist and a radiology trainee independently reviewed the images of each study and reported the number of brain metastases. The sensitivity (Se) and specificity (Sp) of SPACE compared to SPACE + VIBE in metastases detection were reported. Diagnostic accuracy of SPACE compared to SPACE + VIBE was assessed by using McNemar’s test. Significance was set at p  < 0.05. Cohen’s kappa was used for inter-method and inter-observer variability. Results No significant difference was found between the two methods, with SPACE having a Se > 93% and a Sp > 87%. No effect of readers’ experience was disclosed. Conclusion Independently of radiologist’s experience, SPACE alone is robust enough to replace SPACE + VIBE for brain metastases detection.

BackgroundThe added-value of systematic biopsy (SB) in patients undergoing magnetic resonance imaging (MRI)-targeted biopsy (TB) remains unclear and the spatial distribution of positive cores relative to the MRI lesion has been poorly studied. The aim of this study was to determine the utility of perilesional biopsy in detecting clinically significant prostate cancer (csPCa).MethodsWe enrolled 505 consecutive patients that underwent SB and TB for suspicious MRI lesions (PI-RADS score 3-5) at Jules Bordet Institute between June 2016 and January 2022. Patient-specific tridimensional prostate maps were reviewed to determine the distance between systematic cores containing csPCa and the MRI index lesion. Primary outcomes were the cancer detection rate (CDR) per patient and the cumulative cancer distribution rate of positive cores for each 5 mm interval from the MRI index lesion. The secondary outcome was the identification of risk groups for the presence of csPCa beyond a 10 mm margin using the chi-square automated interaction detector (CHAID) machine learning algorithm.ResultsOverall, the CDR for csPCa of TB, SB, and combined method were 32%, 25%, and 37%, respectively. While combined method detected more csPCa compared to TB (37% vs. 32%, p < 0.001), no difference was found when TB was associated with perilesional sampling within 10 mm (37% vs. 35%, p = 0.2). The cumulative cancer distribution rate for csPCa reached 86% for the 10 mm margin. The CHAID algorithm identified three risk groups: (1) PI-RADS3 (“low-risk”), (2) PI-RADS4 or PI-RADS5 and PSA density <0.15 ng/ml (“intermediate-risk”), and (3) PI-RADS 5 and PSA density ≥0.15 ng/ml (“high-risk”). The risk of missing csPCa was 2%, 8%, and 29% for low-, intermediate- and high-risk groups, respectively. Avoiding biopsies beyond a 10 mm margin prevented the detection of 19% of non-csPCa.ConclusionsPerilesional biopsy template using a 10 mm margin seems a reasonable alternative to the combined method with a comparable detection of csPCa. Our risk stratification may further enhance the selection of patients.

Background Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified through multiparametric magnetic resonance imaging (mpMRI), present a clinical challenge due to their equivocal nature in predicting clinically significant prostate cancer (csPCa). Aim of the study is to improve risk stratification of patients with PI-RADS 3 lesions and candidates for prostate biopsy. Methods A cohort of 4841 consecutive patients who underwent MRI and subsequent MRI-targeted and systematic biopsies between January 2016 and April 2023 were retrospectively identified from independent prospectively maintained database. Only patients who have PI-RADS 3 lesions were included in the final analysis. A multivariable logistic regression analysis was performed to identify covariables associated with csPCa defined as International Society of Urological Pathology (ISUP) grade group ≥2. Performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Significant predictors were then selected for further exploration using a Chi-squared Automatic Interaction Detection (CHAID) analysis. Results Overall, 790 patients had PI-RADS 3 lesions and 151 (19%) had csPCa. Significant associations were observed for age (OR: 1.1 [1.0–1.1]; p  = 0.01) and PSA density (OR: 1643 [2717–41,997]; p  < 0.01). The CHAID analysis identified PSAd as the sole significant factor influencing the decision tree. Cut-offs for PSAd were 0.13 ng/ml/cc (csPCa detection rate of 1% vs. 18%) for the two-nodes model and 0.09 ng/ml/cc and 0.16 ng/ml/cc for the three-nodes model (csPCa detection rate of 0.5% vs. 2% vs. 17%). Conclusions For individuals with PI-RADS 3 lesions on prostate mpMRI and a PSAd below 0.13, especially below 0.09, prostate biopsy can be omitted, in order to avoid unnecessary biopsy and overdiagnosis of non-csPCa.

Purpose Utility of prostate-specific antigen density (PSAd) for risk-stratification to avoid unnecessary biopsy remains unclear due to the lack of standardization of prostate volume estimation. We evaluated the impact of ellipsoidal formula using multiparametric magnetic resonance (MRI) and semi-automated segmentation using tridimensional ultrasound (3D-US) on prostate volume and PSAd estimations as well as the distribution of patients in a risk-adapted table of clinically significant prostate cancer (csPCa). Methods In a prospectively maintained database of 4841 patients who underwent MRI-targeted and systematic biopsies, 971 met inclusions criteria. Correlation of volume estimation was assessed by Kendall’s correlation coefficient and graphically represented by scatter and Bland–Altman plots. Distribution of csPCa was presented using the Schoots risk-adapted table based on PSAd and PI-RADS score. The model was evaluated using discrimination, calibration plots and decision curve analysis (DCA). Results Median prostate volume estimation using 3D-US was higher compared to MRI (49cc[IQR 37–68] vs 47cc[IQR 35–66], p  < 0.001). Significant correlation between imaging modalities was observed (τ = 0.73[CI 0.7–0.75], p  < 0.001). Bland–Altman plot emphasizes the differences in prostate volume estimation. Using the Schoots risk-adapted table, a high risk of csPCa was observed in PI-RADS 2 combined with high PSAd, and in all PI-RADS 4–5. The risk of csPCa was proportional to the PSAd for PI-RADS 3 patients. Good accuracy (AUC of 0.69 and 0.68 using 3D-US and MRI, respectively), adequate calibration and a higher net benefit when using 3D-US for probability thresholds above 25% on DCA. Conclusions Prostate volume estimation with semi-automated segmentation using 3D-US should be preferred to the ellipsoidal formula (MRI) when evaluating PSAd and the risk of csPCa.

Purpose Magnetic resonance imaging (MRI) is a promising tool for risk assessment, potentially reducing the burden of unnecessary prostate biopsies. Risk prediction models that incorporate MRI data have gained attention, but their external validation and comparison are essential for guiding clinical practice. The aim is to externally validate and compare risk prediction models for the diagnosis of clinically significant prostate cancer (csPCa). Methods A cohort of 4606 patients across fifteen European tertiary referral centers were identified from a prospective maintained database between January 2016 and April 2023. Transrectal or transperineal image-fusion MRI-targeted and systematic biopsies for PI-RADS score of ≥ 3 or ≥ 2 depending on patient characteristics and physician preferences. Probabilities for csPCa, defined as International Society of Urological Pathology (ISUP) grade ≥ 2, were calculated for each patients using eight models. Performance was characterized by area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Subgroup analyses were performed across various clinically relevant subgroups. Results Overall, csPCa was detected in 2154 (47%) patients. The models exhibited satisfactory performance, demonstrating good discrimination (AUC ranging from 0.75 to 0.78, p  < 0.001), adequate calibration, and high net benefit. The model described by Alberts showed the highest clinical utility for threshold probabilities between 10 and 20%. Subgroup analyses highlighted variations in models’ performance, particularly when stratified according to PSA level, biopsy technique and PI-RADS version. Conclusions We report a comprehensive external validation of risk prediction models for csPCa diagnosis in patients who underwent MRI-targeted and systematic biopsies. The model by Alberts demonstrated superior clinical utility and should be favored when determining the need for a prostate biopsy.

PurposeThere is currently no consensus regarding the optimal number of multiparametric magnetic resonance imaging (MRI)-targeted biopsy (TB) cores and their spatial distribution within the MRI lesion. We aim to determine the number of TB cores and location needed to adequately detect csPCa.MethodsWe conducted a retrospective cohort study of 505 consecutive patients undergoing TB for positive MRI lesions defined by a PI-RADS score ≥ 3 between June 2016 and January 2022. Cores chronology and locations were prospectively recorded. The co-primary outcomes were the first core to detect clinically significant prostate cancer (csPCa) and the first highest ISUP grade group. The incremental benefit of each additional core was evaluated. Analysis was then performed by distinguishing central (cTB) and peripheral (pTB) within the MRI lesion.ResultsOverall, csPCa was detected in 37% of patients. To reach a csPCa detection rate of 95%, a 3-core strategy was required, except for patients with PI-RADS 5 lesions and those with PSA density ≥ 0.2 ng/ml/cc who benefited from a fourth TB core. At multivariable analysis, only a PSA density ≥ 0.2 ng/ml/cc was an independent predictive factor of having the highest ISUP grade group on the fourth TB cores (p = 0.03). No significant difference in the cancer detection rate was found between cTB and pTB (p = 0.9). Omitting pTB would miss 18% of all csPCa.ConclusionA 3-core strategy should be considered for TB to optimize csPCa detection with additional cores needed for PI-RADS 5 lesions and high PSA density. Biopsy cores from both central and peripheral zones are required.