First-line palliative systemic therapy alternated with oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy for unresectable colorectal peritoneal metastases: A single-arm phase II trial (CRC-PIPAC-II).

Background: Palliative systemic therapy alternated with electrostatic precipitation oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy (ePIPAC) has never been prospectively investigated in patients with unresectable colorectal peritoneal metastases (CPM). The CRC-PIPAC-II study aimed to assess safety, feasibility and efficacy of such bidirectional therapy.

Methods: This two-center, single-arm, phase II trial enrolled chemotherapy-naïve patients to undergo three treatment cycles, consisting of systemic therapy (CAPOX, FOLFOX, FOLFIRI, or FOLFOXIRI, all with bevacizumab) and oxaliplatin-based ePIPAC (92 mg/m) with intravenous leucovorin (20 mg/m) and 5-fluorouracil (400 mg/m).

The additional value of Ga-PSMA PET/CT SUVmax in predicting ISUP GG ≥ 2 and ISUP GG ≥ 3 prostate cancer in biopsy.

Background: Prebiopsy magnetic resonance imaging (MRI) increases the detection rate of clinically significant prostate cancer (csPCa). Prostate-specific membrane antigen-positron emission tomography/computed tomography (PSMA PET/CT) maximum standardized uptake value (SUVmax) of the prostate may offer additional value in predicting the likelihood of csPCa in biopsy.

Methods: A single-center cohort study involving patients with biopsy-proven PCa who underwent both MRI and PSMA PET/CT between 2020 and 2021.

Sleep in the intensive and intermediate care units: Exploring related factors of delirium, benzodiazepine use and mortality.

Aim Of The Study: The primary purpose was to examine sleep difficulties and delirium in the Intensive and Intermediate Care Unit. Secondarily, factors impacting night-time sleep duration and quality, mortality, and the impact of benzodiazepine use on sleep outcomes were investigated.

Materials And Methods: This retrospective study encompassed data from 323 intensive and intermediate care unit admissions collected in the Netherlands, spanning from November 2018 to May 2020.

Automated pelvic MRI measurements associated with urinary incontinence for prostate cancer patients undergoing radical prostatectomy.

Background: Pelvic morphological parameters on magnetic resonance imaging (MRI), such as the membranous urethral length (MUL), can predict urinary incontinence after radical prostatectomy but are prone to interobserver disagreement. Our objective was to improve interobserver agreement among radiologists in measuring pelvic parameters using deep learning (DL)-based segmentation of pelvic structures on MRI scans.

Methods: Preoperative MRI was collected from 167 prostate cancer patients undergoing radical prostatectomy within our regional multicentric cohort.

The Development and External Validation of Artificial Intelligence-Driven MRI-Based Models to Improve Prediction of Lesion-Specific Extraprostatic Extension in Patients with Prostate Cancer.

Adequate detection of the histopathological extraprostatic extension (EPE) of prostate cancer (PCa) remains a challenge using conventional radiomics on 3 Tesla multiparametric magnetic resonance imaging (3T mpMRI). This study focuses on the assessment of artificial intelligence (AI)-driven models with innovative MRI radiomics in predicting EPE of prostate cancer (PCa) at a lesion-specific level. With a dataset encompassing 994 lesions from 794 PCa patients who underwent robot-assisted radical prostatectomy (RARP) at two Dutch hospitals, the study establishes and validates three classification models.