Molecular analysis using SalvGlandDx improves risk of malignancy estimation and diagnosis of salivary gland cytopathology: An exploratory multicenter study

BACKGROUND

Diagnosis of salivary gland neoplasms is challenging, especially on cytological specimens acquired by fine-needle aspiration. The recently implemented standardized Milan system for reporting salivary gland cytopathology provides an estimated risk of malignancy (ROM); yet, for two of the categories, the diagnosis of the lesion remains unclear. However, a precise diagnosis is desirable for optimal patient management, including planning of surgery and imaging procedures.

METHODS

Cytological specimens (n = 106) were subjected to molecular analysis using the SalvGlandDx panel. The risk of malignancy was calculated for each detected alteration based on the diagnosis of the resection specimen. By taking into account the molecular alterations, their associated ROM, the clinical and cytological features, and the current literature, the Milan category was evaluated.

RESULTS

Of n = 63 technically valid cases, 76% revealed a molecular alteration. A total of 94% of these molecularly altered cases could be assigned to a different Milan category when additionally taking molecular results into account. In only 2% of the salivary gland neoplasms of uncertain malignant potential, in which a molecular alteration was detected, the classification remained salivary gland neoplasms of uncertain malignant potential.

CONCLUSION

Molecular analysis of cytological specimens provides a benefit in classifying salivary gland neoplasms on fine-needle aspiration. It can improve the ROM estimation and thus help to assign cases of formerly unknown malignant potential to clearly benign or malignant categories.

Inflammation in acute myocardial infarction: the good, the bad and the ugly

Convergent experimental and clinical evidence have established the pathophysiological importance of pro-inflammatory pathways in coronary artery disease. Notably, the interest in treating inflammation in patients suffering acute myocardial infarction (AMI) is now expanding from its chronic aspects to the acute setting. Few large outcome trials have proven the benefits of anti-inflammatory therapies on cardiovascular outcomes by targeting the residual inflammatory risk (RIR), i.e. the smouldering ember of low-grade inflammation persisting in the late phase after AMI. However, these studies have also taught us about potential risks of anti-inflammatory therapy after AMI, particularly related to impaired host defence. Recently, numerous smaller-scale trials have addressed the concept of targeting a deleterious flare of excessive inflammation in the early phase after AMI. Targeting different pathways and implementing various treatment regimens, those trials have met with varied degrees of success. Promising results have come from those studies intervening early on the interleukin-1 and -6 pathways. Taking lessons from such past research may inform an optimized approach to target post-AMI inflammation, tailored to spare 'The Good' (repair and defence) while treating 'The Bad' (smouldering RIR) and capturing 'The Ugly' (flaming early burst of excess inflammation in the acute phase). Key constituents of such a strategy may read as follows: select patients with large pro-inflammatory burden (i.e. large AMI); initiate treatment early (e.g. ≤12 h post-AMI); implement a precisely targeted anti-inflammatory agent; follow through with a tapering treatment regimen. This approach warrants testing in rigorous clinical trials.

Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system

To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated "sufficient image quality" and 117 images rated "insufficient image quality". The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Quantification of perivascular inflammation does not provide incremental prognostic value over myocardial perfusion imaging and calcium scoring

Aims

Perivascular fat attenuation index (FAI) has emerged as a novel coronary computed tomography angiography (CCTA)–based biomarker predicting cardiovascular outcomes by capturing early coronary inflammation. It is currently unknown whether FAI adds prognostic value beyond that provided by single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) and CCTA findings including coronary artery calcium scoring (CACS).

Methods and results

A total of 492 patients (mean age 62.5 ± 10.8 years) underwent clinically indicated multimodality CCTA and electrocardiography (ECG)-gated ^99mTc-tetrofosmin SPECT-MPI between May 2005 and December 2008 at our institution, and follow-up data on major adverse cardiovascular events (MACE) was obtained for 314 patients. FAI was obtained from CCTA images and was measured around the right coronary artery (FAI[RCA]), the left anterior descending artery (FAI[LAD]), and the left main coronary artery (FAI[LMCA]). During a median follow-up of 2.7 years, FAI[RCA] > − 70.1 was associated with an increased rate of MACE (log rank p = 0.049), while no such association was seen for FAI[LAD] or FAI[LMCA] (p = NS). A multivariate Cox regression model accounting for cardiovascular risk factors, CCTA and SPECT-MPI findings identified FAI[RCA] as an independent predictor of MACE (HR 2.733, 95% CI: 1.220–6.123, p = 0.015). However, FAI[RCA] was no longer a significant predictor of MACE after adding CACS (p = 0.279). A first-order interaction term consisting of sex and FAI[RCA] was significant in both models (HR 2.119, 95% CI: 1.218–3.686, p = 0.008; and HR 2.071, 95% CI: 1.111–3.861, p = 0.022).

Conclusion

FAI does not add incremental prognostic value beyond multimodality MPI/CCTA findings including CACS. The diagnostic value of FAI[RCA] is significantly biased by sex.

Improved oncological outcome after radical prostatectomy in patients staged with 68Ga-PSMA-11 PET: a single-center retrospective cohort comparison

BACKGROUND

Positron emission tomography (PET) targeting the prostate-specific membrane antigen (PSMA) has superior sensitivity over conventional imaging (CI) to stage prostate cancer (PCa) and therefore is increasingly used in staging to stratify patients before radical therapy. Whether this improved diagnostic accuracy translates into improved outcome after radical prostatectomy (RPE) has not yet been shown. Therefore, the aim of this study was to compare the oncological outcome after RPE between patients that underwent preoperative staging with CI or PSMA-PET for intermediate and high-risk PCa.

METHODS

We retrospectively selected all patients that underwent RPE for intermediate- or high-risk PCa at our institution before PSMA-PET introduction (between March 2014 and September 2016) and compared the oncologic outcome of patients staged with PSMA-PET (between October 2016 and October 2018). Oncological pre-surgical risk parameters (age, PSA, D'Amico score, biopsy-ISUP, and cT stage) were compared between the groups. Oncological outcome was determined as PSA persistence, nerve-sparing rate, and surgical margin status. Wilcoxon rank-sum, Fisher's, and chi-square tests where used for statistical testing.

RESULTS

One hundred five patients were included, 53 in the CI group and 52 in the PSMA-group. Patients in the PSMA group had higher ISUP grade (p < 0.001) and D'Amico score (p < 0.05). The rate of free surgical margins and PSA persistence after RPE was 64% and 17% for the CI and 77% and 6% for the PSMA group (p = 0.15 and 0.13, respectively). Subgroup analysis with high-risk patients revealed PSA persistence in 7% (3/44) in the PSMA group and 25% (7/28) in the CI group (p = 0.04). Limitations include the retrospective design and choline-PET for some patients in the CI group.

CONCLUSION

Immediate outcome after RPE was not worse in the PSMA group compared with the CI group, despite a higher-risk cohort. In a comparison of only high-risk patients, PSMA-PET staging was associated with a significantly lower rate of postsurgical PSA persistence.