The usefulness of measuring n-butyric acid concentration as a new indicator of blood decomposition in forensic autopsy

In forensic medicine, although various alcohols have been reported as indicators of decomposition in collected blood, no studies have examined short-chain fatty acids as indicators. In this study, the blood n-butyric acid concentration was quantified, and the association between n-butyric acid and decomposition was investigated to determine whether the detection of n-butyric acid could be a new indicator of decomposition. Among the forensic autopsies performed from 2016 to 2018 in our laboratory, the cases were divided into decomposed (n = 20) and non-decomposed (n = 20) groups based on macroscopic findings. Blood samples collected at the time of autopsy were derivatized with 3-nitrophenylhydrazine hydrochloride after solid-phase extraction. The n-butyric acid concentration was measured using liquid chromatography–tandem mass spectrometry. In addition, ethanol and n-propanol were measured using a gas chromatography-flame ionization detector. There was a significant difference (p < 0.01) in the concentrations of n-butyric acid between the decomposed and non-decomposed groups (0.343 ± 0.259 [0.030–0.973] and 0.003 ± 0.002 [0.001–0.007] mg/mL, respectively). In the decomposed group, n-butyric acid was detected at high concentrations, even in cases where n-propanol was low. These results suggest that n-butyric acid is more likely to be an indicator of blood decomposition than n-propanol.     

Future directions in managing aniridia-associated keratopathy

Congenital aniridia is a panocular disorder that is typically characterized by iris hypoplasia and aniridia-associated keratopathy (AAK). AAK results in the progressive loss of corneal transparency and thereby loss of vision. Currently, there is no approved therapy to delay or prevent its progression, and clinical management is challenging because of phenotypic variability and high risk of complications after interventions; however, new insights into the molecular pathogenesis of AAK may help improve its management. Here, we review the current understanding about the pathogenesis and management of AAK. We highlight the biological mechanisms involved in AAK development with the aim to develop future treatment options, including surgical, pharmacological, cell therapies, and gene therapies.     

Risk for Upgrade to Malignancy After Breast Core Needle Biopsy Diagnosis of Lobular Neoplasia: A Systematic Review and Meta-Analysis

PurposeLobular neoplasia (LN) detected on breast core needle biopsy is frequently managed with surgical excision because of concern for undersampled malignancy. The authors performed a systematic review and meta-analysis to estimate the risk for upgrade to malignancy in the setting of imaging-concordant classic LN diagnosed on core biopsy.MethodsPubMed and Embase were searched for original articles published from 1998 to 2020 that reported rates of upgrade to malignancy for classic LN, including atypical lobular hyperplasia (ALH) and classic lobular carcinoma in situ (LCIS). Two reviewers extracted study data and assessed the following quality criteria: exclusion of variant LCIS, exclusion of imaging-discordant lesions, and outcome reporting for ≥70% of lesions. For studies meeting all criteria, pooled risks for upgrade to any malignancy (invasive carcinoma or ductal carcinoma in situ) and invasive malignancy for all LN, ALH, and LCIS were estimated using random-effects models.ResultsFor 65 full-text articles included in the review, the risk for upgrade to any malignancy ranged from 0% to 45%. Among the 16 studies that met all quality criteria for the meta-analysis, pooled risks for upgrade to any malignancy were 3.1% (95% confidence interval [CI], 1.8%-5.2%) for all LN, 2.5% (95% CI, 1.6%-3.9%) for ALH, and 5.8% (95% CI, 2.9%-11.3%) for LCIS. Risks for upgrade to invasive malignancy were 1.3% (95% CI, 0.7%-2.4%) for all LN, 0.4% (95% CI, 0.0%-4.2%) for ALH, and 3.5% (95% CI, 2.0%-5.9%) for LCIS.ConclusionsThe risk for upgrade to malignancy for LN found on breast biopsy is low. Imaging surveillance can likely be offered as an alternative to surgical management for LN, particularly for ALH.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Beyond intraocular pressure: Optimizing patient-reported outcomes in glaucoma

Glaucoma, an irreversible blinding condition affecting 3–4% adults aged above 40 years worldwide, is set to increase with a rapidly aging global population. Raised intraocular pressure (IOP) is a major risk factor for glaucoma where the treatment paradigm is focused on managing IOP using medications, laser, or surgery regimens. However, notwithstanding IOP and other clinical parameters, patient-reported outcomes, including daily functioning, emotional well-being, symptoms, mobility, and social life, remain the foremost concerns for people being treated for glaucoma. These outcomes are measured using objective patient-centered outcome measures (PCOMs) and subjective patient-reported outcome measures (PROMs). Studies using PCOMs have shown that people with glaucoma have several mobility, navigational and coordination challenges; reading and face recognition deficits; and are slower in adapting to multiple real-world situations when compared to healthy controls. Similarly, studies have consistently demonstrated, using PROMs, that glaucoma substantially and negatively impacts on peoples’ self-reported visual functioning, mobility, independence, emotional well-being, self-image, and confidence in healthcare, compared to healthy individuals, particularly in those with late-stage disease undergoing a heavy treatment regimen. The patient-centred effectiveness of current glaucoma treatment paradigms is equivocal due to a lack of well-designed randomized controlled trials; short post-treatment follow-up periods; an inappropriate selection or availability of PROMs; and/or an insensitivity of currently available PROMs to monitor changes especially in patients with newly diagnosed early-stage glaucoma. We provide a comprehensive, albeit non-systematic, critique of the psychometric properties, limitations, and recent advances of currently available glaucoma-specific PCOMs and PROMs. Finally, we propose that item banking and computerized adaptive testing methods can address the multiple limitations of paper-pencil PROMs; customize their administration; and have the potential to improve healthcare outcomes for people with glaucoma.