Eruption guidance of horizontally angulated, distally displaced mandibular second premolars: Three case reports

AIM

An improperly positioned tooth germ can lead to tooth impaction, damage to adjacent teeth, and loss of arch integrity. This report describes three cases of eruption guidance of developing mandibular second premolars (MnP2) that were horizontally angulated and displaced to the distal side of the roots of the second primary molars.

CASE REPORT

The primary second molars were extracted when root formation of the succeeding premolar began. Surgical exposure was performed to accelerate eruption. These two procedures led to spontaneous eruption of all premolars. In the last case, however, a displaced second premolar disturbed the eruption of the first molar into the occlusal plane.

CONCLUSIONS

Several factors should be considered for an optimal treatment approach, including the clinical eruption status, development of the root MnP2, and effect on the mandibular first molar.

Abstract P4-09-06: Analyzing the changes in the HR+/HER2- metastatic breast cancer (mBC) landscape since the arrival of CDK4/6 inhibitors with machine learning and visual analytics

BACKGROUND: The real-world impact of CDK4/6 inhibitor use on HR+/HER2- mBC treatment sequencing, treatment response, and therapeutic utilization is limited. This study sought to describe treatment sequencing and response pre- and post-FDA approval of CDK4/6 inhibitors by conducting a traditional observational study approach and supplementing with a machine-learning methodology.

METHODS: Female patients ≥18yrs were identified in the MarketScan Commercial and Medicare Supplement databases with continuous enrollment for at least 12 months pre-index, ≥2 medical claims for a BC diagnosis and ≥2 medical claims for metastatic disease (earliest=index date), and who had no treatment at any time with HER2 targeted therapy. Patients were excluded if they had received CDK4/6 or everolimus treatment prior to index. Treatment was stratified by line of therapy pre- and post- first CDK4/6 approval (February 3, 2015). We identified treatment patterns with standard distributions and visual analytics. Response to therapy and utilization was analyzed with prediction models and IBM Watson® machine learning population comparison models.

RESULTS: A total of 19,558 patients were eligible for the study with a mean age at diagnosis of mBC of 62 (SD 13). Prior to first CDK4/6 inhibitor approval, anastrazole and letrozole monotherapies were most likely to be identified as both first and second line treatment. Following approval of the first CDK4/6 inhibitor in 2015, CDK4/6 inhibitors were observed as a first line treatment in 25% of patients, and as second line treatment in 24% of patients. Of patients diagnosed following the first CDK4/6 inhibitor approval, 44% of patients were exposed to endocrine therapy and 10% were exposed to chemotherapy in the pre-index period. Patients receiving CDK4/6 inhibitors in combination with endocrine therapy as first line treatment were observed to have a longer progression free survival time than patients receiving endocrine monotherapy. Visual analytics demonstrate a large variation in treatment sequencing, especially after first line therapy. Machine learning and prediction models identified a strong secular bias in the use of CDK4/6 and a signal for improved treatment response in patients with no exposure to endocrine therapies in the pre-index period.

CONCLUSIONS: The mBC treatment landscape has changed significantly with the introduction of CDK4/6 inhibitors, which may be expected to impact long-term outcomes. Visual analytics and machine learning approaches can improve clinical insight. These approaches can help with identifying patient and clinical characteristics that predict response and utilization as well as appropriate treatment selections across lines of therapy.

Citation Format: Meade D, Hensley Alford S, Mahatma S, Malangone-Monaco E, Boulanger L, Tkacz J, Turner SJ, Chen S, Manson S, Mejia S, Buleje I, Madan P, Kim G, Fowler R, Basar A. Analyzing the changes in the HR+/HER2- metastatic breast cancer (mBC) landscape since the arrival of CDK4/6 inhibitors with machine learning and visual analytics [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-09-06.

A data-driven analysis of the knowledge structure of library science with full-text journal articles

In previous studies, full-text analyses and mining techniques have not been combined to identify and trace changes in the knowledge trends of library science over the past 20 years (1997–2016). Thus, to grasp the knowledge trends of library science at a fine-grained level, this study analyzes full-text journal articles from six top-ranked library science journals by applying text-mining techniques such as co-word analysis, text summarization, and topic modeling. Visualization tools were used to map the knowledge structure of library science. The findings indicate that, during the past 20 years, library science has developed into an interdisciplinary knowledge structure that integrates librarianship topics with a range of other fields, generating major topics that include the academic library, the digital library, research methodology, library marketing, information retrieval, digital information, document citation, and so on. In the past ten years, the library science discipline has focused increasingly on research methodology and evaluation and become more concerned with digital information management.

A new software scheme for scatter correction based on a simple radiographic scattering model

In common radiography, image contrast is often limited due mainly to scattered x-rays and noise, decreasing the quantitative usefulness of x-ray images. Several scatter reduction methods based on software correction schemes have been extensively investigated in an attempt to overcome these difficulties, most of which are based on measurement, mathematical-physical modeling, or a combination of both. However, those methods require special equipment, system geometry, and extra manual work to measure scatter characteristics. In this study, we investigated a new software scheme for scatter correction based on a simple radiographic scattering model where the intensity of the scattered x-rays was directly estimated from a single x-ray image using a weighted l¹-norm contextual regularization framework. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. We also conducted some clinical image studies using patient's image data of breast and L-spine to verify the clinical effectiveness of the proposed scheme. Our results indicate that the degradation of image characteristics by scattered x-rays and noise was effectively recovered by using the proposed software scheme, thus improving radiographic visibility considerably. Graphical abstract The schematic illustrations of scatter suppression methods by using a an antiscatter grid and b a scatter estimation algorithm.

Prominent microglial activation in cortical white matter is selectively associated with cortical atrophy in primary progressive aphasia

AIMS

Primary progressive aphasia (PPA) is a clinical syndrome characterized by selective language impairments associated with focal cortical atrophy favouring the language dominant hemisphere. PPA is associated with Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) and significant accumulation of activated microglia. Activated microglia can initiate an inflammatory cascade that may contribute to neurodegeneration, but their quantitative distribution in cortical white matter and their relationship with cortical atrophy remain unknown. We investigated white matter activated microglia and their association with grey matter atrophy in 10 PPA cases with either AD or FTLD-TDP pathology.

METHODS

Activated microglia were quantified with optical density measures of HLA-DR immunoreactivity in two regions with peak cortical atrophy, and one nonatrophied region within the language dominant hemisphere of each PPA case. Nonatrophied contralateral homologues of the language dominant regions were examined for hemispheric asymmetry.

RESULTS

Qualitatively, greater densities of activated microglia were observed in cortical white matter when compared to grey matter. Quantitative analyses revealed significantly greater densities of activated microglia in the white matter of atrophied regions compared to nonatrophied regions in the language dominant hemisphere (P < 0.05). Atrophied regions of the language dominant hemisphere also showed significantly more activated microglia compared to contralateral homologues (P < 0.05).

CONCLUSIONS

White matter activated microglia accumulate more in atrophied regions in the language dominant hemisphere of PPA. While microglial activation may constitute a response to neurodegenerative processes in white matter, the resultant inflammatory processes may also exacerbate disease progression and contribute to cortical atrophy.

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping

BACKGROUND AND PURPOSE

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology.

MATERIALS AND METHODS

Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident.

RESULTS

Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping.

CONCLUSIONS

Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury.