Background: The hippocampus is an important limbic structure closely related to memory function. However, few studies have focused on the association between hippocampal subfields and age-related memory decline. We investigated the volume alterations of hippocampal subfields at different ages and assessed the correlations with Immediate and Delayed recall abilities. Materials and Methods: A total of 275 participants aged 20–89 years were classified into 4 groups: Young, 20–35 years; Middle-early, 36–50 years; Middle-late, 51–65 years; Old, 66–89 years. All data were acquired from the Dallas Lifespan Brain Study (DLBS). The volumes of hippocampal subfields were obtained using Freesurfer software. Analysis of covariance (ANCOVA) was performed to analyze alterations of subfield volumes among the 4 groups, and multiple comparisons between groups were performed using the Bonferroni method. Spearman correlation with false discovery rate correction was used to investigate the relationship between memory recall scores and hippocampal subfield volumes. Results: Apart from no significant difference in the left parasubiculum (P = 0.269) and a slight difference in the right parasubiculum (P = 0.022), the volumes of other hippocampal subfields were significantly different across the adult lifespan (P < 0.001). The hippocampal fissure volume was increased in the Old group, while volumes for other subfields decreased. In addition, Immediate recall scores were associated with volumes of the bilateral molecular layer, granule cell layer of the dentate gyrus (GC-DG), cornus ammonis (CA) 1, CA2/3, CA4, left fimbria and hippocampal amygdala transition area (HATA), and right fissure (P < 0.05). Delayed recall scores were associated with the bilateral molecular layer, GC-DG, CA2/3 and CA4; left tail, presubiculum, CA1, subiculum, fimbria and HATA (P < 0.05). Conclusion: The parasubiculum volume was not significantly different across the adult lifespan, while atrophy in dementia patients in some studies. Based on these findings, we speculate that volume changes in this region might be considered as a biomarker for dementia disorders. Additionally, several hippocampal subfield volumes were significantly associated with memory scores, further highlighting the key role of the hippocampus in age-related memory decline. These regions could be used to assess the risk of memory decline across the adult lifespan.

Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung cancer and possible recurrences upon completion of treatment. Radiomics, an emerging noninvasive technology using medical imaging analysis and data mining methodology, has been adopted to the area of cancer diagnostics in recent years. Its potential application in response assessment for cancer treatment has also drawn considerable attention. Radiomics seeks to extract a large amount of valuable information from patients’ medical images (both pretreatment and follow-up images) and quantitatively correlate image features with diagnostic and therapeutic outcomes. Radiomics relies on computers to identify and analyze vast amounts of quantitative image features that were previously overlooked, unmanageable, or failed to be identified (and recorded) by human eyes. The research area has been focusing on the predictive accuracy of pretreatment features for outcome and response and the early discovery of signs of tumor response, recurrence, distant metastasis, radiation-induced lung injury, death, and other outcomes, respectively. This review summarized the application of radiomics in response assessments in radiotherapy and chemotherapy for non-small cell lung cancer, including image acquisition/reconstruction, region of interest definition/segmentation, feature extraction, and feature selection and classification. The literature search for references of this article includes PubMed peer-reviewed publications over the last 10 years on the topics of radiomics, textural features, radiotherapy, chemotherapy, lung cancer, and response assessment. Summary tables of radiomics in response assessment and treatment outcome prediction in radiation oncology have been developed based on the comprehensive review of the literature.

Background: Breast imaging technology plays an important role in breast cancer planning and treatment. Recently, three-dimensional (3D) printing technology has become a trending issue in phantom constructions for medical applications, with its advantages of being customizable and cost-efficient. However, there is no current practice in the field of multi-purpose breast phantom for quality control (QC) in multi-modalities imaging. The purpose of this study was to fabricate a multi-purpose breast phantom with tissue-equivalent materials via a 3D printing technique for QC in multi-modalities imaging. Methods: We used polyvinyl chloride (PVC) based materials and a 3D printing technique to construct a breast phantom. The phantom incorporates structures imaged in the female breast such as microcalcifications, fiber lesions, and tumors with different sizes. Moreover, the phantom was used to assess the sensitivity of lesion detection, depth resolution, and detectability thresholds with different imaging modalities. Phantom tissue equivalent properties were determined using computed tomography (CT) attenuation [Hounsfield unit (HU)] and magnetic resonance imaging (MRI) relaxation times. Results: The 3D-printed breast phantom had an average background value of 36.2 HU, which is close to that of glandular breast tissue (40 HU). T1 and T2 relaxation times had an average relaxation time of 206.81±17.50 and 20.22±5.74 ms, respectively. Mammographic imaging had improved detection of microcalcification compared with ultrasound and MRI with multiple sequences [T1WI, T2WI and short inversion time inversion recovery (STIR)]. Soft-tissue lesion detection and cylindrical tumor contrast were superior with mammography and MRI compared to ultrasound. Hemispherical tumor detection was similar regardless of the imaging modality used. Conclusions: We developed a multi-purpose breast phantom using a 3D printing technique and determined its value for multi-modal breast imaging studies.

Background and Objective: Terahertz (THz) imaging has wide applications in biomedical research due to its properties, such as non-ionizing, non-invasive and distinctive spectral fingerprints. Over the past 6 years, the application of THz imaging in tumor tissue has made encouraging progress. However, due to the strong absorption of THz by water, the large size, high cost, and low sensitivity of THz devices, it is still difficult to be widely used in clinical practice. This paper provides ideas for researchers and promotes the development of THz imaging in clinical research. Methods: The literature search was conducted in the Web of Science and PubMed databases using the keywords “Terahertz imaging”, “Breast”, “Brain”, “Skin” and “Cancer”. A total of 94 English language articles from 1 January, 2017 to 30 December, 2022 were reviewed. Key Content and Findings: In this review, we briefly introduced the recent advances in THz near-field imaging, single-pixel imaging and real-time imaging, the applications of THz imaging for detecting breast, brain and skin tissues in the last 6 years were reviewed, and the advantages and existing challenges were identified. It is necessary to combine machine learning and metamaterials to develop real-time THz devices with small size, low cost and high sensitivity that can be widely used in clinical practice. More powerful THz detectors can be developed by combining graphene, designing structures and other methods to improve the sensitivity of the devices and obtain more accurate information. Establishing a THz database is one of the important methods to improve the repeatability and accuracy of imaging results. Conclusions: THz technology is an effective method for tumor imaging. We believe that with the joint efforts of researchers and clinicians, accurate, real-time, and safe THz imaging will be widely applied in clinical practice in the future.