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Related Concept Videos

Metallic Solids02:37

Metallic Solids

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Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
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Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
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Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
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Particles in a solid are tightly packed together (fixed shape) and often arranged in a regular pattern; in a liquid, they are close together with no regular arrangement (no fixed shape); in a gas, they are far apart with no regular arrangement (no fixed shape). Particles in a solid vibrate about fixed positions (cannot flow) and do not generally move in relation to one another; in a liquid, they move past each other (can flow) but remain in essentially constant contact; in a gas, they move...
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Volumes of Solids of Revolution

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Volumes of irregularly shaped objects can be systematically determined using the concept of solids of revolution. This approach begins with a region defined by a curve in a two-dimensional plane. When this region is rotated about a fixed line, known as the axis of revolution, it generates a three-dimensional object with rotational symmetry. Such objects frequently arise in mathematical modeling, physics, and engineering applications.When the region being rotated lies directly against the axis...
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Computer-aided Volumetry of Part-Solid Lung Cancers by Using CT: Solid Component Size Predicts Prognosis.

Shinichiro Kamiya1, Shingo Iwano1, Hiroyasu Umakoshi1

  • 1From the Department of Radiology (S.K., S.I., H.U., R.I., H.S., Shinji Naganawa) and Department of Thoracic Surgery (Shota Nakamura), Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

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Three-dimensional (3D) solid volume (3D SV0HU) measured using CT volumetry software accurately predicts postoperative recurrence in part-solid non-small cell lung cancer patients. This imaging biomarker is more effective than 2D measurements for assessing prognosis.

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Part-solid non-small cell lung cancer (NSCLC) poses challenges in predicting postoperative prognosis.
  • Accurate assessment of tumor characteristics is crucial for effective treatment planning and patient outcomes.

Purpose of the Study:

  • To evaluate the relationship between the size of the solid component in part-solid NSCLC and postoperative prognosis.
  • To compare the predictive accuracy of three-dimensional (3D) volumetry measurements against traditional two-dimensional (2D) measurements for recurrence risk.

Main Methods:

  • A retrospective review of 96 patients with part-solid NSCLC who underwent preoperative multidetector computed tomography (CT).
  • Radiologists measured 2D maximal solid size (2D MSSA), 3D maximal solid size (3D MSSMPR), and 3D solid volume (3D SV0HU).
  • Cox proportional hazards models were used to assess correlations between imaging biomarkers, clinical/pathologic factors, and postoperative recurrence.

Main Results:

  • The 3D solid volume (3D SV0HU) demonstrated the highest area under the receiver operating characteristic curve (0.835) for predicting recurrence, outperforming 2D MSSA (0.796) and 3D MSSMPR (0.776).
  • An optimal cutoff of 0.54 cm³ for 3D SV0HU predicted recurrence with 93.3% sensitivity and 71.6% specificity.
  • Significant predictors of disease-free survival included 3D SV0HU ≥ 0.54 cm³ (HR, 6.61) and lymphatic/vascular invasion (HR, 2.96).

Conclusions:

  • Three-dimensional solid volume (3D SV0HU) measured by CT volumetry is a superior imaging biomarker for predicting postoperative prognosis in part-solid NSCLC.
  • This quantitative 3D measurement offers improved accuracy over 2D assessments for identifying patients at higher risk of recurrence.